Know4Car FoF IP - CORDIS · Know4Car FoF IP An Internet-based Collaborative Platform for Managing Manufacturing Knowledge ... 2.8 SYSTEM FOR TRACKING HUMAN OPERATIONS AND PERFORMANCE

Know4Car FoF IP

An Internet-based Collaborative Platform for Managing Manufacturing Knowledge

Contract Number : FoF-ICT-2011.7.4 - 284602

Project : Know4Car FoF IP

Project Start Date : 1st September 2011

Know4Car Consortium : Volvo Technology AB

SAP AG

University Of Patras – LMS

Centro Ricerche Fiat SCPA

Karlsruhe Institute of Technology

Fundacion TECNALIA Research & Innovation

PDTec AG

Innovazione Automotive E Metalmeccanica SCRL

Chalmers University of Technology

EDAG GMBH & CO

BAZIGOS S.A.

D72.2 Exploitation report / Final version M51

Type : R Dissemination Level : Public (PU) Date of submission : 30.11.2015 Authors : IAM, SAP, PDTec, LMS Circulation : Know4Car FoF consortium, EU

Summary

Final version of the report on roadmap activities for integrating the Know4Car technologies in the industry’s working practices as well as exploitation activities and roles regarding the commercial

exploitation of the project's results including Intellectual Property Rights (IPR).

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Know4Car FoF FoF-ICT-2011.7.4 – 284602

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TABLE OF CONTENTS

ABBREVIATIONS LIST ....................................................................................................................................... 5

LIST OF TABLES ................................................................................................................................................ 6

LIST OF FIGURES .............................................................................................................................................. 7

1 INTRODUCTION ...................................................................................................................................... 8

2 KNOW4CAR EXPLOITATION STRATEGY ................................................................................................. 11

2.1 KNOW4CAR EXPLOITABLE RESULTS ................................................................................................................. 11 2.2 PACE – PLATFORM FOR CROSS-SUPPLY CHAIN ENGINEERING .............................................................................. 11

2.2.1 Description of the results .............................................................................................................. 11

2.2.2 Value proposition: innovation content of result and main benefit ............................................... 12

2.2.3 Market and distinguishable characteristics .................................................................................. 12

2.2.4 IPR and patents applications......................................................................................................... 14

2.3 ALTERNATIVE EXPLOITATION STRATEGIES AND ACTIVITIES RELATED TO THE KNOW4CAR COLLABORATION PLATFORM ....... 14 2.3.1 Custom development for the PACE platform ................................................................................ 15

2.3.2 SAP Engineering Design Network .................................................................................................. 15

2.3.3 Project execution ........................................................................................................................... 16

2.3.4 Fall-back exploitation plan for the Know4Car collaboration platform.......................................... 16

2.4 PRODUCT COST CALCULATION ........................................................................................................................ 19 2.4.1 Description of the results .............................................................................................................. 19



2.5 SQL BRIDGE – INTELLIGENT DATA MANAGEMENT FOR A SEAMLESS AND ROBUST DATA AVAILABILITY ............................ 20 2.5.1 Description of the result ................................................................................................................ 20



2.5.4 IPR and possible patents applications ........................................................................................... 21

2.6 CLOUD-BASED COLLABORATION PLATFORM....................................................................................................... 21 2.6.1 Description of the result ................................................................................................................ 21




2.7 AR SYSTEM (3 INTEGRATED MODULES): REGISTRATION – REMOTE ASSISTANCE – VISUALIZATION ............................... 24 2.7.1 Description of the result ................................................................................................................ 24




2.8 SYSTEM FOR TRACKING HUMAN OPERATIONS AND PERFORMANCE INDICATORS OF HUMAN OPERATORS ........................ 29 2.9 VARIABILITY MANAGEMENT TOOL ................................................................................................................... 29 2.10 MANUFACTURING KNOWLEDGE MANAGEMENT INFRASTRUCTURE INCLUDING KNOWLEDGE MODEL REGARDING PRODUCT, PROCESS, RESOURCE AND RELEVANT PARAMETERS (PPR) ............................................................................................. 31 2.11 LINE BALANCING AND OPTIMIZATION (ALB AND DES AGENT), INFORMATION EXTRACTION AGENT PLUS ASSEMBLY PRECEDENCE

DIAGRAM GENERATION SERVICE TO SUPPORT ENGINEERS WORK .................................................................................... 32 2.12 FOCUS ON END USERS EXPLOITATION PLAN ................................................................................................... 33

2.12.1 End users workshops ................................................................................................................ 33

2.13 SPECIFIC ACTIONS TO ADDRESS SMES ......................................................................................................... 37 2.13.1 Main results of the user’s feedback questionnaire – M26 ....................................................... 38

2.14 FOCUS ON ACADEMIC PARTNERS EXPLOITATION PLAN ..................................................................................... 39 2.15 POST-PROJECT EXPLOITATION ACTIONS ....................................................................................................... 39

Abbreviations List Page 4 of 120



3 EXPLOITATION EVALUATION STRATEGY ............................................................................................... 41

3.1 RISK ASSESSMENT STRICTLY RELATED TO EXPLOITATION ....................................................................................... 42

4 CONCLUSIONS ...................................................................................................................................... 45

APPENDIX A – QUESTIONNAIRE TO EUROPEAN SMES – END USERS' FEEDBACK QUESTIONNAIRE ................. 46

APPENDIX B – CATEGORIES CONTRIBUTING TO THE AR MARKET BY 2018 ..................................................... 50

APPENDIX C – FOCUS ON END USERS AND ACADEMIC PARTNERS’ EXPLOITATION PLANS ............................. 51

APPENDIX D – RESULTS FROM THE SECOND QUESTIONNAIRE SENT TO IAM’S PARTNERS ............................. 54

APPENDIX E – RESULTS FROM END-USERS WORKSHOP, DECEMBER 3, 2014 ................................................. 55

APPENDIX F – FINAL KEY EXPLOITABLE RESULTS REPORT .............................................................................. 57

ER1: PACE – PLATFORM FOR CROSS-SUPPLY CHAIN ENGINEERING ................................................................................ 57 ER2: PRODUCT COST CALCULATION ......................................................................................................................... 63 ER3: SQL BRIDGE ................................................................................................................................................ 68 ER4: CLOUD-BASED COLLABORATION PLATFORM ........................................................................................................ 73 ER5: FULL AR SYSTEM (3 INTEGRATED MODULES) ...................................................................................................... 78 ER6: SYSTEM FOR TRACKING HUMAN OPERATIONS + PERFORMANCE INDICATORS OF HUMAN OPERATORS ............................. 83 ER7: LINES BALANCING AND OPTIMIZATION (INCLUDING ALSO DES AGENT) ..................................................................... 88 ER8: SPECIAL AR TOOLS FOR TRAINING AND GUIDANCE OF ASSEMBLY PROCESSES .............................................................. 93 ER9: MANUFACTURING KNOWLEDGE MANAGEMENT INFRASTRUCTURE INCLUDING KNOWLEDGE MODEL REGARDING: PRODUCT, PROCESS, RESOURCE AND RELEVANT PARAMETERS (PPR) ........................................................................................................... 98 ER10: ASSEMBLY PRECEDENCE DIAGRAM GENERATION TOOL ..................................................................................... 103 ER11: INFORMATION EXTRACTION AGENT .............................................................................................................. 108 ER12: VARIABILITY MANAGEMENT TOOL ................................................................................................................ 113

GLOSSARY.................................................................................................................................................... 119

Page 5 of 120 Abbreviations List



ABBREVIATIONS LIST

Acronym Definition

3D Three Dimensional

ALB Assembly Line Balancing

APDG Assembly Precedence Diagram Generation

AR Augmented Reality

ATA Associazione Tecnica dell’Automobile (http://www.ata.it/en)

CAD Computer-Aided Design

CAM Computer-Aided Manufacturing

CAx Computer Aided (Design, Manufacturing, Engineering, …)

DES Decision Support

ER Exploitable Result

ERP Enterprise Resource Planning

GUI Graphic User Interface

HMI Human Machine Interaction (or Interface)

HW Hardware

ICT Information and Communication Technology

IP Intellectual Property

IPR Intellectual Property Rights

IT Information Technologies

KER Key Exploitable Result report

KM Knowledge Management

KPI Key Performance Indicators

OEM Original Equipment Manufacturer

PDM Product Data Management

PLM Product Lifecycle Management

PM Project Management

PPM Project Portfolio Management

PS Project System

R&D Research and Development

SCM Supply Chain Management

SME Small or Medium Enterprise

SP Sub-project

SPARQL SPARQL Protocol and RDF Query Language

SQL Structured Query Language

UI User Interface

List of Tables Page 6 of 120



LIST OF TABLES

Table 1: List of exploitable results and responsible partners .......................................................................... 11 Table 2: PACE SWOT analysis .......................................................................................................................... 12 Table 3: Essential features still missing in the Know4Car platform at the end of the project ........................ 18 Table 4: SQL Bridge SWOT analysis ................................................................................................................. 21 Table 5: Cloud-based collaboration platform SWOT analysis ......................................................................... 23 Table 6: AR system SWOT analysis .................................................................................................................. 26 Table 7: Agenda of Volvo End-users Workshop .............................................................................................. 34 Table 8: Integration Meeting@ CNH Agenda .................................................................................................. 34 Table 9: End-users workshop @ IAM – Final agenda ...................................................................................... 36 Table 10: Collected results of the last questionnaire ...................................................................................... 38 Table 11: Achievement indicators and their values ........................................................................................ 41 Table 12: Risks and mitigation actions related to exploitation ....................................................................... 42 Table 13: Categories contributing to the AR market by 2018 ......................................................................... 50 Table 14: End users exploitation focus ............................................................................................................ 51

Page 7 of 120 List of Figures



LIST OF FIGURES

Figure 1: Know4Car platform’s main components ............................................................................................ 8 Figure 3: PLM market forecast ........................................................................................................................ 14 Figure 4: Cause effect diagram for the direct exploitation ............................................................................. 17 Figure 5 Product Portfolio PDTec .................................................................................................................... 22 Figure 6: Sample output for Registration Module ........................................................................................... 24 Figure 7: Sample output for Visualization Module .......................................................................................... 25 Figure 8: AR market revenues for different areas – Forecast based on Smartech Market Publishing report 27 Figure 9: The five core markets for AR ($ millions revenue by 2018) ............................................................. 27 Figure 10: System for the evaluation of the training activities in the shop-floor ........................................... 29 Figure 11: Variability Agent Assisting the update of Ebom ............................................................................. 30 Figure 12: Automatically created mBOP ......................................................................................................... 31 Figure 13: Six step methodology used by the ASG agent ................................................................................ 32 Figure 14: Picture from the demonstration to CNH experts ........................................................................... 35 Figure 15: Picture of the discussion with CNH experts ................................................................................... 35 Figure 16: Pictures from the workshop @ IAM ............................................................................................... 37 Figure 17: Type of respondents #1 .................................................................................................................. 38 Figure 18: Type of respondents #2 .................................................................................................................. 38 Figure 19: Organization’s internal structure ................................................................................................... 54 Figure 20: Availability of a central repository for projects’ data ..................................................................... 54 Figure 21: Permission management to this repository ................................................................................... 54 Figure 22: Access to a specific customer’s data repository/database ............................................................ 54

Introduction Page 8 of 120



1 INTRODUCTION

The Know4Car platform is mainly composed by four principal components, which could be commercialized separately.

Figure 1: Know4Car platform’s main components.

SAP is the responsible partner for the development and commercialization of the Agent Core Component. After the end of the project SAP’s developments will be exploited under the Engineering Design Network. This will be an innovative in-the-cloud platform for engineering collaboration which will integrate project management, workflow and data access. The target market for such a product encompasses all those companies that do engineering in a collaborative fashion. Main competitors are other platform for in the cloud engineering collaboration, such as TeamPlatform and Dassaults’ EngineeredToFly. There are three patents which have been issued for PACE. The extended engineering component is the part of the platform which takes care of ways to distribute the product/production knowledge of manufacturing companies within a value-added supply chain amongst each other in a context-sensitive and thus sophisticated way. PDTec is the partner mainly responsible for the exploitation of such component, and in particular:

PDTec will exploit the SQL Bridge – Intelligent data management for a seamless and robust data availability, which is a tool supporting the integration of the K4C platform and other databases

Collaboration oriented specifications and software components, will be enhanced and shall become part of the PDTec ice.NET product suite, which will be offered on the market as a “cloud-based Collaboration Platform for supply chains”.

Solutions on the cloud are growing fast in the today’s market, as also shown in several market researches. Cloud computing has been revolutionizing the way business are run, especially in small and medium enterprise which cannot afford high investment costs and fee/licenses. The promise intra and inter enterprise-wide operability provides a solid base for leveraging these solutions in the whole product and process development life cycle. Furthermore, the cloud could be an appealing prospect to face some of the present day technology limitations in engineering collaboration. Both SAP and PDTec intend to target this market, where SAP is focused on supporting engineering collaboration by a combination of process support, social media and data storage, while PDTec focuses on supporting structured data exchange. PDTec, starting from its current customer portfolio, will try to extend it, gaining an advantage in competitiveness in the market concerning cloud solutions. LMS is responsible for the development of the Process Knowledge Component and some engineering and execution support tools, in particular:

Advanced simulation-based decision making agents;

Line balancing and optimization;

Page 9 of 120 Introduction



Special AR tools for training and validating manufacturing operations;

Manufacturing Knowledge Management infrastructure; a tool for knowledge management, which can be further divided into:

o Knowledge Management Interfaces o Ontology Synchronizer o KM Abstraction Layer

Being an official academic partner of 3DS-Delmia, LMS is allowed to develop 3DS custom tools, thus these tools could be integrated in standard digital manufacturing tools, offering additional exploitation channels. Regarding Advanced UIs and training component, partners in charge are TECNALIA and Chalmers. TECNALIA is responsible for the development of the AR Training Framework System which is able to detect, track and augment objects with virtual information without the use of fiducial markers. It is composed of 3 different modules:

1. AR Module for Registration, 2. AR Module for Visualization and 3. AR Module for Remote Assistance.

These three modules could be sold separately showing also a great flexibility in terms of field of application, offering important opportunity for exploitation almost in any kind of industry which has a production line. Chalmers is responsible for the tool dedicated to the tracking of human operations and performance indicators to evaluate the performance of the operators. The proposed solution is composed of three main modules, which act as distributed agents connected through an agent framework:

Human tracking module

Performance measurement module

Scenario module.

Industrial partners; Volvo, CRF, EDAG, IAM and BAZIGOS will also contribute to the exploitation of projects’ results. Moreover, there are other relevant developments such the Product Cost Calculation by SAP or the Variability Management tool developed by Chalmers which have arisen from work done within the Know4Car project and constitute further exploitable results and also additional channels for the exploitation of the platform itself. Volvo specific exploitation activities will be managed by the Technology Area Steering Committee – Supply Chain (TASC-SC), which has corporate responsibility for identifying and disseminating strategically-important manufacturing developments throughout the Industrial Group. EDAG, being an engineering service provider company, is interested in using the platform in its daily business, in order to gain advantages in terms of competitiveness in acquisition an execution of complex projects and cooperation with OEMs and Suppliers. IAM and CRF exploitation activities will mostly consist in the promotion of the K4C achievements towards the industrial end-users group, respectively FIAT and the IAM Consortium, and also relevant group of interest around Europe to incentivize their engagement. Moreover, all the industrial partners will be involved in the use-cases towards the end of the project, allowing them to concretely demonstrate the benefits achievable by using the K4C platform. BAZIGOS is basically interested in the Extended Engineering and AR related functionalities. Academic partners will mostly focus on dissemination and promotional activities; the output of the project will form the basis for further research and development actions. This will result in the future launch of R&D projects in collaboration with existing partners and/or similar organizations and in PhD, Master courses or academic lectures.

Introduction Page 10 of 120



In section 2.13 specific actions undertook to involve SMEs are described. Thus, results of questionnaires/surveys which have been sent to IAM Associates and, in some cases, also to external partners to collect information about European SMEs’ current use of ICT technologies and match points with their interests and the Know4car developments are presented.

Page 11 of 120 Know4Car Exploitation Strategy



2 KNOW4CAR EXPLOITATION STRATEGY

2.1 Know4Car Exploitable Results

The exploitable results of the project can be seen in the table below:

Table 1: List of exploitable results and responsible partners.

Reference component Exploitable result Responsible

partner

Agent component/ Extended Engineering Collaboration

PACE – PlAtform for cross-supply Chain Engineering SAP

Project Execution SAP

Product cost calculation SAP

Extended Engineering Component

SQL Bridge – Intelligent data management for a seamless and robust data availability

PDTec

Cloud-based collaboration platform PDTec

Variability Management tool Chalmers

AR subsystem Full AR system: 3 integrated modules for Registration, Remote Assistance and Visualization

TECNALIA

System for tracking human operations + Performance indicators of human operators

Chalmers

Process Knowledge Component and engineering + execution support

Lines Balancing and Optimization: Assembly Lines Balancing (ALB) algorithm and Discrete Event simulation (DES) agent

LMS

Assembly Precedence Diagram Generation tool

Information Extraction Agent

Special AR tools for training and guidance of assembly operations

Manufacturing Knowledge Management infrastructure including knowledge model regarding: Product, Process, Resource and relevant parameters (PPRE)

2.2 PACE – PlAtform for cross-supply Chain Engineering

2.2.1 Description of the results

PACE - PlAtform for cross-supply Chain Engineering is a concept for a product resulting from the Know4Car efforts with the following attributes: It is a cloud-based platform providing:

Collaboration support for development (engineering) of products and production facilities: In particular when new products are to be developed or when a change request of products or/and equipment facilities is issued;

Support for inter-organizational collaboration: Offering a multi-tiered support: OEM (such as Volvo), Integrator, equipment & component suppliers

Support for intra-organizational collaboration: Involving all the departments/areas within an organization: Product development, Product & production preparation, Production development, Production execution

Know4Car Exploitation Strategy Page 12 of 120



Support for collaboration between production & engineering organizations.

Thus, the main functionality can be described as the integration of project management, (engineering) workflow and data access:

Supporting collaborative projects with flexible structures and responsibilities

Supporting complex coordination between collaborating partners

Ensuring full (seamless) integration between the project view and the engineering view

Ensuring a process controlled access to project related (engineering) data sets.

2.2.2 Value proposition: innovation content of result and main benefit

PACE offers the following value propositions:

For large-scale organizations: it ensures data – process – project (DPP) engineering integration across departments;

For all kind of organizations (large scale as well as small scale) it offers DPP integration across companies for development purposes: in the engineering, development & ramp-up processes;

It provides support to manufacturing organizations working together with engineering organizations, especially regarding equipment development, both in green and brown field.

Table 2: PACE SWOT analysis.

Helpful

to achieving the obj. Harmful

to achieving the obj.

Inte

rnal

(att

rib

ute

s o

f th

e o

rgan

izat

ion

)

STRENGHTS WEAKNESSES

Support for collaborative projects with flexible structures and responsibilities

Support for complex coordination between collaborating partners

Process controlled access to project related (engineering) data sets

Further development efforts are required

Exte

rnal

(a

ttri

bu

tes

of

the

org

aniz

atio

n) OPPORTUNITIES THREATS

Growing attention toward collaborative platform (intra and inter organizations)

Growing market trends toward PLM SaaS solution

Possibility of being «Early follower»

Increase SAP’s Market Reputation and Visibility

Address main actual customers’ «pain points»

Positioning may not be so easy

2.2.3 Market and distinguishable characteristics

PACE targeted groups of customers can be grouped as following:

Projects based on collaborative engineering:




o Organizations doing engineering together; o Large organizations where multiple departments are involved in engineering processes

Projects involving collaborative engineering and realization phase: o Organizations doing engineering together AND realization

Projects involving manufacturing and engineering processes: o Organizations doing manufacturing, working together with engineering organizations

(e.g. factory equipment) SAP expects that the potential target markets will be in the following areas

1. “Discrete industries”: o Automotive o Industrial Machinery and Components o Aerospace and Defense o High-tech industry

2. Engineering and Construction, engineering of buildings, roads etc.

Market size and main competitors

PACE is an innovative platform supporting collaboration integrating project management, workflow and data access. Directly related competition is the following:

TeamPlatform,

EngineeredToFly

As it shows only limited competition provides similar functionality. Especially TeamPlatform provides a similar approach to the PACE where collaboration is based on executing projects to the level of individual “to do” elements for engineering, giving them also access to the relevant data. Other competition is in the area of supporting collaborative project execution:

Clarizen

Project Management

Project Pro for Office

However, these kind of solutions do not support advanced engineering support, such as access to structured and versioned engineering data. PLM SaaS is another related area. Competition in this is for example:

Siemens TeamCenter. Siemens TeamCenter provides data integration together with workflow process. Note that workflow processes have the problem of not integrating with project management and ad-hoc to-do support for engineers.

AutoDesk360: AutoDesk 360 is an in-the cloud collaboration environment for working together on (CAD) Designs. Although project management and engineering workflows are not supported, the “social software” functionality of AutoDesk is an important reference.

Business Case

The Engineering Design Network is currently seen within SAP as the product to be developed on basis of PACE (Know4Car results), see also section 2.3.2. For this product the following business case was developed within SAP:

2015 2016 2017

Incremental Revenue1)

1 m€ 6 m€ 15 m€

Customers2) All LE and ME customers

All LE and ME customers All LE and ME customers

Dev. Invest. 10 ToT 12 ToT 12 ToT




Market for PLM SaaS1

Market Forecast. SaaS revenue is expected to grow significantly faster than the PLM market average. SaaS will account for 8% of the total PLM market by 2015

Buying Trends towards on-demand and mobile solutions. Move from the traditional PLM being within the four walls of an organization to now encompassing supply network integration.

Figure 2: PLM market forecast.

2.2.4 IPR and patents applications

Currently, there are four patents in process for PACE. Three of them can be seen below:

Coordination execution of a collaborative business process (Patent regarding the kernel collaboration engine). Application authority: United States Patent and Trademark Office. Filed Sep 19, 2011. Issued Mar 21, 2013. http://patents.justia.com/patent/20130073469

Realizing Collaborative Engineering Support (with constricted process visibility and data sharing, controlled iterations and iteration based versioning; D41.1 contribution). Application authority: United States Patent and Trademark Office. Filed Oct 15, 2013. Issued Apr 17, 2014. http://patents.justia.com/patent/20140108269

Dynamic and adaptable event integration for flexible business processes (Patent regarding the PACE architecture). Application authority: United States Patent and Trademark Office. Filed Dec 13, 2013. Issued June 18, 2015. http://patents.justia.com/patent/20150170074

2.3 Alternative Exploitation strategies and activities related to the Know4Car collaboration platform

SAP as a large IT enterprise has an enterprise-wide portfolio process to determine what new products to bring to the market. From the start, SAP’s activities within Know4Car were targeted to achieve an optimal exploitation of Know4Car results within SAP. These activities encompassed:

Defining PACE as a concept for a potential product for SAP, a product that would be both viable (having potentially sufficient market potential and interest) and feasible (realizable within certain limits of effort)

1 CMI estimates based on IDC WW SW Market Forecaster – May 2012

http://patents.justia.com/patent/20130073469






Disseminating this concept to SAP’s higher management and other influential persons, such that a portfolio decision, or any other decision to create a product on basis of the Know4Car results would be taken

Defining a fallback approach, in case a decision to create a product within SAP would not be taken In the following we shall briefly summarize these activities

1. Weekly phone calls with Product Owners of PS (Project System), PPM (Project and Portfolio Management) and PLM solutions. This lead to the contribution of Know4Car concepts in “Project Execution”, see section 2.3.3

2. Organization of a Customer Engagement Initiative dedicated to “simplified project management”, these activities also. These activities also flowed into the overall concept of “Project Execution”, as described in section 2.3.3

3. Ongoing discussions with PPM – PLM consulting, being the main link to potential customers for this kind of solution

4. Participation in the PLM Future Roadmap initiative, to set up a roadmap for SAP to follow in its PLM strategy. As a result of this activity, project-based engineering collaboration has been included in the SAP PLM Roadmap

5. Participation on an SAP-wide contest “Intrapreneurship” for ideas that would get funding for making them to independent new SAP products (note: the Intrapreneurship initiative is independent of the normal portfolio process mentioned above). PACE was selected among the 25 best proposals of the 400+ that were submitted. Although it did not win the competition at the end, it raised positive attention and interest

6. Working towards Custom development (see section 2.3.1 below) 7. Taking part in defining the SAP Engineering Design Network. All above activities in fact resulted in a

positive decision to start product development in the area of Cloud-based Collaboration for PLM, the product (tentatively) to be called: SAP Engineering Design Network. Some details are given in section 2.3.2

Relevant detailed information regarding these activities have been described below.

2.3.1 Custom development for the PACE platform

A route that can be followed within SAP to turn concepts into products is the development of solutions directed to certain customers. This is called “custom development”. Customers interested in a collaboration platform can sign a contract in advance with SAP and pay for the additional development needed and for the customization of the product on their specific needs. Contacts have been made with Volvo, EDAG and CNH. CNH is a company belonging to the FCA group; an expert of CNH was already involved in the phase of testing of the platform prototype. The development of a solution targeted at specific customers implies the involvement of the “custom development” department within SAP but does not leave out the possibility for SAP to build a standardized product in the future.

2.3.2 SAP Engineering Design Network

SAP has decided to continue on the results of Know4Car as a basis for creating a product for enabling PLM based collaboration in the cloud. The (tentative) name for this product is “Engineering Design Network” the proposed solution and value proposition is based on that of PACE, however:

As collaboration between engineering firms is a topic within SAP where there is a big gap, due to the outsourcing of the product “CFolders”, first focus will be on the support for data exchange;

In order to come quickly to a marketable product, a “minimal viable product” will be defined, having the minimal set of features required to be of interest to SAP’s customers

In order to develop this product SAP will follow the principle of co-innovation. This means that designated (potential) customers will be involved in the development of the product:




1. Customers will be requested for their priorities, what features are essential to start with. 2. Customers will take part in so-called design thinking workshop. Design Thinking (DT) is a human-

centered, rapid prototype based innovation method. Its main idea is to develop a solution in close exchange with stakeholders and target users to ensure desirability, viability, and feasibility of the final solution.

3. Customers will take part in usability testing sessions in which the customers can test the results of developments, and give feedback.

The points 1 until 3 will be executed iteratively. Current status is that potential customers are being contacted, these include Know4Car partners. The participation of Co-innovation customers may run over a public funded project (see section 2.3.4.1) to get funding for customers to participate in the project. This initiative has been also presented to end-users during the workshop in Turin in November 2015.

2.3.3 Project execution

While SAP EDN is directed at supporting project execution for collaborative engineering, „Project Execution“ is a more generic potential SAP product that allows to manage the daily project related tasks and deliverables, so that people involved in the project can efficiently put the planned project into action in a collaborative manner. Project Execution is more generic then the functionality provided by PACER –it supports therefore a broader domain, and a broader set of potential customers–, but it is also (therefore) less specific: It does not include an integration with a component for enabling sharing of engineering data between organizations. Features such as automated access rights management, automated version control (on basis of iteration) are not supported. Data sharing is constrained to the sharing of files. Project Execution is currently seen by various product owners in the area of project management as an essential component of a potential product bringing SAP project management in the cloud. Bringing products in the cloud is an essential part of SAP’s current strategy of “simplification”. The broader scope also means that the domain of application may be widened towards professional services, the support for services that are provided and managed as projects, there again outsourcing plays a big role. These professional services maybe for example consulting services or implementation services.

2.3.4 Fall-back exploitation plan for the Know4Car collaboration platform

For the case that SAP would have chosen not to invest in Project Execution, and/or when a timeline for the productization of PACE would not be defined at the end of the Know4Car project, an alternative exploitation plan for the Know4Car platform was developed, so that the Know4Car platform “as-is” could become a full-fledged product used by (potentially) interested customers such as Volvo and EDAG, and partners of IAM. This is called the “direct exploitation” approach. In plans described above in sections 2.3.2 and 2.3.3, project execution and/or EDN will be developed and exploited “in isolation” by SAP. Those plans also includes building the main components anew to fit with the SAP strategy of using HANA and Fiori as the main technical platform. The main distinction of the alternative “direct exploitation” as described here is therefore, that it assumes the further development and usage of the current technical substance of the Know4Car platform, and requires the packaging of the current Know4Car components accordingly. The direct exploitation plan therefore includes how to handle revenue and IPR issues with the partners of Know4Car. The “direct exploitation” approach can best be introduced by means of a graphical model as shown in Figure 3 below.




Figure 3: Cause effect diagram for the direct exploitation.

The main elements of the diagram are explained below:

1. Exploitation: Commercial Customers for Engineering Collaboration Platform. This is the target of the exploitation.

2. Commercial Customers. Clearly, the final exploitation needs customers, with commercial commitments. Currently, with this regard the following can be mentioned :

a. Commercial customers should be an outcome from the trial, as well as from the partner of the Know4Car platform (Volvo, EDAG, partners from IAM). Note that the trial should also show the usability and power of the platform

b. Commercial customers should come from the existing customer base of SAP and PDTec 3. Revenue Model & IPR Model. All partners shall agree how revenue is distributed and how IPR issues

are handled. A simple model is as follows: a. License through SAP. Customers purchase licenses per user through SAP, who will therefore

function as the “Distributor” for this software. b. Renting of Services. SAP will use part of these revenues to rent/ buy corresponding licenses of

the underlying components, especially the ice.NET data repository (from PDTec) and the agents (from LMS).

Note: This approach solves the Revenue distribution as well as the IPR problems, as none of the partners need to sell or disclose their IPR.

4. Trial: Extend & Improve the Platform. In order to come to a viable product, a trial is foreseen to extend and improve the platform and make it viable as a product to be used and sold for the purpose of collaborative engineering. A trial consists of the following aspects:

a. Extend development of missing features. At the end of the Know4Car project certain essential features will still be missing to make the platform into a viable project. For this development a funding is still needed. Currently the following funding mechanisms are considered (not shown in the picture):

i. Public funding. Public funding will be searched in order to diminish the risk of partners involved in the other funding mechanisms.




ii. Investment from the Primary Customers. Primary customers are customers that take part in the trial, primary customers shall do an upfront investment, to be used as (part of) the funding of the missing feature development. This up-front investment shall be reimbursed once the product will generate revenue. One way to do this is to make the actual platform usage for free.

iii. Investments from the technology providers. Technology providers such as SAP, PDTec and LMS will probably also invest in the further development of features

b. Improve. A trial will be used to improve the platform so that it will be ready for daily usage in collaborative engineering. This aspect requires tight interactions with the primary customers (see below) - their feedback as well as improvement proposals will be crucial to mature the product.

c. Revenue model. Already during the trial, a Go2Market-Strategy will be introduced. This is partially to test the revenue model which will be used during the actual exploitation of the product. Revenue is needed to finance the hosting of the platform, the improvement of the platform and its further maintenance. Note that the Revenue Model will be principally the same as the one mentioned above.

d. Primary Customers & Use case. A use case and corresponding primary customers will be identified. Fundamentally (Basically), the use case should not be “live implemented” and be business critical, but still be a real live use case.

Table 3: Essential features still missing in the Know4Car platform at the end of the project.

Feature Description

Ad-hoc spawning of activities Addition of new activities at run-time

Ad-hoc (re-) planning Including role assignment

Support for decision processes E.g. decisions on quality gates

Copying of data between partners (synchronization)

When a project is delegated, the relevant data are copied

Support for informal processes Social media-like decision taking

Automated versioning & result tracking Iterations: explicit contribution of each work-item execution

For the direct exploitation a phased realization was proposed:

1. Phase 1: Feasibility study for the trial. During this phase discussions take place with possible partners, especially regarding the definition and organization of the trial, potential primary customers etc.

2. Phase 2: Preparation of the trial. During this phase the details are further worked out, this includes applying for funding, (further) preparing the revenue model (Go2Market Strategy), defining the trial procedures etc.

3. Phase 3: Initiating the trial. During this phase, the contracts for the trial are formulated and signed 4. Phase 4: Further development. During this phase the development of the missing platform features

takes place in order to prepare for Phase 5. 5. Phase 5: Trial execution (limited availability). During this phase the platform is used for an engineering

collaboration project of the involved customers. It is especially directed at improving the product and proving its viability.




6. Phase 6: Roll out (general availability). During this phase the platform is used and sold to all interested customers.

We note that principally Phase 4 and Phase 5 may have some overlap, that is, during the trial further development typically takes place to handle missing aspects and issues. Principally, however, in Phase 5 the solution would be sufficiently robust and complete so that partners can start using it. Phase 2 will only be entered if the roadmap for productization of PACE is not yet clear (at month 45 of the Know4Car project), or if the strategy for productization of PACE and this direct exploitation have been aligned. Further details regarding (phase 1) are shortly described in the following section.

2.3.4.1 Current Status

As part of the feasibility study (phase 1), a trial was proposed as continuation of the “Evolution” project. The trial project was targeted to become a public funded project, so that potential participants, such as Pininfarina, FIAT and EDAG would be paid for their participation to the trial. The main goal of the Evolution project is to demonstrate the feasibility of a FEV urban car of 600kg by the end of 2016: starting from an existing concept car by the Italian design company Pininfarina, a totally new archetype of vehicle is derived by leveraging on the integration and hybridization of components and advanced materials and on enabling technologies such as gas forming, etc. By the end of March 2015 the design activities of the EVolution vehicle will be ending. One of the alternatives which are currently under investigation is to build a trial project where the outcomes of the Evolution project constitute the basis of a new initiative. The trial stresses the collaboration between different players of an automotive supply chain since it involves:

the finalization of the design activities (since there are some aspect that the EVolution project does not take into account, e.g. trimming parts of the vehicle or high-strength aluminum alloys body side),

the design of a production line in which the lightweight car designed in the Evolution project can be produced,

and, the evaluation of the impact of the new designed component/system to the current production line.

Targeted primary customers were: Fiat, Pininfarina –as designers of the car– and EDAG –as being the company responsible for designing the production line. Also suppliers for realizing the production line and parts and components suppliers as company from IAM will be included. The first step of set-up of the trial was planned to be coordinated by the Know4Car partner IAM, then, depending on the funding scheme identified, the proper leading partner would be selected. The plan was that after the end of the trial, the involved companies will be the primary customers of the improved platform. At present time the idea of going for a trial project in the context of a “direct exploitation” approach has been turned down by SAP, however, the idea for a funded project for involving co-innovating partners in the development of the “isolated” SAP EDN product (see section 2.3.2) is under consideration.

2.4 Product cost calculation

2.4.1 Description of the results

The product cost calculation tool has been developed by SAP also taking advantages from achievements gained in the Know4Car project in the field of collaboration. Product cost calculation requires close collaboration within an organization (Engineering, Controlling, Procurement, Sales, etc.) and also along the supply chain (suppliers, sub-suppliers). So, this is a tool for collaborative cost estimation to be used in the design phase to take into account the cost factor. It also represents an important channel for the exploitation of the collaborative features of Know4Car and also put the basis for a so-called “network effect”. This tool is currently not integrated in the current prototype, but the concept is under elaboration and pre-validation as parallel activity.





Engineers always aim at designing a functioning product without taking too much into account economic and schedule constraints. However, research has shown how decisions made during early design phases determine the majority of the product's costs (up to 70%), together to quality and manufacturability characteristics. This indicates the great leverages that an effective tool for product cost calculation can have on a company's success and profitability. Moreover, currently, similar tool are not yet available on the market.


This tool is suitable for a number of different industrial sectors. Currently customers operating in the development and manufacturing of tractors, pumps, automotive parts, custom made machines, mass-produced furniture have requested for a powerful cost calculation functionality. The commercial exploitation of the tool is foreseen for second quarter of 2015. The product cost calculation tool will be sold as an independent product, but SAP strategy will be also to explain how the cost evaluation is based on collaboration and so it will represent a channel of exploitation for the solutions which support engineering collaboration offered by SAP.

2.5 SQL Bridge – Intelligent data management for a seamless and robust data availability

2.5.1 Description of the result

The SQL Bridge is a tool, which supports the integration of the K4C platform and other databases. It maps relational data transparently into ice.NET model with legacy data within ice.NET without replication and connects ice.NET to Master Data Management solutions. It ensures model consistency across databases thanks to rule-based relationships consistency and avoids dangling references. Finally, it allows a fast access to relational data thanks to SQLBridge Querie, which span database boundaries and minimize server roundtrips. At this stage of the project, the tool is fully implemented and functional and it has been already integrated in the PDTec ice.NET Suite.


The SQL Bridge will be offered as part of the current ice.NET suite. The SQL Bridge links the databases of the various partners in a common place, directly linked to the K4C ontology. It faces the current challenges represented by:

the total number of files and amount of data,

complex versioning and configurability of data

multiple domains, various philosophies about data storage, persistence, update times, data quality etc.

Moreover, it ensures an intelligent data management including domain integration (manufacturing, product planning, product design) and generic (reference) data model. In addition it offers full availability of the entire shared project data at all times, significantly reducing the time for data exchange or synchronization. Finally, it benefits from shorter time to market, high versatility and acts as independent from domains and philosophies and as a prerequisite for international standardization.




Table 4: SQL Bridge SWOT analysis.

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It faces the current challenges mainly represented by quantity of files/amount of data, complex versioning and configurability of data, as well as multiple domains, and issues related to data storage, persistence, update times, data quality etc.

Migration/Implementation requires some effort

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It ensures an intelligent data management including (industrial) domain integration and generic (reference) data model;

Shorter time to market, high versatility;

It acts as a prerequisite for international standardization (standards are currently lacking);


The target group of the overall customer market is expected to be 3 – 4%. Currently there are on-going acquisition activities with potential customers. More details on this are given in section 2.6.3.

2.5.4 IPR and possible patents applications

No patents’ applications have been submitted regarding PDTec’ contribution to the development of the Know4Car platform.

2.6 Cloud-based collaboration platform


After the project, the collaboration oriented specifications and software components, will be enhanced and shall become part of the PDTec ice.NET product portfolio. It is planned to offer this product to the market as a “cloud-based Collaboration Platform for supply chains”, which shall be offered under the SaaS paradigm. The developed cloud features will be part of a so called “Engineering Collaboration Cloud”. It will enhance in the first step especially PDTec’s product portfolio geared at the product design market. Therefore, currently implementation work is ongoing to include the new features to PDTec’s own Collaboration Platform (CADPortal). Figure 4 depicts the ice.NET platform and the upper application layer. Due to the modular set up of PDTec’s product portfolio, all features developed within the context of ice.NET framework will be eventually available for other PDTec applications as well.




Figure 4 Product Portfolio PDTec.


The added value of such a solution is seen mainly in the ability to offer a service-oriented Collaboration Platform in the cloud, in combination with dedicated consulting and training services to the market, thus extending the solution portfolio of PDTec and potentially extending its own customer base. The main challenges faced by PDTec in providing this solution include high development, as well as functional and integration testing costs accompanied with large number of iteration cycles in development. This solution will be offered under a cloud-based paradigm and will provide a collaborative development environment which enables data modeling and validation up to code implementation and validation (adapters, distributed and local, on- and offline synchronization, plug’n play, out of the box solution). Customer can benefit from faster product development, higher quality of the final product and higher degree of user’s satisfaction. Development of the platform entered the final phase of implementation, followed by tests and integration to ice.NET product suite.

ice.NET Platform

CAD Frontend IntegrationCollaboration Portal

CAD Portal

K4C

Catia CreoNX

Lifecycle Mgmt. Subscription

Authentication Batch Processing …

ReportingAudit Trail

Documents, VaultsScripting Profiles, Permissions

UI ComponentsUsers, Groups, Roles

CAD ModelProjects PDM Interfaces

Import / Export Jobs Product Structure Baselines

…




Table 5: Cloud-based collaboration platform SWOT analysis.

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Scalability: Organizations can easily add or subtract users;

Rapid implementation, instead of extensive local implementation, and decreased costs for maintenance;

Ease of use enhanced by the elimination of duplicate entries and reduction of errors;

New features and functions already included in an ongoing subscription;

Independence of performance, size, system, also in case of private deployment;

Minimum degree of complexity of data management systems is necessary;

Standards for data exchange are lacking due to high amount of different file formats;

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Eliminate investment in rapidly depreciating IT capital equipment and systems through the use of pay-as-you-go solutions;

Growing market toward Cloud solutions;

End-users resistance towards the implementation of changes to current IT systems;

End-users resistance toward the adoption of cloud-based solutions, in particular as for access/properties rights;


Offering the cloud-based platform together with the SQL Bridge as part of the current ice.NET suite, will allow PDTec to consolidate and expand their customer base. The customer base for the platform will basically be situated by the product design and production industry, e.g. machine and plant manufacturers and automotive industry (OEM as well as suppliers). The target group of the overall customer market is expected to be 5 - 7%, including specific consulting and training services. Currently the ice.NET solution is running mostly in middle-sized and large companies (machine and plant manufacturers, automotive industry) with in-house computer centers. Such companies offer their own infrastructure for solution purposes. In such cases PDTec is responsible for the following activities:

Installation of the ice.NET platform;

Launch and start of operations;

Support and training The costs for IT infrastructure are covered by the company, using ice.NET. With the introduction of ice.NET cloud solution the potential market size and customer base substantially increase. Small to middle-sized companies are potential customers with no need of investment and support of technical infrastructure (computer centers). This is covered by the cloud service provider. In addition to the ice.NET licenses, the companies have to cover only cloud service provider costs (e.g. Azure Cloud). This approach enables a way to new customer base and bigger market.




Since ice.NET suite is modular and flexible, cloud solution can be adjusted to specific needs of small and middle-sized companies in different ways. It gives PDTec a major advantage in comparison to other solution providers (big players like Siemens, Dassault, etc.). Cloud-based solutions in PDM sector are not yet established in a widespread way. Thus, PDTec has an advantage in winning the customers and the market. During the duration of the project, PDTec developed and detailed a strategy for the marketing of the cloud-based Collaboration Platform together with specific consulting and training services. Currently it is foreseen to license the cloud-based Collaboration Platform on a named user basis.


The possibility to run in a cloud environment is a major change for the platform architecture (moving the architecture to the cloud influences all major components), but not a new product.

The current ice.NET IPRs are to be applied.

No patents applications are foreseen.

2.7 AR system (3 integrated modules): Registration – Remote Assistance – Visualization


The AR Training Framework System able to detect, track and augment objects with virtual information without the use of fiducial markers. It is composed by 3 different modules:

AR Module for Registration: o This module allows aligning a set of augmented objects with an object that the user wishes

to detect and track in real time. o The outputs are represented by a set of augmented objects with correct

location/orientation. o It is based on marker less tracking technique. o It recovers the precise collocation of the user in the working area, which in turn is needed

for the geometric rendering of the 3D graphics with good alignment with the real objects in the environment.

Figure 5: Sample output for Registration Module.

AR Module for Remote Assistance: o It provides an expert operator with the ability to assist the shop floor worker while

carrying out a specific assembly task; o It ensures bidirectional audio communication and a remote visual perception, realized by

streaming the live camera image from the shop floor worker’s AR head mounted display to the remote expert via Internet.

AR Module for Visualization o It allows to visualize the live image and the augmented objects on the physical display

hardware (video or optical head-up display or computer monitor). o This module is responsible for rendering the augmented 3D objects in the correct

positions on top of the user’s view of the real world.




o It is committed to show additional information about the environment that the worker is seeing.

Figure 6: Sample output for Visualization Module.


Major challenges faced in the development of this AR system are:

Accuracy required in tracking and registration in such applications.

Quality of the user’s experience.

Robustness and availability of these systems working at the shop-floor level.

Usability aspects of UIs (simple, intuitive, precise, etc.) and user acceptance.

Compliance to legal regulations, industrial safety aspects, ergonomics, human factors, cognitive strain on the users, etc. since engineering users of AR applications will spend large amount of time using this kind of systems.

These tools were intensively examined through the Automotive Assembly use case. For what concerning user’s acceptance, several face-to-face meetings will be held at the involved plants to sensitize operators to this kind of technologies.

Main benefits to the customers can be summarized as follows: AR Module for Registration and Visualization

Reduction of time and costs when performing a task;

Get better understanding of assembly components and process;

Improve safety aspects of final assembly operators;

Improve the way to share information with end users;

Improve natural visualization of the augmented information;

Reinforce the communication between experts distributed all over the production, promoting the exchange of knowledge and exploiting different expert profiles.

AR Module for Remote Assistance

Reinforce the communication between experts distributed all over the production chains, promoting the exchange of knowledge and exploiting different expert profiles;

Improve safety aspects of final assembly operators.

Fix with screw

#2.

Full tightening.




Table 6: AR system SWOT analysis.

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Bridge the gap between engineering and shop-floor;

Offer real-time remote assistance;

Improved quality of operations;

More intuitive methodologies and shorten time for training;

Possible compatibility issues with safety regulations and usability;

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Market trends show an increase towards application of advanced UIs for on the job training/safety (applications for education and instructional);

Suitable both for training and remote support purposes;

Suitable for a number of different industrial sector;

Resistance of the operator;

Availabilities of mature technologies;


Trends in AR Market

A rise in the AR market, with exponential growth in terms of revenue, is expected in the period 2011 – 20222. Countries contributing by now to the AR applications market are North America and Europe but Japan, China and South Korea are expected to join; AR applications market is described as “leaded by small companies with talented and highly-skilled teams”. The major companies developing SW and applications for AR are Total Immersion (F), Metaio GmbH (D), Layar (NL), Wikitude (A), etc.3. More recent market researches show how the exponential behavior of revenues’ growth for AR application is much more stressed, as it can be seen in the following figure.

2 Source: Global Augmented Reality (AR) Market Forecast by Product (HMD, HUD, Tablet PC, Smartphone) for Gaming, Automotive, Medical, Advertisement, Defense, GPS applications (2011 – 2016) http://marketpublishers.com/r/G3792FD4FB9EN.html 3 http://www.t-immersion.com; http://www.metaio.com; http://www.layar.com; http://www.wikitude.com.

http://marketpublishers.com/r/G3792FD4FB9EN.html



http://www.t-immersion.com/

http://www.t-immersion.com/

http://www.metaio.com/

http://www.layar.com/

http://www.wikitude.com/

http://www.wikitude.com/




Figure 7: AR market revenues for different areas – Forecast based on Smartech Market Publishing report4.

As presented by Mr. Lawrence Gasman, CEO of Smartech Market Publishing, in the wrap-up section of the Augmented World Expo 2013, who reported about addressable markets and expected market expansion, the areas of application which seems to be more promising are:

Application for retail and promotional (advertising, virtual shopping etc.)

Application for entertainment and gaming

A relevant position is also occupied by applications for education and instructional of AR technologies, which include also industrial applications such as on the job training and safety. Mr. Lawrence Gasman in his speech5, also highlighted the following points:

revenue generation in the field of AR will take a few year until it ramps up;

big companies are not going to commit themselves to make big investments, due to the current size of the market;

there will be significant source of finance, SMEs are favorite and there a lot of young entrepreneurs in this field;

investment is the main roll-block for adoption of AR and revenues’ growth, because getting this to the mass market is always expensive;

as shown below, only a few categories are strongly contributing to the market.

The categories contributing to the AR market by the year 2018 as well as the involved challenges can be seen in the Appendix B in Table 13.

Figure 8: The five core markets for AR ($ millions revenue by 2018).

4 http://www.smartechpublishing.com/opportunities-for-augmented-reality-2013-2020.html presented at Augmented

World Expo 2013, 4-5 February 2013, Santa Clara, California 5 http://www.youtube.com/watch?v=l94A824nUZk

http://www.smartechpublishing.com/opportunities-for-augmented-reality-2013-2020.html

http://www.youtube.com/watch?v=l94A824nUZk




Targeted segments

AR Integrated module The potential uses of AR application in Industry span the complete life-cycle of the product. It is, therefore, evident that any kind of industry that has a production line which changes the stations pieces and assembly operations from time to time can be a reference market. The key target market is in the automotive industry, which currently strives to improve training actions. Nevertheless, other sectors can also be taken into consideration.

AR Module for Registration and Visualization Concerning the registration and visualization modules, the main customers are represented by:

Manufacturers and companies that maintain heavy and complex machines (crushers, harvesters, mobile machinery);

Automotive manufacturers and service providers;

Medical;

Advertising and promotion;

Sightseeing.

AR Module for Remote Assistance In addition to the previous ones, target customers for the remote assistance module include also

Power plants, marine industry (Engines);

Heavy transportation;

Equipment suppliers;


Within the SP5 subproject it is expected to have very good prototypes. Since the project results are by nature pre-competitive, they will be at Technology Readiness Level (TRL in NASA’s terminology) between 4 and 5. Yet, they will need further development towards TRL-8 in order to enable exploitation as commercial products. An estimation of such commercial development will require a further effort and time after project completion. TECNALIA has a TTO (Technology Transfer Office), which will assist in the identification of the most convenient way of protection for these AR Exploitable Results and for the time being, the most appropriate IPR Strategy and Protection instruments (patents, copyrights, industrial secrets, know-how, etc.) has not been defined.

A very preliminary analysis of patents is as follows:

AR Module for Registration (Object Detection and Tracking): We have used two algorithms from the literature (initially DOT for object recognition and PTAM for tracking). Publicly available source code of these algorithms has also been used. However, two novel uses of these algorithms have been generated:

o The integration of the two algorithms in order to do simultaneous object recognition and tracking in real-time.

o The use of advanced object detection algorithms for implementing marker less Augmented Reality.

Then, a further analysis of the patentability of these developments has been carried out as described below:

AR Module for Remote Assistance: It is necessary to examine in more depth if the idea of doing "remote augmented reality" could be patentable: e.g. to stream the camera pose, the 3D models and the video image to the remote user, augment the video stream remotely and allow the remote user to annotate it.

AR Module for Visualization: Standard material is used at a high extent; therefore there is low opportunity for a patent in this field.




AR Training Framework: It refers to the whole integrated solution, so its patentability should be considered by the Know4Car Consortium.

The final decision was not to proceed with patent request.

2.8 System for tracking human operations and performance indicators of human operators

A lot of work has been done by Chalmers in order to develop a system for tracking human operations and methodologies to evaluate the performances of the operators which execute the work in a production environment. The result has been a serious game platform for the evaluation of the training activities of shop-floor operators which is able to:

Display real-time work instructions and collect online feedback information

Measure the performance of operators thanks to proper metrics for real time evaluation and readjustment of various parameters of the training platform.

The system used is the one showed in the figure below.

Figure 9: System for the evaluation of the training activities in the shop-floor.

2.9 Variability management Tool

The product variability represents a tricky issue to be faced. In Volvo AB there are 500 variant families, 50 000 configuration rules and so 10100 truck instances. The real challenge about variability management is to be able to manage and analyse all these rules and instances, while being able to track any specific instance. Usually the OEM can only provide the detailed documents for the high volume truck models instead of all the truck model variations to the System Integrator, so it means that an assembly line will be built only based on this information. Moreover, the exchange of information which often takes place by e-mails, the need for ”manual” translation between different knowledge representation specific to the needs of stakeholders (e.g. eBOM, mBOM, mBOP) and the manual management of certain constraints could all lead to errors. The variability management tool offer a solution thanks to the possibility of:

Generating detailed documents for all models irrespective of their high or low volume;

Automatically checking and tracing all the constraints to each truck instance.




The variability agent acts as a stand-alone tool and collaborates with the collaboration platform. First the collaboration platform is used to download latest version of the needed engineering document, i.e. eBOM, mBOM, and mBOP. In the next step, the Variability Agent is used to update and analyze engineering documents, i.e. eBOM, mBOM, and mBOP. This agent is designed to assist the user for updating the eBOM and mBOM, while automatically creating the mBOP from the mBOM. In the eBOM the variants present in the product family are structured from a functional point of view. While in the eBOM these variants are structured from a manufacturing point of view. The eBOM also includes the configuration rules which are used in the product design. The variability agent assists the engineer in updating these two engineering documents (eBOM and mBOM) by providing the possible variants which can be used in each part of these structures. This list of variants can also be used while building the configuration rules in the eBOM.

- Figure 10: Variability Agent Assisting the update of Ebom.

Figure 8 shows an example of how the variability agent will assist the engineer while updating the eBOM, by showing him/her the possible variants which can be used in this structure.

The variability agent also is able to analyze this eBOM document to automatically produce the eBOP for all the valid products that fulfill the configuration rules specified in the eBOM.

Figure 9 shows an example list of products which fulfill the stated configuration rules. For each of these sample products the corresponding mBOP is created. As it can be seen in the figure 9 this mBOP includes all the variants which are used in each specific product instance, while also showing the manufacturing operations which are needed to assemble the different variants with in the product.




- Figure 11: Automatically created mBOP.

The fact that the engineer is able to produce the eBOP automatically means that it is now possible for the engineers to update the details of eBOM and see how these changes affect the different eBOPs instantaneously.

In the last step, after the eBOM, mBOM, and mBOP are updated and finalized the collaboration platform is used to upload the finalized engineering files.

After the project ending, Volvo is willing to continue using this tool. Moreover the developed applications raised a high consensus during the last end-users workshop plus Chalmers is thinking about extend the field of applications not only to product but also to equipment management. This could ensure a great potential in terms of dissemination of such a tool in the industrial world.

2.10 Manufacturing Knowledge Management infrastructure including knowledge model regarding Product, Process, Resource and relevant parameters (PPR)

The manufacturing knowledge infrastructure includes different components that include both the infrastructure that supports the storage of data and their translation into semantic instances as well as agents that support the identification and management of knowledge. The infrastructure includes different applications that help users store data into a common data model and when required, it automatically translates this information into a semantic model for faster and easier identification of relevant knowledge. The similarity matching application is a mechanism leveraging the knowledge infrastructure of the Know4Car platform to identify and reuse knowledge from previous engineering projects in future situations that present similar challenges to the engineers. In its final refined version, the similarity matching mechanism was updated in order to include additional similarity matching criteria supporting the user to perform tasks on basis of data




entered and decisions taken in previous projects in similar contexts. In the updated application, a user working on a certain tasks such as “calculation of cycle time”, can check the relevance of an old case based on the name of the product or product variant considering string similarity matching values. In this way the semantic queries can provide results to requests such as “show me the number of stations used for the assembly of a similar or same product variant” up to “show me the process time of an assembly process used for similar products”. The PPR knowledge model developed within the Know4Car project will be freely available to the users after the project ending.

2.11 Line balancing and optimization (ALB and DES agent), information extraction agent plus Assembly Precedence Diagram Generation service to support engineers work

Three main outcomes of the Know4Car project are the Lines Balancing and Optimization, which includes the Assembly Line Balancing algorithm and the Discrete Event Simulation agent, the Assembly Precedence Sequence Generation tool and the Information Extraction Agent, all results owned by LMS. The balancing of the assembly line is one of the core phases of the design process that deals with the efficient assignment of processes among the workstations, considering a series of criteria, such as cycle time and production cost. The ALB agent that was developed to support the collaborative design of a line considers information stored in the data repository of the Know4Car platform. In detail, the ALB agent takes as input all processes for the assembly of the product including precedence and compatibility relations, as also all different process configurations. The user only needs to select the products or variants to be assembled for the line. All other relevant information are automatically retrieved from the PPR Library, including cost and time information for all above mentioned process configurations. Then, a series of alternative process sequences are generated by the ALB agent based on the different process configurations. Finally, the ALB agent evaluates the valid process sequences against some user-defined conflicting criteria such as the desired cycle time, the number of stations and budgetary restrictions that are defined through weight factors. Based on the evaluation criteria, the best line balancing option, as also a number of alternative results are stored in the PPR library. The DES agent takes care of the way the processes are distributed over the stations, for each alternative, and builds the corresponding simulation model for each alternative. Based on the resources used by the process configurations selected, the DES considers reliability and maintenance parameters for all stations, specifically, the Mean Time Between Failures (MTBF) and the Mean Time To Repair (MTTR). Finally, the Assembly Precedence Diagram Generation tool supports engineers in assembly. It is based on a six step methodology that has as input an assembly CAD and as output an XML file containing the assembly sequence. Both the ALB and the ASG agents will be the object of post-project exploitation actions as further described in section 2.15. In particular, the ALB and DES agent will be made available to end-users after the end of the project as web-app. In order to do so, some additional work has been done, as described in D72.7.

Figure 12: Six step methodology used by the ASG agent.

The basic part of the algorithm is the execution of intersection tests that are used for the calculation of the disassembly sequence of parts as well as their subtraction paths. After the disassembly sequence and




subtraction paths are generated, they are reversed resulting in the assembly sequence and insertion paths of the parts which is stored in a standard XML structure that can be further communicated to an AR component in order to assist human operators in real-time for the assembly of a product through virtual instructions. LMS an official academic partner of 3DS-Delmia, is allowed to develop 3DS custom tools which can be integrated in standard digital manufacturing tools. In particular the APDG has been integrated in CATIA using VBScript and it is compatible with different releases of CATIA V5-6. The Information Extraction Agent, set up in a server that contains a running version of Delmia, is able to control Delmia automatically, receive files, open them and extracts all relevant data. More specifically, it is able to extract from CATProcess files, the names and relations of the product components, the processes and their information related to them (including their relations between them and the components) and finally the resources (as instances). The agents temporarily stores this information and presents it to the user who can review and edit them. When prompted by the user, the agents creates the necessary classes and instances and upload all data on the Know4Car repository.

2.12 Focus on end users exploitation plan

The Know4Car consortium includes three categories of partners: industrial partners, software developers and academic partners, involved also in development activities. The presence of the industrial partners guarantees the exploitation potential for the solutions proposed. End-users belonging to the Consortium have played a fundamental role in the identification of the business pain points and in the setting of the requirements and specifications of the platform. Each industrial partner is more focused on some specific aspects; in particular Volvo is more interested in knowledge capturing and reuse, while EDAG is more focused on the management of engineering objects and in the tools which can support engineering daily work. CRF is interested in the AR applications, which have been recently requested for demonstration by plant managers who are increasingly interested in the Know4Car developments (mainly CNH group). IAM on their part, have been showing interest in all features of the platform more related to cross company collaboration since most of the IAM associates are SME service or part suppliers to the automotive industry. Finally, BAZIGOS would like to use the Know4Car platform as an opportunity to upgrade its IT infrastructure and is focusing on the central data access point. As described in section from 2.2 to 2.11 and also in the dedicated deliverable D72.7, both the collaboration platform and a number of additional services/tools developed will be make available to partners, so the Know4Car industrial partners, as well as external users, will be able to continue to use them in their daily business. More information about the future plan of each end-users are reported in Appendix C – Focus on end users and academic partners’ exploitation plans in Table 14. In addition to the internal Know4Car partners, the Consortium also did some actions to attract the external market. In particular, three end-users workshops with potential external customers have been organized during the project and three questionnaires have been prepared and circulated among possible interested customers to collect feedback and expectations on the developments carried out within the Know4Car project. A number of workshops have been organized also internally to the Consortium to check the acceptance of real end-users (mainly engineers) from the Know4Car industrial partners. During these events, end-users, both internal and external, have also been invited to test the successive release of the platform prototype.

2.12.1 End users workshops

One major channel for exploitation of project results is represented by industrial partners. In order to actively engage end-users, the Know4car consortium has agreed on organizing a number of workshops at industrial partners premises described hereafter.

END-USERS WORKSHOP @ VOLVO

A workshop to present the Know4Car platform to end users was organized at Volvo premises on May 22, 2014.




An overview of the work carried out so far in Know4car has been given to engineers from Volvo to collect feedback. An overview of the agenda can be seen below:

Table 7: Agenda of Volvo End-users Workshop.

Volvo End-users Workshop Thursday, 22 May 2014

09:00 – 09:20 Welcome and agenda overview Volvo | SAP

09:20 – 11:00

[A7] Presentation of the K4C platform to end users: [A7_1] Overall objectives of developments, overview of K4C [A7_2] Collaboration engine functionalities and Demo [A7_3] Engineering support agents and Demo [A7_4] VR training and process measurements

LMS | SAP | Chalmers

11:00 – 12:00 [A8] Discussion with experts_ Part 1: Q&A with Volvo engineers All

12:00 – 13:00 Lunch break

13:00 – 14:00 [A8] Discussion with experts_ Part 2: Discussion based on feedback from engineers

All

14:00 – 14:30 [A9] Business process simulation using Discrete Event Simulation: Current plan and gathering of information from industrial partners

LMS

14:30 – 15:00 [A10] Sum up and final content for review meeting

[A10_1] Next steps – workshops, GA meetings [A10_2] Sum up and closing of meeting

Volvo

A second workshop at Volvo premises took place one year later, in June 2015, to show to Volvo engineers the last year improvement of the platform and collect their feedback on the final prototype.

INTEGRATION MEETING @ CNH

An Integration Meeting has been organized at the CNH Jesi plant on July 6-7, 2014. The main objectives of the meeting were to give a demonstration of the AR achievements developed and integrated in the Know4Car project to the Automotive Use Case end-users and to discuss with them in more detail the use case and the next steps for its implementation and collect feedback. The agenda of the meeting can be seen below.

Table 8: Integration Meeting@ CNH Agenda.

Integration meeting and preparation

Wednesday, 16 July 2014

09:00 – 10:00

[T1-1] Preparation activities

Registration procedures

Safety briefing

Setting up of meeting room

Inspection to the poka joke corner

Visit to the assembly location and workers interview

CNH management, LMS, TECNALIA, CRF

10:00 – 13:00 [T1-2] Setup demonstrator LMS, TECNALIA

13:00 – 13:45 Lunch Break

13:45 – 15:00 [T1-3] Marker calibration LMS, TECNALIA

15:00 – 18:00 [T1-4] LMS-TEC final coordination and familiarization with actual production operation

LMS, TECNALIA, CRF

18:00 – 21:00 [T1-5] Integration, improvements LMS, TECNALIA

Final set up and demonstration




Thursday, 17 July 2014

08:00 – 12:30 [T2-1] Further improvements, final check of demonstrator LMS, TECNALIA, CRF

12:30 – 13:30 [T2-2] First demo session with CNH people, Other K4C presentations and discussion

All

13:30 – 14:15 Lunch Break

14:15 – 15:30 [T2-3] Second demo session with CNH people All

15:30 – 16:15 [T2-4] Feedback from CNH

CNH management and function responsible, LMS, TECNALIA, CRF

16:15 – 16:45 [T2-5] Final Briefing, Action items, next steps LMS, TECNALIA, CRF

In this case end-users are represented by people from the CNH Jesi plant since the CRF use case is built around the DPF, which is produced in this plant. The plant director, lead people from quality, training and human resources areas together with other CNH employees took part to the demonstration.

Figure 13: Picture from the demonstration to CNH experts.

Figure 14: Picture of the discussion with CNH experts.

END-USERS WORKSHOP @ IAM

An end-users workshop took place on December 3rd 2014 at IAM. The workshop is structured as follows:

A first section focused on the presentation of the project and of the achievements reached so far in the main areas of interest of the Know4Car project (i.e. knowledge management, collaboration, engineering supports and virtual training). This part of the workshop will be open to IAM companies plus selected people invited and other local companies, which may be interested to the topic;




A second section with platform demos, detailed discussion and feedback collection.

The aim of the second part of the workshop is to gain technical commitment not only from industrial partners, which are already connected to the project, but also from a number of external industrial representatives, which will be selected in the IAM collaboration network and by means of suggestions from other project partners among the industrial sectors, which have been identified as relevant in the Know4Car exploitation strategy. Moreover I4MS project partners have been invited to the workshop a presentation from their side has been foreseen in the agenda. I4MS (ICT Innovation for Manufacturing SMEs) is the initiative promoted by the EC to support the European leadership in manufacturing through the adoption of ICT technologies. The initiative is dedicated to the whole European manufacturing industry with special focus on SMEs to address their needs to access to technology, infrastructures and new markets. In this sense, I4MS could ensure an additional channel for the exploitation of the Know4Car solutions towards to SMEs world. A representative of the Project Coordinator of I4MS project participated via web to the workshop. Here it follows the final agenda of the meeting:

Table 9: End-users workshop @ IAM – Final agenda.

End-users workshop @ IAM

Wednesday, 03 December 2014

08:45 -12:30 [WS0] Welcome and presentation of the Automotive Innovation Pole and agenda overview + IAM Factories tour (Seven and Isringhausen plants)

Project Partners + Selected participants

12:30 – 12:40 [WS1] Welcome to the workshop and round table IAM

12:40 – 13:00 [WS2] Introduction to the Know4Car project : Overall objectives of developments, philosophy of Know4Car

LMS

13:00 – 13:30 [WS3] Introduction to the I4MS project I4MS partner

13:30 – 14:30 Lunch break All

14:30 – 16:45

[WS4] Presentation of the K4C platform to end users:

[WS4_1] Overall and Collaboration Engine Pain Points & Demo + Q&A

SAP

[WS4_2] Engineering support agents Pain Points & Demo + Q&A

LMS

[WS4_3] Variability management Pain Points & Demo + Q&A

Chalmers

[WS4_4] VR/AR training and process measurements Pain Points & Demo + Q&A

Chalmers

16:45 – 17:00 Coffee break All

17:00 – 18:30

[WS5] Interactive demo : Presentation of the main features of the platform by means of “guided” demos and more detailed discussion based on feedback from engineers

[WS5_1] Interactive demo: Overall story-board presentation [WS5_2] Interactive demos [WS5_3] Questionnaire feedback [WS5_4] Final discussion and closure of the meeting

All

As external partner PININFARINA was invited and due to the interest shown towards the collaborative part of the platform, as a result of the workshop the idea of a successor project of Know4Car which could be built on a real industrial case was born.




During the interactive demo part of the workshop users are asked to guide the moderator through the various step he/her has to do according to the pre-defined script. In this way users are asked to recall and repeat what they have been shown during the presentations and the demos. The main comments collected during the interactive demo which have been shared with project partners are reported in Appendix E – Results from End-users Workshop, December 3, 2014. Here it follows some pictures taken during the workshop at IAM.

Figure 15: Pictures from the workshop @ IAM.

A second end-users workshop has been organized by IAM in collaboration with the MESAP Innovation Cluster in Turin to present to end-users the last integrated version of the Know4Car platform developed within the project. More information about this workshop and the main outcomes are presented in D72.7.

2.13 Specific actions to address SMEs

Specific efforts will be dedicated to European SMEs operating in the automotive sector or in other relevant sectors identified within the Know4Car project boundaries. One dissemination and exploitation channel can be EFFRA. In fact, BAZIGOS, LMS, IAM, Volvo, Chalmers, and SAP are part of the European Factories of the Future Research Association. The possibility to have a plan for joint exploitation and dissemination activities within EFFRA (e.g. joint exploitation and dissemination seminar) will be evaluated within the Consortium. A user’s feedback questionnaire has been developed and sent to European SMEs in order to collect information about:

Organization dimension and sector of activity

Current ICT tools level of use and level of investments and expectations

Interest in the functionalities provided by Know4Car The dissemination channels used have been the following:

Social networks: LinkedIn, Facebook, Twitter

E-mails




SMEs part of EFFRA, VDMA, other relevant cluster (MESAP, ProPlast, ViaMéca, Pole Vehicule du Future) have been contacted through their general contacts collected on the respective website. This questionnaire can be found in the Appendix. It will be available on the website until M26 (October 2013). Main results of this survey are presented in Appendix A. Moreover, a second questionnaire has been provided to IAM’s Associates in month 17 (January 2013) and has been presented in the second Review Meeting on April 2013. A more specific presentation of the initial results can be found also in the Appendix D.

2.13.1 Main results of the user’s feedback questionnaire – M26

The following analysis is based on data collected until the end of September 2013. Participants to the survey were mainly R&D Directors or CEO of SMEs, in the following density:

Figure 16: Type of respondents #1.

The majority of SMEs respondents base their business in the country where they are located.

Figure 17: Type of respondents #2.

The 67% offers and provides engineering services, but more than half operate also in the manufacturing sector (raw material or final product manufacture/equipment or part suppliers). The survey shows a high interest of participants towards the knowledge and the adoption of simpler ICT technologies (e.g. web infrastructure such as intranet), rather than adopt cloud-based platform. This is in agreement with answers given in Part 2 and expectations about the diffusion among participants of well-known ICT tools in the industrial world, such as PLM and/ or ERP/CRM software. In fact, none of the participants declared to currently use PLM tools, and only a 50% of them already use an ERP or CRM software. On the other hand, more than 80% of companies make use of CAD/CAM tools and among these 60% knows and uses standard file formats. In line with general trend, the majority of SMEs are more willing to buy ICT solution under a token base (pay per use or limited time slot), ranked with an average level of interest of 4 over 5, and declared that costs play an important role when choosing a tool of this kind (4,7/5). Another expected characteristic is the ease of use, while the possibility to interface with other tools (PLM, ERP etc.) and the customization capabilities are ranked only between 3 and 4. This results in an overall interest towards the adoption of a tool which supports collaboration by integrating project management, complex workflow management and data access placed between 3 and 4 (average ranking 3,7). Parts 3, 4 and 5 of the survey are aimed at collecting specific interests and needs of SMEs in line with features provided by the Know4Car platform. The results are presented in detail below.

Table 10: Collected results of the last questionnaire.

Part 3 - Communication and collaboration with other organizations or within your organization Priority

Average ranking




Smoothing and streamlining the communication across departments within your organization

1 4,7

Sharing projects' related information with a supplier/customer 2 4,7

Having a secure and safe information sharing inter and intra organizationally 3 4,3

Having an ICT platform which is able to handle complex collaborative workflows 4 3,2

Having a sophisticated role (and project) based tool to manage access rights of users 5 2,8

Part 4 Knowledge collection and re-use Priority

Average ranking

Organizing and collecting your organization's knowledge (e.g. past projects) 1 4,7

Being able to find and re-use knowledge about past projects 2 4,7

Being able to collect "new" knowledge in the shop-floor to improve performance in your future projects

3 4,5

Using IT-based decision support tool (i.e. your engineers) in the design processes 4 4,3

Part 5 AR technologies application Priority

Average ranking

Using AR tools for training purposes 1 3,8

Supporting your shop-floor operator with AR tools and technologies 2 3,7

Supporting your shop-floor personnel with AR equipment for communication with engineering department

3 3,2

In order to enrich the pool of potential end users to be engaged, it is worthy to keep the survey open and up to date and to keep promoting it through the channels described. This will ensure that a valuable set of data will validate these preliminary results. Moreover, it has to be noted that email have turned out to be a not effective dissemination channel, especially based on the fact that email addresses used do not allow to reach the relevant person within the organization. In order to face this problem a more capillary distribution of the questionnaire will be planned and put in place in order to extent feedback.

2.14 Focus on academic partners exploitation plan

The academic partners’ main focus will be the inclusions of their Know4Car developments as part of educational courses, undergraduate and post-graduate and the support of Ph.D. theses. Further details can be found in D71.2, the dissemination final report. Moreover, the Know4Car development will enhance the consultation competences of the academic partners to several European industrial partners. Finally, the output of the project will form the basis for further research and development actions; future launches of research projects in collaboration with existing partners and/or similar organizations are expected after the project’s completion. Moreover, as described in sections 2.8 to 2.11, LMS and Chalmers will also be involved in maintaining the applications and services of their responsibilities developed within Know4Car for future use by end-users.

2.15 Post-project exploitation actions

Some more resources have been allocated to exploitation activities with the aim of maximizing the impact of the Know4Car project as well as the chances for further exploiting the Know4Car developments. In order to achieve a further exploitation of the Know4Car tools by the industrial partners the K4C applications will be reconfigured as distinct applications in order to be used separately. The main pillars of this new plan are described hereafter. The K4C platform will be deployed and maintained in the premises of LMS by both LMS and PDTec, supporting standard scenarios to be implemented by external users. It will support project and file management including all features developed in the context of Know4Car (semi-automatic task allocation, change management etc.).




Within the Know4Car Consortium, this means that the platform will be accessible and usable from industrial partners, mainly Volvo, EDAG and BAZIGOS, directly from their workplaces. The Assembly precedence diagram generation (APDG) tool, both for CATIA and an additional tool selected by CRF, will be further refined / redeveloped, which will be adjustable to different versions of existing CAD SW (past and future). Assembly Line Balancing (ALB) and Decision Support Agents (DES) will be configured as distinct services and will be deployed on a web-based form with public access separately from the platform. Within the Know4Car Consortium, the partners which will make use of this tools are Volvo, EDAG and CRF. The variability management tool will highly likely become part of Volvo IT tools in the near future. Moreover, a second workshop has been organized in Turin where a number of external partners belonging to the MESAP and the ICT Piedmont Innovation Cluster have been invited. More information about the deployment plan and the collected feedback from end-users are reported in an additional document, D72.7, in order to better communicate the business issues and trends. This document will be public and could be used for the creation of additional project topics and will also be disseminated to companies in the relevant markets.

Page 41 of 120 Exploitation Evaluation Strategy



3 EXPLOITATION EVALUATION STRATEGY

The exploitation activities’ effectiveness should be evaluated during the project development, starting from year 2, in order to evaluate performances vs. project’s objectives. Methods and tools to evaluate effectiveness of exploitation will be better defined along the project, although a useful tool can be represented by radar chart. This is a graphical method of displaying multivariate data in the form of a two-dimensional chart that can give a fast and intuitive perception of project’s exploitation performances.

Performances indicators that can be uploaded during the project development could be:

Number of cooperations activated vs. planned;

Number of industrial communities or organizations involved vs. planned;

Number of new patent applications;

Number of educational courses/Ph.D. activated vs. planned;

Number of exploitation seminars organized by each partners and other specific exploitation/dissemination activities;

Number of licenses sold after two years after the end of the project;

Number of users using the platform (or a specific component) after two years after the end of the project.

Exploitation effectiveness can be further evaluated after the end of the project by referring to the number of customers involved as beta testers, number of licenses sold within one year from the end of the project, number of new products developed or to be developed exploiting projects results, etc. This activity can be undertaken in close collaboration with SP8, project management, which is more interested in technical and economic monitoring of the project. The following table shows the main achievements until month 51.

Table 11: Achievement indicators and their values.

Indicator Value Comments

Number of cooperations activated

10 PlantCockpit; VFF; e-Custom; KAP; VirtCom; COSMOS; SkillPro; Apps4aME; amePLM; LinkedDesign

Number of specific exploitation actions

3 questionnaires 2 questionnaires to IAM’s associates, 1 questionnaire to EU SMEs (results of the latter expected end of September 2013)

Number of new patent applications

3 patent applications for the PACE (See section 2.2.4).

Number of workshops 5 2 workshop @Volvo plants with Volvo engineers; 1 workshop @CNH plant; 1 workshop @IAM with engineers from companies of the IAM Consortium and a number of external partners; a 2nd workshop where external potential customers have been invited took place in November 2015 at MESAP Innovation Cluster premises, in Turin;

Number of educational courses/Ph.D. activated

3 Four PhD theses are currently supported in the academic partners.

Number of conferences/events 4 • Joint action between Know4Car and Vistra project (12th IFAC/IFIP/IFORS/IEA Symposium).

Exploitation Evaluation Strategy Page 42 of 120



• EFFRA Assembly Workshop, 7 June 2013 – presentation to other relevant project

• PLM Conference 2013 – presentation of the Know4Car project to PLM developers and people from the industry

• IMAGINE FoF 2020 Conference, 12-14 June 2013 – Discussion on current challenges, including exploitation, with other European projects

3.1 Risk assessment strictly related to Exploitation

The following table summarizes risks strictly related to the exploitation with the sub-project/s they are connected to and the possible solutions, which have already been or can be put into action.

Table 12: Risks and mitigation actions related to exploitation.

Risk Type Relevant to Solutions and actions

Disagreement on ownership rules due too many different partners involved in the development

IPR risk Manufacturing Knowledge infrastructure (and model); AR tools for training and guidance of assembly processes;

IPR management within the exploitation WP

Potential customers could not be interested

Market risk All Do good dissemination and advertisement in order to diminish the likelihood;

Cloud-based collaboration platform;

Attractive offers (SW bundles)

Unspecific/ too general solution

Market risk Cloud-based collaboration platform;

Re-specify according to market needs

The solution could be rejected by end-users.

Market risk Manufacturing Knowledge infrastructure (and model); Lines balancing and optimization (ALB and DES agent); APDG; Information Extraction Agent; AR tools for training and guidance of assembly processes; System for tracking human operations + Performance indicators of human operators; Variability management application;

Developments are planned based on specific requirements of the end-users. Presentation of developments progress to end-users on a bi-weekly basis (SW TelCo); collect end-users feedback through workshops/questionnaires and adapt;

Cost for the solution is too high

Market risk PACE; Find multiple customers, the price will be lowered

Page 43 of 120 Exploitation Evaluation Strategy



Cloud-based collaboration platform

lower the cost, provide attractive SW bundles

AR system Wait till new gadgets and devices are available

Insufficient understanding of the value of the solution with potential customers

Market risk PACE; Do a good communication of the added value of the proposed solution

End-users are reluctant to new technologies introduction

Market risk AR system Training programme and slow adaptation stage planning

Cost of the investment too high

Financial risk PACE; Get more interest from customers;

Solution does not provide the needed ROI to justify such an investment

Financial risk AR system Get more interest from customers;

No further budget after project-end to continue developing the solution

Financial risk AR system Find potential customers who may co-finance

Personnel is no longer available to transfer implementation knowledge

Personnel and organization related risks

PACE; Retain people;

The organization is not interested in exploiting the result for the moment

Partnership risk

AR system Wait for the organization to resume this research line as part of its strategic research agenda

Low Quality services (bugs)

Technological risk

Cloud-based collaboration platform;

Testing; continuous improvement

Solution not providing industrial-grade needed accuracy and robustness

Technological risk

AR system Further research/development

Scalability with amount of data to be handled in time

Technological risk

SQL Bridge; Cloud-based collaboration platform;

In depth testing (infrastructure and services)

Critical performance requests on database

Technological risk

SQL Bridge; Cloud-based collaboration platform;

Continuous debugging and logging

Exploitation Evaluation Strategy Page 44 of 120



Worthless result: performance lower than market needs.

Technological risk

Manufacturing Knowledge infrastructure (and model); Lines balancing and optimization (ALB and DES agent); APDG; Information Extraction Agent; System for tracking human operations + Performance indicators of human operators; Variability management application;

Developments are planned based on specific requirements of the end-users.

Presentation of developments progress to end-users on a bi-weekly basis (SW TelCo).

Page 45 of 120 Conclusions



4 CONCLUSIONS

The current deliverable showed that a number of software outcomes can be exploited commercially from the development partners and that the end-users are growing to be even more interested in using them. Actions for enhancing the exploitation capabilities of the K4C components include questionnaires to the SME world, the latest of which has been sent to a great number of SMEs that span across Europe. Moreover, other actions to keep end-users in the loop have been put in place. Five end-users workshops have already took place: the first at Volvo premises, a second organized by CRF at CNH Jesi plant, then the two workshops organized by IAM, one in Abruzzo in 2014 and one in Turin in 2015 and a second workshop took place at Volvo in June 2015. During these events both presentations and demos have been showed to the industrial partners, engineers and shop floor operators, in order to collect additional feedback and suggestions on current and future developments. During the workshop hosted by the MESAP Innovation Cluster in Turin in November 2015, the last integrated prototype of the platform and also the Co-Innovation initiative from SAP have been presented. The acceptance of the users at this last workshop was quite high, and this seems to confirm the expectations for the future of such a product. The risks identified are constantly being mitigated mainly through the inclusion of the industry partners in all of the development cycles and the proper and wide dissemination of the ongoing results of the project. Furthermore, through the early definition of the use cases and the use of industry defined scenarios the outcome of the project is expected to be highly exploitable, especially by the main development partners. For the time being many developments carried out within the Know4Car project framework are already on the market and this is the case for example of PDTec developments which have already been integrated in the current PDTec portfolio. The same will happen in the near future for the Product Cost Calculation tool within SAP, which is in the validation phase, and for the tools and applications developed by Chalmers and LMS which will make available to the users in different forms and will be also part of future developments to broader their scope (e.g. Variability Management and Assembly Precedence Diagram Generation). The Co-Innovation project put in place by SAP is targeting a commercial product for the PACE to be ready by 2017.

Appendix A – Questionnaire to European SMEs – End users' Feedback questionnaire Page 46 of 120



APPENDIX A – QUESTIONNAIRE TO EUROPEAN SMES – END USERS' FEEDBACK

QUESTIONNAIRE

SMEs FEEDBACK QUESTIONNAIRE

Organization name:

Organization country:

Part 1 Organization information

1.1 Your organization-type yes/no

offers and provides engineering services

is a system integrator (e.g. from design to installation of an automatic

production line)

is a final product or raw material

manufacturer

is a part or equipment/tool supplier

other (specify)

1.2 Your organization-dimension yes/no

your organization is an SME (1)

has less than 250 employees



1.3 Your organization-additional information yes/no

mainly operates in your Country

mainly operates in the EU market

operates worldwide

1.4 Your organization is characterized by 1-not at

all 2 3 4

5-definitely interested

high responsiveness to customer

demands

short time-to-market

highly customized production

high production/service flexibility

many products/service under

development at the same time

wide range of products/services offered

to customers

Page 47 of 120 Appendix A – Questionnaire to European SMEs – End users' Feedback questionnaire



Part 2 ICT use in your Organization and expectations

2.1 How would you be interested in using the following ICT technologies in your daily business?

1-not at all

2 3 4 5-definitely interested

Web-based technologies (applications

using web infrastructure, e.g., Internet, Intranet)

Cloud computing (Platform as a Service, Software as a Service, Infrastructure as

a Service) (2)

Advanced UIs and augmented reality

tools

2.2 You are more willing to buy an ICT tool for your organization

1-not at all


under a license base (major initial

investment costs)

under a token base (it is possible to buy

a number of token licenses)

2.3 Which parameters are you taking into higher consideration when choosing an ICT tool

1-not at all


initial investment costs (e.g. license) - choose 5 if you are willing to pay less

customization possibilities

easiness-to-use (user friendliness)

possibility to interface with other tools

(e.g. CAD/CAM or PLM tools)

How much would you be interested having a tool which supports

collaboration by integrating project management, complex workflow

management and data access?

2.4 ICT investments and costs

How much does your company usually invest in ICT tools per year? (magnitude order)

How much does your company currently spend on ICT tools per year? (magnitude order)

How much are you willing to pay for such a solution? (magnitude order)

Appendix A – Questionnaire to European SMEs – End users' Feedback questionnaire Page 48 of 120



2.5 You currently use within your organization

yes/no

CAD/CAM tools

PLM tools

ERP or CRM tools

Standard file formats (e.g. STEP,

AutomationML, etc.)

Part 3 Communication and collaboration with other organizations or within your organization

3.1 How much would you be interested in 1-not at

all 2 3 4


smoothing and streamlining the

communication across departments within your organization

having a secure and safe information

sharing inter and intra organizationally

sharing projects' related information

with a supplier/customer

having a sophisticated role (and project)

based tool to manage access rights of users

having an ICT platform which is able to

handle complex collaborative workflows

Part 4 Knowledge collection and re-use


all 2 3 4


organizing and collecting your organization's knowledge (e.g. past

projects)

being able to find and re-use knowledge

about past projects

using IT-based decision support tool (i.e. your engineers) in the design processes

being able to collect "new" knowledge in the shop-floor to improve

performance in your future projects

Part 5 AR technologies application


all 2 3 4


supporting your shop-floor operator

with AR tools and technologies

using AR tools for training purposes

supporting your shop floor personnel

with AR equipment for communication with engineering department”

Part 6 Contact:

6.1 Your role within the company:

Page 49 of 120 Appendix A – Questionnaire to European SMEs – End users' Feedback questionnaire



6.2

Your email address in case you would like to receive our newsletter or in case you would like to be invited to a Know4Car presentation/workshop

Thank You for Your Cooperation!

The Know4Car Consortium

Notes

(1) For more information: http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/sme-definition/

(2) For more information: http://www.rackspace.com/knowledge_center/whitepaper/understanding-the-cloud-computing-stack-saas-paas-iaas

http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/sme-definition/

http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/sme-definition/

http://www.rackspace.com/knowledge_center/whitepaper/understanding-the-cloud-computing-stack-saas-paas-iaas

http://www.rackspace.com/knowledge_center/whitepaper/understanding-the-cloud-computing-stack-saas-paas-iaas

Appendix B – Categories Contributing To The Ar Market By 2018 Page 50 of 120



APPENDIX B – CATEGORIES CONTRIBUTING TO THE AR MARKET BY 2018

The categories contributing to the AR market including the respected challenges can be seen below:

Table 13: Categories contributing to the AR market by 2018

Market Business Model and Product Directions Challenges

Retail and promotional

Virtual shopping malls AR-enhanced checkouts Part of Web designer pallet

Loss of “wow” factor Technical challenges

Entertainment and gaming

Mobile games (mature) Sports-related games Games for AR glasses

Successful games are rare Optimization of AR glasses (wearable in general) needed

Education and instructional

Adding information to print “Go inside” services

Early stage How useful is added info

Communication and collaborations

Enhanced videoconferencing, messaging and social networking

Unclear what market needs

Navigation, travel and location-based

Can be priced “high” Revenue from locations

Keeping info current

Page 51 of 120 Appendix C – Focus on end users and academic partners’ exploitation plans



APPENDIX C – FOCUS ON END USERS AND ACADEMIC PARTNERS’ EXPLOITATION PLANS

Table 14: End users exploitation focus.

Partner Volvo

Volvo will focus on internal exploitation of the project’s results through internal operational development activities. Exploitation of the project results will be governed by Volvo’s Technology Area Steering Committee – Supply Chain (TASC-SC). The TASC-SC has corporate responsibility for identifying and disseminating strategically-important manufacturing developments throughout the Volvo Group. Volvo focuses on following results:

Capturing and reuse of knowledge (3.1/3.2.2)

Project management functionality (3.1/3.4)

One central access point for production data for all partners (1.2) Specific exploitation activities performed by Volvo may be summarized as follows:

To demonstrate the Know4Car platform as a whole as well as separate features on Volvo TEC-events

To show the Know4Car developments to relevant people within the organization in order to get feedback

To publish results in Global Magazine, a quarterly magazine sent out to all Volvo employees, printed in over 30 languages.

After the project ending Volvo is one of the industrial partner who will continue to make use of Know4Car solutions in their daily business. In particular Volvo is interested in using:

- The Collaboration Platform - The Variability Management Application - The APDG and ALB/DES tools

In order to do so the work will pass from the research division to the Volvo Group Trucks Technology (GTT), which is in this case is responsible for the integration of support tools in the product/technology development process. The need to set specific partnership agreement with partners will be assessed in the future according to each case.

Partner EDAG

EDAG is planning to use the platform in its everyday business in order to gain

more competitiveness in acquisition an execution of complex projects.

smoother, faster and more efficient cooperation with OEMs and Suppliers , through a systematic use of the platform;

The utilization of the platform, through the products and services of EDAG, by large automotive manufacturers can increase product and process development indicators:

Up to -10% in process design cycle (1st year of implementation).

Up to -20% of process development costs and cycle-time (during the first 2 years of fully integration in the design process chain).

+5% expansion of customer base for Turn-key Facilities BIW services (within 3 years after the end of the project).

EDAG focuses on following results:

Capturing and reuse of knowledge (3.1/3.2.2)

Project management functionality (3.1)

Common project data platform for internal engineering, customer and suppliers (3.2)

Specific exploitation activities performed by EDAG may be summarized as follows:

Discussing of Know4Car functionalities with potential customers to show the advantages, according to what described above;

Improve internal project management methodology parallel to specification activities for Know4Car.

Appendix C – Focus on end users and academic partners’ exploitation plans Page 52 of 120



After the project ending EDAG will continue to make use of the collaboration platform and of all the engineering services such as APDG and ALB/DES agent which are very relevant to their core business. Moreover EDAG, in quality of system integrator, may be interested also to the Variability Management. The participation to the SAP Co-Innovation initiative is under evaluation.

Partner CRF

Exploitation activities of CRF will mostly consist in the promotion of the K4C achievements towards the industrial end-users of the FIAT group. Many activities of CRF in the project are related to the application of the AR subsystems of the K4C platform to the manufacturing domain. The aim is to involve stakeholders of the above end-users for the implementation of innovative HMIs for reducing the cognitive and physical load of the users, allowing operators to perform tasks more efficiently and improve the user’s interaction with machines by augmenting the degree of control and the cognitive awareness in a closed loop fashion. CRF focuses on following results. Support for operative production processes (various requirements)

AR application for station recognition, marker less tracking, parts recognition and visualization, human tracking (various requirements)

Interaction between user and K4C platform (3.7) Specific exploitation activities performed by CRF may be summarized as follows:

To involve end users belonging to the FIAT group to the use-cases;

To promote the K4C platform as a whole as well as separate features on specific events dedicated to the industrial end users of the FIAT group;

To establish direct links and collaborations with the stakeholders of the above end-users (e.g. CNH) in order to apply innovative HMIs.

CRF is highly interested toward the developments in terms of VR/AR from LMS, Chalmers and TECNALIA. During the project life, CRF get the commitment of the CNH group; the CNH group also hosted one of the Integration Meeting in July 2014 where the main developments, especially in the field of solution for training and human performance evaluation, were presented to end-users. After the end of the project, this may results in further collaboration between partners on these fields in order to obtain a viable industrial solution that can be applicable in an industrial environment for training or testing purposes. Moreover, LMS developed the APDG in a different tool (Siemens NX) in order to be used by the CRF related partners (FIAT etc.).

Partner IAM

IAM will focus on internal exploitation of the project’s results through the promotion of the K4C achievements and innovation contents towards the IAM Consortium itself; IAM will also attempt to involve other end-users and similar Italian/European associations/organizations; The extended engineering components for the collaboration along the supply chain represents for IAM an important outcome of the project. Other results of major interest for IAM are:

Project management functionality (3.1 – 3.4)

One central access point for production data for all partners (1.2)

Common project data platform for internal engineers, customer and suppliers (3.2)

Web-based access to manufacturing data and knowledge (3.7) Specific exploitation activities performed by IAM may be summarized as follows:

To get feedback from IAM Associates, especially SMEs, inform them about project progress and, if possible, to involve a small number of Associates, representing a small supply chain, in a concrete test case;

To present and/or demonstrate the Know4Car platform as a whole as well as separate features on workshops at IAM or other locations, also inviting other project’s partners and external stake-holders;

To contact external end-users to get technical commitment to the project

Page 53 of 120 Appendix C – Focus on end users and academic partners’ exploitation plans



o by sending questionnaires to specific groups of people through different channels to inform them about Know4Car and collect feedback from potential customers;

o by organizing promotional events dedicated to these end users towards the end of the project;

o by participating in dissemination events, such as the one which took place in June 2013in Turin (ATA conference).

IAM is interested towards the collaboration functionalities of the tool. In the end of 2014 and the beginning of 2015 IAM had worked, together with SAP, in the setting up of a trial project as continuation of the Know4Car project to go on with the developments in the field of collaboration. This initiative was turned down and the current approach of SAP is now represented by Co-Innovation project proposal. As post-project activity, IAM is now considering the possibility of joining this initiative presented by SAP at the Turin workshop in November. The current plan is to select a limited number of companies belonging to the IAM consortium which may be highly interested in the solutions developed and to perform restricted usability testing in order to show the current status of developments of the prototype (mainly the collaboration platform) to get their commitment to join the initiative by, for example, signing a Letter of Intent. Being IAM a Consortium, it is essential to get commitment from associates, and this can also drive to a kind of network effect within the IAM perimeter. The usage of the platform or other services within IAM itself would not be a feasible solution, on the contrary it may impede in some way a smooth cross-organizations collaboration.

Partner BAZIGOS

The main interest of BAZIGOS is on the outputs of SP4 and SP5, which can have a great impact on the everyday practice of human-based manufacturing firms like BAZIGOS S.A.

Extended engineering: BAZIGOS will make use of the extended engineering components since its main interest is in the field off cooperation with OEMs. Additionally, BAZIGOS will set up local hardware that is now absent from the company. Meetings with strategic partners have already taken place, and there is specific interest from two parties that are already in close collaboration with each other, a mold maker from the Netherlands and one of the largest plastics producer in Greece, with presence in more than 30 countries.

Augmented Reality: BAZIGOS will use the Augmented Reality visualization developments for process guidance by engineers to shop floor workers. Training new employees or cross training experienced technicians of diverse expertise is very important, especially in the tool making industry. Two main operations are envisioned to be supported by the AR tool for training purposes: workpiece preparation, mounting and calibration on the VMC work tables, and mold assembly and disassembly.

Appendix D – Results from the second questionnaire sent to IAM’s partners Page 54 of 120



APPENDIX D – RESULTS FROM THE SECOND QUESTIONNAIRE SENT TO IAM’S PARTNERS

The SMEs of IAM were provided with a new questionnaire which targeted their communication and data exchange “habits” with their clients. A percentage of 20% is not organized into specific departments which have different roles and perform specific tasks. This was evident in SMEs that have smaller sizes.

Figure 18: Organization’s internal structure

Regarding the existence of an organized central repository, 75% of the SMEs have one, and all that work with the automotive industry use one which is encouraging for the embracement of the K4C related technologies.

Figure 19: Availability of a central repository for projects’ data

The access to these repositories is mostly user based which seems to be in line with what was observed by the other organizations.

Figure 20: Permission management to this repository

Finally, a main problem that the SMEs expressed was the lack of access to the relevant data from the client’s (OEM) repository.

Figure 21: Access to a specific customer’s data repository/database

Page 55 of 120 Appendix E – Results from End-users Workshop, December 3, 2014



APPENDIX E – RESULTS FROM END-USERS WORKSHOP, DECEMBER 3, 2014

Comments from end-users

1. When the action item of the type “aiNumiWallType” for uploading the NumiWall is repeated,

but no new NumiWall is uploaded, the NumiWall shown at the validation is empty

2. It should be made clearer what are required fields and what are not. A simple * with the fieldname

suffices. Some issues regarding specific screens:

a. At the project request, it does not make sense to only allow to submit when a comment

has been given

3. At the Operation Plan & Sequence it does not make sense to allow a submit where no file has been

uploaded

4. After logging in as Phyllis Robinson there is nothing in the area “running project”– This is due to different ways of interpreting the meaning of a “real project” and a “project request” (Is the project request a project itself?)

5. There was a question regarding the overlap between set in progress and save. Shouldn’t be a set in

progress also be a save?

6. There was a remark regarding the overlap between comments on an action item and on an issue:

maybe it is better to remove the action item comments.

7. It would be nice to have a list to see a list of the possible file to downloads and choose what to

download

8. In the “Validation” action item people had a problem with the set-up of the screens, for example it

was commented that the static tabs (the tabs showing purely the data –Input details, Input

overview, etc.) and the issues tab (where the issues are entered) are shown so similarly, the tabs

are completely the same even though the functionality is quite different. We were looking for a

way to show the difference between the aspects. Moreover, it was not clear what the semantics is

of submitting the validation action item without entering any issues. As a simple solution (closest to

what it is now) we came to the following:

a. Make a stronger difference between the static tabs and the dynamic tab (maybe also

change the sequence or the placing between them?)

b. When there are no issues, the submit should be: “Submit as valid” (or something like that)

or “submit” can be replaced with “validate” in all the tabs, apart from the one related to

issues overview and submission.

c. When there are issues, the submit should be: “Submit issues”

d. In the future it would be nice to have the possibility to delegate the validation of a task, etc.

to someone;

9. General remark: A project can be closed only if there are no issues? Currently yes.

10. In the overview of the issues, show that we know who has to do it. So add a field: responsible. It

seems ok if currently this responsible cannot be changed.

a. In the future it will be nice also to be able to choose who is going to take care of the issue.

11. Project request approval: When there are documents to download, that should be clearer.

Optimally, there should be a list of the documents that can be downloaded.

12. Staffing: The current way we work with staffing is not so clear. Some remarks:

a. Roles are below the tasks to be associated – not so clear, since you first need to assign roles;

b. It should be simple to use a (fixed?) People <-> Role mapping, similarly as it has been

realized in ICE.net? Yes, Usually the staff is already “fixed”, staff and we just need to assign

tasks (roles are already known);

c. Thus, the purpose should be to:

i. Use that fixed mapping (or import such a mapping also from external PM tools)

ii. Use that mapping to assign people to action items

Appendix E – Results from End-users Workshop, December 3, 2014 Page 56 of 120



d. If no reviewer had been assigned in the previous step, it is not possible to choose who does the validation (and no error message/suggestion is shown)

13. The save has not been implemented yet. How much work will it be to really implement the save?

Can we add a functionality when someone goes away from a page (closes it or goes to another

page in the application) the system asks whether we want to save the results?

14. A general remark about the way a project is started: better to have a button on the bottom right

a. Not very clear why there is also a “stop” button

15. When uploading Op Plan&Sequence, the “submit” button is already on even if no actions has been

done yet

16. It looks strange that who has to take care of the issue (Nathan - EDAG engineer) can both “set in progress” the issue (button at bottom right) and put the issue “in progress” from the bottom down menu.

Comments for future improvements

1. Calculation of Cycle time: the entering of the data to calculate the cycle time is not always

appropriate. Sometimes it is known what the cycle time is. Note: the excel integration approach

could help here.

a. nice to have the possibility to choose between using the embedded form and loading a

different calculation form and also the possibility to insert only the result(since sometimes

you already know the cycle time)

2. Issues could be raised to a higher level: this is not an issue that is at my level, it is a higher level

issue (e.g., the complete production line is flawed)

3. The Validation Process itself could be delegated to different people: there are different experts that

do part of the validation

Page 57 of 120 Appendix F – Final Key Exploitable Results report



APPENDIX F – FINAL KEY EXPLOITABLE RESULTS REPORT

ER1: PACE – PlAtform for cross-supply Chain Engineering

GENERAL DESCRIPTION OF THE RESULT

D-1

Number 1

D-2

Title PACE – PlAtform for cross-supply Chain Engineering

D-3

WPs WP31 WP62

D-4

Deliverables D31.1 D31.2 D31.3 D31.4 D31.5 D31.6

D-5

Partner Number 2 Partner Acronym →

SAP Contact Person →

Theo Dirk Meijler

D-6

Nature of the result Product

D-7

Level of achievement (Select from the drop-down menu)

40% (A percentage is not applicable here. It is a working prototype.)

D-8

Expected Completion date End of 2017

I-1

Partners interested in exploitation

SAP PDTEC

I-2

Partners with BK for this result

SAP

I-3

Partners with FK for this result

SAP

E-1

Description of the results

PACE is a platform for collaborative project execution and will provide: • Collaboration support for development of products and production facilities

o In particular when new products are to be developed or when a change request of products or/and equipment facilities is issued;

• Support for inter-organizational collaboration: o Offering a multi-tiered support: OEM (such as Volvo), Integrator, equipment & component suppliers

• Support for intra-organizational collaboration: o Involving all the departments/areas within an organization: Product development, Product & production preparation, Production development, Production execution

• Support for collaboration between production & engineering organizations: The main functionality can be described as the possibility to integrate project management, (engineering) workflow and data access 1. Supporting Project Execution, enabling the link between the classical project management in terms of planning and tracking, and the daily “execution” of projects, the definition of simple work-items, the tracking of their execution etc.

1a. Work-items provide access to the relevant data 1b. Executable sub-structures (sub-projects, tasks) have an in-built iteration, corresponding to validation and issue handling 1c. Project structures can be ad-hoc adapted 1d. An integration bridge allows external applications to integrate with the platform. External applications can download data, update adapted data, and communicate status changes

2. Supporting Collaborative Project Execution, allowing assigning work-items to external partners (suppliers), and allowing also suppliers to set up their own projects (so-called delegated projects) to deliver for the assigned work-item. This includes that both control flow as also data flow is exchanged between the original work-item and the delegated project. This latter aspect creates a network effect, and allows, in principle to let whole supply-chains to work together over such a solution.

Appendix F – Final Key Exploitable Results report Page 58 of 120



E-2

Brief description

A cloud platform for “Collaborative and Agile Project Execution” which covers a broader domain, including professional services mainly in three domains: • Collaborative Engineering (PACE); • Collaborative Professional Services; • Collaborative Engineering Construction & Operations Networks of collaborating partners can be supported

EXPLOITATION

For each exploitation provide the nature and forms (use the drop-menu to select)

Exploitation-1 Exploitation-2 Exploitation-3 Exploitation-4 Exploitation-5 Exploitation-6

F-1

Natures of the exploitation

Licencing Selling Customisation

F-2

Form of the exploitation

Internally Memorandum

of Understanding

Partnership agreement

CONFIDENTIALITY

Please specify the confidentiality of the content of this file. You allow access to →

Consortium Partners

Exploiting Partners

Specific Partners European Commission (by law)

All public Other

C-1

Requested Status by the exploiting partners (Select Yes or No from the Drop-Down menu)

YES NO NO YES NO NO

C-2

List of authorized organizations if access is allowed to specific partners)

DEPENDENCY ANALYSIS BETWEEN THE EXPLOITABLE RESULTS

List of project results R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14

The exploitation of his result depends on the exploitation of →

X



CHARACTERIZATION

What is the TRL? (see tab “TRL” if you're not familiar with this) – Use the drop-down menu to select the level

NA

What are the markets / customer(s) for this exploitable result? (If the result is only to be used by your company – please state this).

CUSTOMERS: PACER targeted groups of customers can be grouped as following: 1. Projects based on collaborative engineering such as Organizations doing engineering together/Large organizations where multiple departments are involved in engineering processes/ 2. Projects involving collaborative engineering and realization phase such as Organizations doing engineering together AND realization. 3. Projects involving manufacturing and engineering processes such as Organizations doing manufacturing, working together with engineering




organizations (Example: factory equipment) SAP expects that the potential target markets will be in the area of “discrete industries”: • Automotive • Industrial Machinery and Components • Aerospace and Defence • High-tech industry

What benefit will the exploitable result bring to the market/customer(s)? (If only internal to your company – please state what the benefit to your company will be)

PACER offers the following benefits: • It is a platform targeted for large-scale organizations: it ensures data – process – project (DPP) engineering integration across departments; • For all kind of organizations (large scale as well as small scale) it offers DPP integration across companies for development purposes: in the engineering, development & ramp-up processes; • It provides support to manufacturing organizations working together with engineering organizations, especially regarding equipment development, both in green and brown field.

When will the result be achieved by you (year / month)?

17

When will the result be launched to market / customers (DD/MM/YYY)?

Q1 2017

What costs are likely to be incurred after the project funding has ended in order for you to fully exploit this result (Euros)?

This is to be determined

Is there any competitive alternative(s) to this result?

The main market players and competitors in this market are: a. Other organization offering Collaborative Project Execution for Engineering - TeamPlatform - Engineered to Fly b. Organization offering Cloud Project Execution - Clarizen - Project Management -Project Pro for Office

If so, how does this result compare with the competitive alternative(s)?

Especially the competitors under a. are of relevance. Our targeted product is better in supporting networks of collaborating organizations, amongst others, projects can be linked with each other for automatic data and status exchange

How is your competition likely to respond to this result?

They may want to include the organizational collaboration feature

What commercial benefits are likely to be achieved by this result e.g. Increase in sales, reduction in development / production / logistics costs, new products, new markets etc.?

Licenses will be sold on per usage basis, thus leading to high possible revenues

What societal benefits are likely to be achieved by this result e.g. job creation and / or existing jobs supported (state how many), local economic improvements etc.?

The result will be open for integrating with all kind of engineering software, thus creating a new software ecosystem, and a basis for further innovation

What environmental benefits are likely to be achieved by this result e.g. improved health & safety, reduced solvents, emissions, waste carbon footprint etc.?

NA

What research / technological benefits are likely to be achieved by this result?

Conceptual and technical improvements have been laid down in several patents

Which other project partners have been involved in developing this result?

NONE: the collaboration platform has been solely developed by SAP

Which other project partners would be interested in exploiting this result?

SAP PDTEC

Have you protected this result or planning to do so? In what way?

Patents

What other benefits are likely to arise from this result that are not covered elsewhere?




BACKGROUND

#

Type of Knowledge (Expertise, software,

patent, product, process,...) and details

Organization’s

acronym Description (text)

Estimation of Importance of this knowledge for the result (in

%)

Consensus reached (Y/N) [Partners agree

with you on the shares of BK]

Actions requested from your perspective

to reach the consensus if not

reached

1 Expertise SAP Expertise in IT tools development

100% Y

2

3

4

5

The exploitable result is a SOFTWARE product. Partners like Volvo, EDAG and BAZIGOS have helped us to understand their processes, but our exploitable result is NO Process. Process Knowledge from these partners has been generalized to create a viable product. But this generalization was our own work, and its result is therefore SAP IP.

FOREGROUND

#


patent, product, process,...) and

details

Organization’s


Estimation of Importance of this knowledge for the result

(in %)

Estimation of the effort

provided to reach the

result (in %)

Consensus reached (Y/N)

[Partners agree with you on the

shares of FK]

Actions requested from your

perspective to reach the

consensus if not reached

1 Know-how SAP Generalized industrial process knowledge

100% 100% Y

2

3

4

5




GROUND IDENTIFICATION FORM / PUDF

SUMMARY FROM PREVIOUS TABLES

VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X

3 Exploiting Partners with background knowledge X

4 Exploiting Partners with foreground knowledge X

ACCESS RIGHT - FOR PARTNER NOT WILLING TO EXPLOIT THIS RESULT

5

Non Exploiting Partners providing background knowledge willing to claim rights

6

Non Exploiting Partners providing background knowledge NOT willing to claim rights

However may request NDA on their Background Knowledge

7

Non Exploiting Partners providing foreground knowledge willing to claim rights

Regardless if they plan to exploit the result or not

8

Non Exploiting Partners providing foreground knowledge NOT willing to claim rights

However may request NDA on their Foreground Knowledge

9

Non Exploiting Partners without foreground willing to claim access right

Secured by the CA

10

Non Exploiting Partners without background willing to claim access right

Secured by the CA




11

Status as regard the exploitation right from other partners

FREE NEGOTIATION NO

In case all the non-exploiting partners agree to transfer the

exploitation rights to the exploitation team

In case there is still room to clarify the IP/IPR

In case at least one partner do not agree to transfer the

rights (VETO)

YES

NATURE OF ACTIVITY FORESEEN FOR THIS RESULTS BY THE PARTNERS

VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

12 M Manufacturing, Realization

A Assembly

R Research X

C Consultancy, Training, Education

U Utilization in other business not listed elsewhere

S Selling, Distribution, Licensing X X

S Services (maintenance, promotion etc.)

X X

Y N

13 Consensus: There is a total agreement between the consortium members.

X Put a cross for YES in case no partner did block the exploitation (for whatever reason)

14 Ad hoc Partnership building X YES in case you agree to consider going for specific partnership with the other partners as listed in 2-4

15 New legal entity X YES in case you agree to consider setting a new legal entity with the other partners as listed in 2-4

16 Single engagement (internal use only of the result) X YES in case we got the acceptance from all partners that you can exploit in a free way





ER2: Product Cost Calculation


D-1

Number 2

D-2

Title Product Cost Calculation

D-3

WPs

D-4

Deliverables

D-5


SAP Contact Person →

Theo Dirk Meijler

D-6

Nature of the result Concept

D-7


100%

D-8


I-1


SAP

I-2


NA

I-3


NA

E-1


Know4Car has contributed several concepts (esp. around collaboration) and some prototypical implementations to a new software tool for calculating product costs.

E-2

Brief description

Research has shown how decisions made during early design phases determine the majority of the product's costs (up to 70%). This indicates the great leverages that an effective tool for product cost calculation can have on a company's success and profitability.

EXPLOITATION



F-1


Selling

F-2


Internally

CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other







C-1


NO NO NO YES NO YES

C-2


SAP






CHARACTERIZATION


8


This tool is especially suitable for product cost calculation in the domain of discrete manufacturing. Currently customers operating in the automotive industry, the high-tech industry and the machinery and components industry have requested a powerful cost calculation tool.


Research has shown how decisions made during early design phases determine the majority of the product's costs (up to 70%). This indicates the great leverages that an effective tool for product cost calculation can have on a company's success and profitability.


October 2015


October 2015


SAP will continue to invest in the development of the product cost calculation tool with a team of approx. 30 people.


Microsoft Excel and several niche market players


Better calculation performance, deeper integration with SAP ERP systems, better usability when compared to current product costing applications.


Competitors may address their shortcomings w.r.t. speed, integration and usability to stay competitive.


It will be a product, sold by SAP. Buyers will use this software for accurately estimating the costs of a new product, such that they can maintain their profitability.


If companies know their product cost early they are likely to be more successful for a longer period of time, i.e. their products will be more sustainable.


For example, automotive suppliers do not just calculate cost but rather use the same tooling to reduce weight and CO2 production of the cars they manufacture.


The main benefits of this result are related to business impact, both for SAP as for its customers. State of the art technology has been used to realize the result.






NO OTHER PARTNERS


ONLY SAP


SAP owns all IP as all work related to this topic has been solely done by SAP without the support of partners.


N/A

BACKGROUND

#



Organization’s



%)





reached

1 Expertise SAP Expertise in IT tools development

100% Y

2

3

4

5

The exploitable result is a SOFTWARE product. Partners like Volvo, EDAG and BAZIGOS have helped us to understand their processes, but our exploitable result is NO Process. Process Knowledge from these partners has been generalized to create a viable product. But this generalization was our own work, and its result is therefore SAP IP.

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]




1 Know-how SAP Generalized industrial process knowledge

100% 100% Y

2

3

4

5






VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X




5


6



7



8



9


Secured by the CA

10 Non Exploiting Partners without

Secured by the CA




background willing to claim access right

11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research

C Consultancy, Training, Education


S Selling, Distribution, Licensing X


X

Y N










ER3: SQL Bridge


D-1

Number 3

D-2

Title SQL Bridge – Intelligent data management for a seamless and robust data availability

D-3

WPs WP41 WP61 WP62

D-4

Deliverables D41.1 D41.2 D41.3 D41.4

D-5


PDTec Contact Person →

Hardy Krappe

D-6

Nature of the result Software

D-7


100%

D-8


I-1


PDTec SAP LMS Volvo Edag

I-2


PDTec

I-3


PDTec

E-1


Tool, which supports the integration of the K4C platform and other databases. It maps relational data transparently into ice.NET model with legacy data within ice.NET without replication and connects ice.NET to Master Data Management solutions. The SQL Bridge links the databases of the various partners in a common place, directly linked to the K4C ontology

E-2

Brief description Tool, which supports the integration of the K4C platform and other databases.

EXPLOITATION



F-1

Natures of the exploitation Licencing

service (training)

Lobbying/Advising

F-2

Form of the exploitation Internally

Partnership agreement

Internally

CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other





C-1


YES NO NO YES NO NO

C-2







CHARACTERIZATION


TRL 8


The SQL Bridge is part of the ice platform and therefore a component sold as part of the current ice.NET suite. The target group of the overall customer market is expected to be 3 – 4%.


It faces the current challenges represented by: • the total number of files and amount of data, • complex versioning and configurability of data • multiple domains, various philosophies about data storage, persistence, update times, data quality etc. Moreover: • It ensures an intelligent data management including domain integration (manufacturing, product planning, product design) and generic (reference) data model. • It ensures the full availability of the entire shared project data at all times, significantly reducing the time for data exchange or synchronization. • It benefits from shorter time to market, high versatility and acts as independent from domains and philosophies and as a prerequisite for international standardization.


15


already available


$0,00


sql bridging is a known method for IT companies


there are no distinct differences


It broadens PDTec's portfolio. Competitors will most likely developed a similar mechanism in case they don't have it yet


PDTEC’s product portfolio has been increased






NA


NA


NA


PDTec




no


NA

BACKGROUND

#



Organization’s



%)





reached

1 Expertise PDTEC Software Developer 100% Y

2

3

4

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]




1 Expertise PDTEC Bridging between objective and relational DB

100% 100% Y

2

3

4

5





VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X X X X




5


6



7



8



9


Secured by the CA

10


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research

C Consultancy, Training, Education X


X X X X

S Selling, Distribution, Licensing X


Y N








ER4: Cloud-based collaboration platform


D-1

Number 4

D-2

Title Cloud-based collaboration platform

D-3

WPs WP41 WP61 WP62

D-4


D-5


PDTec Contact Person →

Hardy Krappe

D-6


D-7


100%

D-8


I-1



I-2


PDTec

I-3


PDTec

E-1


Cloud based platform which will provide a collaborative development environment which enables data modeling and validation up to code implementation and validation (adapters, distributed and local, on- and offline synchronization, plug’n play, out of the box solution). The platform will be offered in combination with dedicated consulting and training services

E-2

Brief description cloud-enabled ice.NET platform

EXPLOITATION



F-1


service (training)

Licencing Lobbying/Advi

sing

F-2


Internally Partnership agreement

Internally

CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other




C-1


YES NO NO YES NO NO

C-2





X



CHARACTERIZATION


TRL 6


The cloud-enabled platform is part of the ice.NET platform and therefore a component sold as part of the current ice.NET suite. The target group of the overall customer market is expected to be 3 – 4%.


The added value of such a solution is seen mainly in the ability to offer a service-oriented Collaboration Platform in the cloud, in combination with dedicated consulting and training services to the market, thus extending the solution portfolio of PDTec and potentially extending its own customer base.


2015


it is already available on the market, we are introducing the new features to our customers


$0,00


many cloud providers, but the ice.NET platform is proprietary SW.


the feature is unique to our platform


enabling cloud service in their products


increased turnover, modern reputation to help create a strong innovative drive


NA


NA


NA


PDTec






no


NA

BACKGROUND

#



Organization’s



%)





reached

1 Expertise PDTEC Software Developer 100% YES

2

3

4

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]




1 Expertise PDTEC Bridging between objective and relational DB

100% 100% YES

2

3

4

5






VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X





5


6



7



8



9


Secured by the CA


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research



X X X X

S Selling, Distribution, Licensing X X


X

Y N










ER5: Full AR system (3 integrated modules)


D-1

Number 5

D-2

Title Full AR system (3 integrated modules)

D-3

WPs WP52 WP52 WP51 WP51

D-4


D-5


TECNALIA Contact Person →

Miguel Loitxate Cid

D-6

Nature of the result Prototype

D-7


70%

D-8


I-1


TECNALIA

LMS CRF

I-2


TECNALIA

I-3


TECNALIA

E-1


The AR Training Framework System is able to detect, track and augment objects with virtual information by means of markers.

E-2

Brief description

The framework provides, through its visualization module, assistance to operators in the workshop and an easy to use mechanism so that the operator can give feedback or report problems back to engineering department or phase

EXPLOITATION



F-1


Expertise Customisation

F-2


Research program

Under contract

Engineering Project

CONFIDENTIALITY

Please specify the confidentiality of the

Consortium Partners

Exploiting Partners


All public Other



content of this file. You allow access to →

C-1


YES NO NO YES NO NO

C-2





X



CHARACTERIZATION


TRL 5


The potential uses of AR application in Industry span the complete life-cycle of the product. It is, therefore, evident that any kind of industry that has a production line which changes the stations pieces and assembly operations from time to time can be a reference market: automotive, railway, aerospace, machine-tools, etc. AR market is growing and AR applications in the fields of maintenance and training are increasing.


• Reduction of time and costs when performing a task; • Get better understanding of assembly components and process; • Improvement of training processes and formation stage of new employees • Improve safety aspects of final assembly operators; • Improve the way to share information with end users; • Improve natural visualization of the augmented information; • Reinforce the communication between experts distributed all over the production, promoting the exchange of knowledge and exploiting different expert profiles.


16



N.A.


Customized solutions sold by Computer Vision based companies


N.A.


N.A.


N.A.






Improvement of training and formation methods so that all kind of new employees (specially young ones) can easily and faster access and adapt to a workplace


Avoid trips (and CO2 emissions) between remote scenarios and engineering/production plant


Major challenges faced in the development of this AR system are: • Accuracy required in tracking and registration in such applications. • Quality of the user’s experience. • Robustness and availability of these systems working at the shop-floor level. • Usability aspects of UIs (simple, intuitive, precise, etc.) and user acceptance. • Compliance to legal regulations, industrial safety aspects, ergonomics, human factors, cognitive strain on the users, etc. since engineering users of AR applications will spend large amount of time using this kind of systems.


TECNALIA


TECNALIA LMS CRF


No


N.A.

BACKGROUND

#



Organization’s



%)





reached

1 Algorithm/methodology

TECNALIA

Expertise in Computer Vision based algorithms and their customization

100% YES

2

3

4

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





TECNALIA

Combination and customization of Computer Vision based algorithms for a marker less approach, regarding objects recognition and tracking solutions

100% 100% YES

2

3

4

5





VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X X




5


6



7



8



9


Secured by the CA

10


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research X X X

C Consultancy, Training, Education X X


S Selling, Distribution, Licensing


Y N








ER6: System for tracking human operations + Performance indicators of human operators


D-1

Number 6

D-2

Title System for tracking human operations + Performance indicators of human operators

D-3

WPs WP21 WP31 WP41 WP52 WP52

D-4

Deliverables D52.2 D52.3

D-5


CTHA Contact Person →

Knut Åkesson

D-6


D-7

Level of achievement (Select from the drop-down menu) 100%

D-8

Expected Completion date Nov’15

I-1


CTHA VOLV

O

I-2


CTHA VOLV

O

I-3


CTHA

E-1


In order for advanced user-interfaces for shop-floor operators to be useful the right information has to be provided at the right time. A key problem is to estimate what the operator is currently doing so relent information is presented to the operator. Traditional systems forces the operator to press buttons or scan barcodes to inform the system about that a task has been completed. However, RGB cameras and more especially RGB-D (i.e. 3D-cameras) is now available of the shelf. The main research finding is a proof-of-concept implementation of a system with a 3D-camera that is tracking the movements of the operator for an assembly operation. A user interface where the operator gets the instructions for what to do next based on the computerized tracking of the movements. The system is fully automatic in the sense that the operator is not required to press any buttons or scan bar-codes to indicate that certain tasks have been fulfilled. The system might be used in training scenarios where the operator uses the instructions to build up the necessary skill. A consequence of tracking of the movements is the possibility to also measure performance indicators, like how often is a task done in the wrong way, how long does it take complete a certain task. This information might be useful in finding out the best way to assemble product.

E-2

Brief description

3D-cameras might be used to track the state of an operator and based on this give the right information at the right time to the operator. A relevant application is training of new operators that can then be assisted by a computer system that provide the operator under training with instructions that allow it to work efficiently.

EXPLOITATION






F-1


Service (engineering)

F-2


Research program

CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other

C-1


YES NO NO YES NO NO

C-2



List of project results

R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14



R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28


CHARACTERIZATION


TRL 4


OEMs. Sub-contractors. Logistic companies.


Fast training, less errors, possibility of finding out the most efficient and reliable way of assembling a product.


15


NA


NA


Yes


The full problem involving the automated analysis of configurable products, including bill-of-material, bill-processes, and relations between processes is novel.


NA


Faster development of assembly systems for products with multiple variants. The use of automated analysis imply that all related stakeholders can analyse the consequences of suggested changes, thus more reliable product systems without costly errors after deployment of new production systems.




NA


Avoid assembly problems at shop-floor, fewer scrapped products.


NA


Volvo


CTHA VOLVO


Scientific publications.


NA

BACKGROUND

#



Organization’s



%)





reached


CTHA

Knowledge of algorithms for estimation of state of operators using RGB-D cameras, and how the state can be used to display the right instructions at the right time.

90% Not Set Yet

The modelling and algorithms are published in scientific publications and are free to use.

2 Expertise VOLVO Knowledge about relevant work stations.

10% Not Set Yet

3

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





CTHA

Additional knowledge of how to implemented tracking and advanced user-interfaces.

100% 100% not set yet

2

3

4






VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X

3 Exploiting Partners with background knowledge X X



5


6



7



8



9


Secured by the CA


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research X



X



Y N









ER7: Lines balancing and optimization (including also DES agent)


D-1

Number 7

D-2

Title Lines balancing and optimization (including also DES agent)

D-3

WPs WP21 WP31

D-4


D-5


LMS Contact Person →

Nikolaos Papakostas; George Pintzos

D-6


D-7


D-8

Expected Completion date May 2015

I-1


LMS VOLV

O EDAG CRF IAM

I-2


LMS VOLV

O EDAG CRF IAM

I-3


LMS VOLV

O EDAG CRF IAM

E-1


The ALB and DES agents take as input all processes for the assembly of the product including precedence and compatibility relations, as also all different process configurations. The user only needs to select the products or variants to be assembled for the line. All other relevant information are automatically retrieved from the PPR Library, including cost and time information for all above mentioned process configurations. Then, a series of alternative process sequences are generated by the ALB agent based on the different process configurations. Finally, the ALB agent evaluates the valid process sequences against some user-defined conflicting criteria such as the desired cycle time, the number of stations and budgetary restrictions that are defined through weight factors. Based on the evaluation criteria, the best line balancing option, as also a number of alternative results are stored in the PPR library. The DES then automatically creates models for each alternative and then simulates their performance providing additional information to the engineers regarding the production rate that is estimated and so forth.

E-2

Brief description

Agents that perform assembly line balancing and assembly line simulation by automatically identifying and downloading the necessary information from the data base. This is one of the core engineering feature of the Know4Car platform. It has been implemented as a web-service.

EXPLOITATION



F-1






F-2


Research program Internally

CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other

C-1


YES NO NO YES NO NO

C-2







CHARACTERIZATION


TRL 6


All companies responsible for planning assembly systems; OEMs, System Integrators etc.


The assembly line balancing task is implemented through a software agent as a part of a cloud-based system, contributing in the reduction of time and effort required for sharing results between people that perform certain tasks in different process planning phases.


15


NA


NA


Yes


Some commercial solutions currently exist, integrated into larger software suites. As an example, the DELMIA platform includes a line balancer. However, solutions such as this are not integrated with a collaborative platform or have access to an extended database.


NA


Faster execution of collaborative projects related to assembly line design.





NA


Possibly more efficient assembly lines - less energy and resource consumption.


NA


LMS VOLVO EDAG CRF IAM


LMS VOLVO EDAG CRF IAM




NA

BACKGROUND

#



Organization’s



%)





reached


LMS Knowledge of how to develop intelligent web-based agents.

100% YES

2 Expertise VOLVO Knowledge about relevant line balancing methods.

20% Not set yet

3 Expertise EDAG

Knowledge about relevant line balancing methods.

20%

4 Expertise CRF

Knowledge about relevant line balancing methods.

20%

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





LMS Multi-criteria assembly line design under demand uncertainty.

100% 100% Not Set Yet

2

3

4

5





VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X





5


6



7



8



9


Secured by the CA

10


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research x

C Consultancy, Training, Education x


x x x x

S Selling, Distribution, Licensing x


Y N








ER8: Special AR tools for training and guidance of assembly processes


D-1

Number 8

D-2

Title AR tools for training and guidance of assembly processes

D-3

WPs WP52

D-4


D-5




D-6


D-7


D-8

Expected Completion date May 2015

I-1


LMS CRF N.BAZI

GOS S.A.

TECNALIA

IAM VOLV

O

I-2


LMS

I-3


LMS

E-1


Framework for guiding assembly workers which has 3D visualization support as well as communication support through two devices: • AR goggles • Handheld device Within the Know4Car project the knowledge framework is used to support the training of operators through the advances user interfaces and augmented reality (AR) techniques. The main objective is to reduce the overall training time of blue collar workers as well as to better communication between them a design engineers.

E-2

Brief description

Framework for guiding assembly workers which has 3D visualization support as well as communication support through two devices: • AR goggles • Handheld device

EXPLOITATION



F-1

Natures of the exploitation service (training)

service (training)

F-2


Research program internally




CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other

C-1


YES NO NO YES NO NO

C-2







CHARACTERIZATION


TRL 6


All companies performing manual assembly processes and training of workers


The main objective is to reduce the overall training time of blue collar workers as well as to better communication between them and design engineers.


15


NA


NA


Yes


NA


Develop similar approaches.


Improvement of training performance and better communication between blue collar workers and design engineers.


NA

What environmental benefits are likely to be achieved by this result e.g. improved health

NA



& safety, reduced solvents, emissions, waste carbon footprint etc.?



LMS


LMS CRF N.BAZIGOS S.A. TECNALIA IAM VOLVO




NA

BACKGROUND

#



Organization’s



%)





reached


LMS Knowledge of VR/AR tools.

100% YES

2

3

4

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





LMS Use of AR technologies for training blue collar workers


2

3

4

5






VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X X X X X




5


6



7



8



9


Secured by the CA


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research X

C Consultancy, Training, Education X X X X X X




Y N









ER9: Manufacturing Knowledge Management infrastructure including knowledge model regarding: Product, Process, Resource and relevant parameters (PPR)


D-1

Number 9

D-2

Title Manufacturing Knowledge Management infrastructure including knowledge model regarding: Product, Process, Resource and relevant parameters (PPRE)

D-3

WPs WP21 WP41

D-4

Deliverables D21.1 D21.2 D21.3 D21.4 D41.2 D41.3 D41.4

D-5




D-6


D-7


D-8

Expected Completion date August 2015

I-1


LMS VOLV

O CRF IAM EDAG

N.BAZIGOS S.A.

I-2


LMS VOLV

O

I-3


LMS VOLV

O EDAG CTHA

E-1


The manufacturing knowledge infrastructure includes different components that include both the infrastructure that supports the storage of data and their translation into semantic instances as well as agents that support the identification and management of knowledge. The infrastructure includes different applications that help users store data into a common data model and when required, it automatically translates this information into a semantic model for faster and easier identification of relevant knowledge. The similarity matching application is a mechanism leveraging the knowledge infrastructure of the Know4Car platform to identify and reuse knowledge from previous engineering projects in future situations that present similar challenges to the engineers. In its final refined version, the similarity matching mechanism was updated in order to include additional similarity matching criteria supporting the user to perform tasks on basis of data entered and decisions taken in previous projects in similar contexts. In the updated application, a user working on a certain tasks such as “calculation of cycle time”, can check the relevance of an old case based on the name of the product or product variant considering string similarity matching values. In this way the semantic queries can provide results to requests such as “show me the number of stations used for the assembly of a similar or same product variant” up to “show me the process time of an assembly process used for similar products”.

E-2

Brief description A backend and frontend infrastructure that supports the storage and identification of various information related the execution of manufacturing systems' design tasks.

EXPLOITATION

For each exploitation provide the nature and forms (use the




drop-menu to select)

F-1




F-2



CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other

C-1


YES NO NO YES NO NO

C-2







CHARACTERIZATION


TRL 5




Easier and faster identification of data and information related to process design.


15


NA


NA


NA


NA



What commercial benefits are likely to be achieved by this result e.g. Increase in sales, reduction in development / production /

Better understanding of market trends as well as new backend infrastructure developments for the development partners involved (PDTec).




logistics costs, new products, new markets etc.?


NA


NA


New approaches to the management of data in manufacturing design projects.


LMS


LMS VOLVO CRF IAM EDAG N.BAZIGOS S.A.




NA

BACKGROUND

#



Organization’s



%)





reached


LMS Semantic translation of data through specific mechanisms.

80% YES

2 Expertise VOLVO Relevant knowledge models.

10% Not set yet

3

4

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





LMS

How the algorithm currently calculates the similarity between current interests and historical information.


2 Expertise VOLVO

3 Expertise EDAG

4 Expertise CTHA

5





VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X



4 Exploiting Partners with foreground knowledge X X X


5


6



7



8



X

9


Secured by the CA

10


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research Y

C Consultancy, Training, Education Y


Y Y Y Y Y



Y N









ER10: Assembly Precedence Diagram Generation tool


D-1

Number 10

D-2

Title Assembly Precedence Diagram Generation tool

D-3

WPs WP21 WP31

D-4

Deliverables D21.5

D-5




D-6


D-7


D-8

Expected Completion date August 2015

I-1


LMS VOLV

O CRF IAM EDAG

N.BAZIGOS S.A.

I-2


LMS

I-3


LMS

E-1


The application uses controlled motion of assembly components and performs collision detection to estimate the precedence relations regarding their assembly. The latest version of the application has been improved in terms of speed as well as ease of use. The algorithm can perform faster generation of information through various techniques (e.g. symmetry). The required input from the user is the selection of the base part(s). In the end, the algorithm generates an excel sheet that contains all the information that are required for the engineer to construct the processes’ precedence.

E-2

Brief description An add-on to commercial CAD systems (CATIA) that can help generate the assembly precedence diagram for a particular product design.

EXPLOITATION



F-1

Natures of the exploitation Assembling

Service (engineering) Licencing

F-2


I don't know Start-Up

Memorandum of

Understanding




CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other

C-1


YES NO NO YES NO NO

C-2







CHARACTERIZATION


TRL 6




Faster and more accurate generation of assembly information from product designs. More specifically, detailed assembly precedence information based on geometric constraints.


15


NA


NA


No


NA




Faster and more accurate generation of assembly information from product designs. More specifically, detailed assembly precedence information based on geometric constraints.


NA

What environmental benefits are likely to be achieved by this result e.g. improved health

Possibly more efficient assembly lines - less energy and resource consumption.




& safety, reduced solvents, emissions, waste carbon footprint etc.?



LMS


LMS VOLVO CRF IAM EDAG N.BAZIGOS S.A.




NA

BACKGROUND

#



Organization’s



%)





reached


LMS Knowledge of how the algorithm works.

100% YES

2

3

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





LMS EoL information extraction regarding dismantling of products.


2

3


Know4Car FoF

FoF-ICT-2011.7.4 – 284602 Doc-Ref: D72.2 Public



VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X





5


6



7



8



9


Secured by the CA

10


Secured by the CA


Doc-Ref: D72.2

Public


11


FREE NEGOTIATION NO




In case at least one partner do not agree to transfer the rights

(VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research X



X X X X X



Y N







\ Know4Car FoF

FoF-ICT-2011.7.4 – 284602


ER11: Information Extraction Agent


D-1

Number 11

D-2

Title Information Extraction Agent

D-3

WPs WP21 WP31

D-4


D-5




D-6


D-7


D-8

Expected Completion date End of the project

I-1


LMS VOLV

O EDAG

N.BAZIGOS S.A.

I-2


LMS

I-3


LMS

E-1


The Information extraction application is an agent, set up in a server that contains a running version of Delmia. The agent is able to control Delmia automatically, receive files and open them. After the agent opens the files it reads through the standard hierarchy and extracts all relevant data. More specifically, for CATProcess files, the agent can extract (if available), the names and relations of the product components, the processes and their information related to them (including their relations between them and the components) and finally the resources (as instances). The agents temporarily stores this information and presents it to the user who can review and edit them. When prompted by the user, the agents creates the necessary classes and instances and upload all data on the Know4Car repository.

E-2

Brief description Web-application that extracts and forwards information from engineering files generated from DELMIA. Configured for assembly related information.

EXPLOITATION



F-1

Natures of the exploitation Expertise Engineering


Doc-Ref: D72.2

Public Know4Car FoF FoF-ICT-2011.7.4 – 284602

F-2



CONFIDENTIALITY


Consortium Partners

Exploiting Partners

Specific Partners

European Commission (by law)

All public Other

C-1


YES NO NO YES NO NO

C-2




R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14



R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28


CHARACTERIZATION


TRL 5


Engineering and manufacturing companies.


Faster sharing of information from files that can't be shared for various reasons.


15




Yes, but not direct, i.e. CAD converters.


Different and focused on engineering files.


Produce similar solutions.


What societal benefits are likely to be achieved by this result e.g. job creation and


Know4Car FoF

FoF-ICT-2011.7.4 – 284602

/ or existing jobs supported (state how many), local economic improvements etc.?



Faster sharing between collaborating organisations in big or small manufacturing related projects.


-


LMS VOLVO EDAG N.BAZIGOS S.A.




New business model. New research method.

BACKGROUND

#



Organization’s



%)





reached


LMS Knowledge of how engineering files are created and shared.

100% YES

2

3

4

5

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





LMS How a possible application should be formed for end users.

20% YES

2

3


Know4Car FoF




VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X X X




5


6



7



8



X

9


Secured by the CA

10


Secured by the CA




11


FREE NEGOTIATION NO




In case at least one partner do not agree to

transfer the rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research Y

C Consultancy, Training, Education Y


Y Y Y



Y N









ER12: Variability Management tool


D-1

Number 12

D-2

Title Variability Management tool

D-3

WPs WP21 WP31 WP41 WP51 WP62

D-4

Deliverables D31.5 D51.6 D62.2

D-5


CTHA Contact Person →

Knut Åkesson

D-6


D-7


D-8

Expected Completion date Nov’15

I-1


CTHA VOLV

O EDAG

I-2


CTHA VOLV

O

I-3


CTHA

E-1


The variability agent support the development of manufacturing systems that has to support a large number of different product variants. A typical example is a truck that the customer can customize in many different variants, for example, length of frame, type of engine number of axles, type of cabin etc. Typically a truck is can have about 500 different variant types and above 10000 rules that describe how the different variants may be combined together. The number of possible trucks than be ordered by a customer can be more than 10^100. All of these trucks that are allowed by the rules have to be possible to manufacture, but the number of possible variants make it hard to manually analyze the effect of variants on the manufacturing systems. The variability agent support the automated analysis of the manufacturability of product variants based on models of the product, the bill-of-material, engineering bill-of-process, manufacturing bill-of-process. It is supporting both the roles done by the OEM and the System Integrator and the use of computer algorithms to analyze the manufacturability of all possible product variants is an important step in going from a largely manual process to a process that can be automated and where every stakeholder can get instant feedback on the effects on proposed changes in either the product or on the manufacturing system.

E-2

Brief description

An agent that support the development of product and manufacturing systems that has a large number of possible variants, for a car or a truck is product that can be configured differently to satisfy the needs of individual customers.

EXPLOITATION

For each exploitation provide the nature and forms (use the





drop-menu to select)

F-1


Service (engineering) engineering

F-2


Research program internally

CONFIDENTIALITY


Consortium Partners

Exploiting Partners


All public Other

C-1


YES NO NO YES NO NO

C-2







CHARACTERIZATION


TRL 6


OEMs, System Integrators. All companies responsible for planning assembly systems.


More efficient development process of products and related manufacturing system.


15


NA


NA


Yes


The full problem involving the automated analysis of configurable products, including bill-of-material, bill-processes, and relations between processes is novel.


NA





Faster development of assembly systems for products with multiple variants. The use of automated analysis imply that all related stakeholders can analyse the consequences of suggested changes, thus more reliable product systems without costly errors after deployment of new production systems.


NA


Avoid assembly problems at shop-floor, fewer scrapped products.


Increase speed at which new or modified products can be introduced at market.


Volvo, EDAG


CTHA VOLVO EDAG




NA

BACKGROUND

#



Organization’s



%)





reached


CTHA

Knowledge of how to model and support the development of computer algorithms for the automated analysis of product variability and its effect on the manufacturing system.

80% Not Set Yet

The modelling and algorithms are published in scientific publications and are free to use.

2 Expertise VOLVO

Knowledge about interconnection between eBoM, mBoM and mBoP

20% Not Set Yet

3

FOREGROUND

#



details

Organization’s



(in %)



result (in %)



shares of FK]





CTHA

Additional knowledge of how to model and support the development of computer algorithms for the automated analysis of product variability and its effect on the manufacturing

100% 100% not set yet

2




3

4


Know4Car FoF




VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.

1 Lead partner X

2 Partners willing to exploit the result X X X




5


6



7



8



9


Secured by the CA

10


Secured by the CA




11


FREE NEGOTIATION NO





rights (VETO)

YES


VO

LVO

SAP

LMS

CR

F

KIT

TECN

ALIA

PD

TEC

IAM

CTH

A

EDA

G

N.B

AZIG

OS

S.A.


A Assembly

R Research X



X X



Y N






Page 119 of 120 Glossary

Know4Car FoF


GLOSSARY

Audit Area: The audit area is an area where the final testing is accomplished. Final testing is e.g. brake test, performance test and water leakage test. AutomationML: Automation Markup Language (AutomationML) is a neutral data format based on XML for the storage and exchange of plant engineering information, which is provided as open standard. Database: Databases store large amounts of data in a predefined form. The uniformity allows easy accessibility of stored or derived data, but limits possibilities of representing real life concepts. EC screwdrivers: Electronically commutated (EC) screwdrivers are controlled screwing devices which monitor the turning moment and the rotation angle in the assembly process. These devices are installed because of quality and documentation reasons. Engineering(verb) Process: To plan, construct, or manage a set of actions and steps in order to produce a result, following an engineering(noun) value chain. The result could be a design(noun) of a robotic cell or an assembly line. Functional Requirement (Requirement): A statement of a need or objective, or of a condition or capability that a product must possess to satisfy such a need or objective. ice.NET: ice.NET is a software platform on which information systems, data warehouses, portal solutions and "collaboration spaces" can be implemented efficiently and effectively. IS Testers: IS testers are electronic testers which program electronic control units (ECUs) and test all installed electronic components and systems in the car. Knowledge Management: (KM) comprises a range of practices used by organizations to identify, create, represent, and distribute knowledge. Line Balancing: Line Balancing is a method for an optimal and evenly spread workload in each station of the final assembly. Manipulators: A Manipulator is an arm-like mechanism for material handling. It supports the worker for e.g. in lifting and handling heavy parts. Material Provision: The supplier for material provision supplies carriers for material handling. Carriers are defined as boxes where material is stored. Non-functional Requirement: A requirement that specifies criteria that can be used to judge the operation of a system, rather than specific behaviors. Ontology: Ontology formally represents knowledge as a set of concepts within a domain, and the relationships between those concepts. More theoretically expressed an ontology is a formal, explicit specification of a shared conceptualization. OWL: The Web Ontology Language (OWL) is a specification by the World Wide Web Consortium (W3C) for the creation, publication and distribution of ontologies based on formal description logic.

Glossary Page 120 of 120



Platform feature (feature): A feature is a logical unit of behavior that is specified by a set of functional and quality requirements. A feature generally captures a considerable set of requirements and is, as such, used to group requirements, which simplifies requirements handling. Process planning: In manufacturing the practice of process planning provides precise and clear sequential directions about how the product is to be routed and fabricated in a manufacturing facility. Query: Queries are statements that retrieve a portion of data from an information system. Both the query and the result have a predefined and unambiguous format, and thus act as an interface to an information system. Semantic Technology: denotes a set of technologies that aim to encode meanings separately from data and content files, and separately from application code. Semantic technologies provide an abstraction layer above existing IT technologies. Specification: A specification is an explicit set of requirements to be satisfied by a service. STEP: The Standard for the Exchange of Product Model Data (STEP), is a comprehensive ISO standard (ISO 10303) that describes how to represent and exchange digital product information. Team Rooms: Team rooms are defined as conference rooms or offices. Therefore the supplier for team rooms furnishes these rooms. XML: Extensible Markup Language (XML) is a mark-up language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable.