CREMA, together with C2NET, has successfully organised and

executed the 1st CREMA/C2NET Industrial Workshop in Spain.

To keep pace with the needs of the manufacturing industry of the future, companies

need to flexibly react to changing demands and be able to manage production

capacities in a rapid and efficient way requiring agile collaboration among supply

chain partners. Innovative solutions to allow industrial companies to incorporate faster

and more efficient decision making looking for a better use of manufacturing assets

are demanded.

A total of 80 people coming from different manufacturing industries from the

Basque Region and surroundings joined the first CREMA/C2NET Industrial

Workshop in Spain. The Basque Country is one of the main industrialised regions of

Spain and therefore the speeches given by CREMA, and C2NET, were addressed

directly to the potential users of CREMA fulfilling one of the main objectives of the

project. A stunning and futuristic place, the Orona Foundation Auditorium, was

selected for this purpose. Orona is one of the biggest Spanish manufacturers of lifts,

escalators and other products such as moving walks. Both projects used their R&D

facilities to have a joint session for exchange of information, impressions and

research topics.

Topics and discussions of the Industrial workshop, with recognised speakers

coming from the Basque Government and the EU Industry, were very well received

and provoked the audience to think about the outcomes of the two projects and

potential benefits to invest in latest ICT solutions coming from R&D projects.

Please take a minute to visit www.crema-project.eu for more information about us

and our goals, contact us at hello@crema-project.eu or watch our video in YouTube!

Cloud-based Rapid Elastic MAnufacturing

Edition 2—2016

Welcome

Since starting this innovative H2020

project in January 2015, we aimed at

CREMA standing out as the project with

the biggest impact and the best exploita-

tion in all the projects we have wit-

nessed before. Participating in other

Factories of the Future FP7-projects

before, we knew the potential pitfalls,

challenges and hidden levers to press to

make CREMA more successful.

The first year of CREMA was exclu-

sively about defining use-cases, talking

to industry partners, visiting their facto-

ries, trying to understand the actual real-

world problems. Also, streamlining what

had been written in the proposal into a

more effective plan to have a tangible

impact on our industry culminated in

shifting the dissemination efforts towards

this business plan in 2016, in parallel to

starting the implementation phase.

With this newsletter, the end of the

project Y2 is approaching. We’ve set

high expectations, and we’re pushing

hard to keep them. It was, and still is, a

tour de force. The project partners are

fully dedicated and try to achieve more

than was expected from the start, they

work pragmatically to achieve the mile-

stones, they combine forces of multiple

tasks for putting a stronger focus on

exploitation, and they’ve had much more

physical meetings to factories than in

any project so far.

We’re looking forward to the 2nd EC

review, to be able to continue the fruitful

work and provide a competitive product

for improving information and collabora-

tion in factories. In a nutshell, to realise

tomorrows vision today.

Tim Dellas, CREMA Coordinator

CREMA Newsletter

CREMA/C2NET Collaboration Team

Implementation of the Predictive Maintenance Use Case demonstrator is performed with a Fagor mechanical press machine that contains a Goizper Clutch Brake component

The demonstrator is located in Fagor Arrasate facilities in the

Basque country and it is based on a real mechanical press ma-

chine. This Use Case is focused on the clutch brake failure

modes and downtimes of the press machine caused by this

critical component.

In order to capture

clutch brake’s data to

enable its diagnosis,

several sensors have

been installed on the

machine during the

last year in CREMA

project. Most of the

sensors have been

installed within the

clutch brake, but

some others have

been installed in

specific points which

provide interesting

data for performing

the clutch brake’s

diagnosis.

Temperature sen-

sors, pressure trans-

ducers, encoder,

inductive sensors,

opto coupler and a

flow meter give the

actual health data of

the clutch brake. This

data is sent to a data

logger which has

been installed and

programmed during

the year in order to

receive information

from these sensors

and from the ma-

chine PLC. This data

logger generates a

data file per machine stroke ready to transfer the file to CREMA

platform for further data processing.

During the next year, the validation of the diagnostics and

process data must be performed. In fact, real machine failure

modes will be simulated in the press machine, and the result of

the diagnosis will be evaluated. Some of the failure modes will

be simulated by software while some others will be forced in the

press machine demonstrator in Fagor Arrasate. Apart from this,

alarm detection and prediction will be elaborated while the press

is monitored from Fagor and Goizper offices. Fagor Arrasate

and Goizper are willing to get proper results during the valida-

tion in 2017.

Implementation of the Automotive Use Case demonstrator is well underway with a live robot cell and real-time asset location tracking throughout the test zone reflecting the scenario to be applied to the Tenneco Belgium shop floor

Progress on implementing the Tenneco Automotive Use Case

has been quick off the blocks with the Industrial hardware imple-

mentation, at the Waterton Technology Centre, having been

completed within the first two months. This sees a fully enclosed

ABB Robotics cell installed

and commissioned, along

with zones for testing of

products and shipping pro-

ducts. In addition a Siemens

S7 PLC controller has been

used along with Fortis

4DIAC units to collect dis-

crete and analogue sensor

data from the robot produc-

tion and testing processes.

In the months following,

an Industreweb 4.0 Micro

Server has been installed

running Industreweb Global

and Collect that will interfa-

ce with all shop floor data

sources through a range of

protocols. Currently, the

service interfaces provided

by Industreweb will be con-

sumed by the CREMA pro-

cess runtime in order to test

the orchestration of the

production process. In addi-

tion, focus is being placed

on the optimisation features

of CREMA, and how selec-

tion of the most appropriate

production assets to meet

customer demand and qua-

lity targets. The Industreweb

4.0 Display will also be used

to pull appropriate data and

alerts from the CREMA

Cloud Storage, Big Data

Analytics and Monitoring

components to keep Operators aware of the status of production

and any errors or issues. In October the Smart Factory platform

from project partner Ubisense was installed and commissioned

in the Automotive pilot laboratory. This now tracks products and

tooling assets to an accuracy of 10cm and allows both error

proofing, and asset finding functionality to be carried out in real-

time.

The next 6 months will see the final integration with the CRE-

MA platform and the start of system testing for the final valida-

tion - both Tenneco Belgium and Technical Partner Control 2K

[TANet] have high hopes for the exploitable outcomes.

1 Industreweb: http://www.industreweb.co.uk

Hernani

Saarbrücken

Automotive use case powered by

Machinery Maintenance use case powered by

CREMA in Action: the Industry side

Vienna

Brussels

Manufacturing Ontology CDM-Core in OWL2 To enable semantic interoperation and optimisation of service-based processes, CREMA

developed the largest publicly available manufacturing domain ontology CDM-Core in the

standard formal ontology language OWL2. CDM-Core covers the CREMA use case do-

mains of metal press maintenance and automotive exhaust production, and leverages

many relevant standard vocabularies and ontologies. The practical applicability and quali-

ty of CDM-Core according to common criteria of verification and validation were success-

fully evaluated and approved by the user partners.

Optimisation of Service-Based Processes For the optimisation of service-based manufacturing processes at design time, CREMA

developed an innovative solution called ODERU that integrates pattern-based semantic

process service composition planning with QoS-based constraint optimisation problem

solving. This will be applied to both CREMA use cases in support of an optimal organisa-

tion of machinery maintenance and OEE maximisation for exhaust production processes.

Scientific Research in CREMA

Elastic manufacturing process landscapes have been introduced, together with a re-

search agenda on methodologies, instrumentation and toolsets for Cloud manufacturing.

From a technical point of view, research on elastic stream processing and the Internet of

Things (IoT) has been performed, along with the VISP (Vienna Platform for Stream Pro-

cessing) ecosystem for stream processing, which can be used to process distributed data

streams in a cost-efficient way. Further work conducted covered the usage of (private

and public) cloud resources to be able to realise the large-scale Cloud manufacturing

landscapes supported by CREMA. Apart from computational resources, also Cloud-

based storage solutions have been developed in CREMA, which allow avoiding the ven-

dor lock-in when storing data in the public Cloud.

Want to know more? Visit the CREMA Wiki website.

The Academic side

Technology of the Year

Business Activity Monitoring solutions aiming business process monitoring

BAM systems are useful monitoring tools but it is important to know what it is really worth to monitor. The combination between simple business rules and complex business rules could be a perfect approach for almost any enterprise.

Business process monitoring is one of the best ways to increase flexibility and respond more rapidly to changing markets. The

actual market forces enterprises to track these changes in real-time so that they can react to the real needs. Various

monitoring tools known as Business intelligence can be used to facilitate these purposes. However, regular dashboard like

applications that tend to provide real-time charts are not useful enough to improve all business aspects, as they do not actually

report the current state of business processes. For that aim, more specific monitoring tools are needed and this is where

business activity monitoring comes.

Business activity monitoring, also known as BAM is a tool with the aim of monitoring business activities, such as operations,

processes and transactions to take better business decisions. A current BAM solution provides KPIs based dashboard that

helps evaluating the current status of the processes. The main goal of BAM solutions is to monitor real-time business metrics

and detect events, filter them and trigger business process management solutions. The main difference between BAM and BI

solutions is that BAM solutions are developed for reporting rather than analysing information while Business intelligence is

used in future predictions.

As the main objective of the BAM systems is to report the actual status of the business, various criteria need to be set in order

to evaluate them. In many cases the criteria selected to evaluate the current situation are the well-known business rules. A

business rule defines or constraints some aspects of business and resolves to either true or false. These kinds of rules

evaluate the precise moment where a condition is reached and in many cases the use of these kind of rules are more than

enough to evaluate the process’ status.

However, when various given conditions need to be taken into account, the simple business rules are not enough. In many

situations, organisations need to control the previous values of a given business rule instead of evaluating just a single KPI

value. In the same way, a time slot could be considered for those rules as an alarm is just triggered when a precise condition

has been met during a batch time. When we talk about this kind of rules, we are talking about complex rules.

Technically speaking the difference between the simple business rules and complex business rules is that the simple business

rules are recommended for stateless processing, where there is not pre-processing, while complex business rules are used

when there is a correlation between the events over a time slot.

Want to know more? Visit the CREMA Wiki website and follow this link.

Partners

Factsheet Program: H2020 Budget: €5.3M Start: January 2015 End: December 2017

Cloud-based Rapid Elastic MAnufacturing Copyright © CREMA Project Consortium. All Rights Reserved

Grant Agreement No.: 637066

The next year the CREMA team will be focused on the following activities:

What will be done next year?

Concept, Requirements and Specification

Business Innovation Model

Market Watch and State-of-the-Art review

Architecture, Functional Specs, Security &

Privacy, Integration

Security and privacy concerns will be made available

Software integration

Manufacturing, Virtualisation & Interoperability

Harmonisation: Transformation services will be available in the

Marketplace for their usage in the Process Designer

Cloud Storage: Implementation of privacy awareness and multi-instance-

service

CPS Sensors: Integration with Marketplace; creation of more CPS services

Services Abstraction: Refinement of abstraction templating system

Cloud Manufacturing Process and Optimisation

Process Designer: Design of complex Manufacturing processes will be

possible

Process Engine: Several independent running Process Engines will

enhance the scalability of the process execution functionality

(Re-)Leasing: A sophisticated resource optimisation will be provided

Optimisation: Integrated functional and QoS-driven optimisation of service-

based business process models at runtime

Cloud Manufacturing Collaboration,

Knowledge and Stakeholder Interaction

Marketplace: CPS-Scheduling and Booking will be available accompanied

by the connection to payment processors

Monitoring: The monitoring and alerting component will be integrated with

the rest components of CREMA for predictive maintenance Big Data: Predictive analysis functionality will be added

Collaboration: Smart Glasses implementation and integration

Dashboard: Ticketing system incl. FAQ style system for CPS,

implementing Security and Privacy system

Use Case I: Machinery Maintenance

CREMA solution validated within the Machinery Maintenance use case

Feedback to developers

Use Case II: Automotive

CREMA solution validated within the Automotive use case

Feedback to developers

Impact

CREMA Business Plan

Plan and organise second CREMA Workshop

On-going collaboration with other projects, especially C2NET

CREMA Crossword

Across Down

1. CREMA Monitoring and Alerting

1. CREMA Data Model, Model Library and Pro-files

6. CREMA Cloud Process and Messaging Runtime Environment

4. CREMA Cloud Collaborative Process

2. CREMA Service Virtualisation and

7. CREMA Dashboard and Visualisation

9. CREMA Marketplace and Monetisation

3. CREMA Cyber-Physical Systems, Sensor Abstraction and Virtualisation

8. CREMA Design and Runtime Optimisation

10. CREMA Manufacturing Big Data,

5. CREMA On-Demand Service Leasing and

11. CREMA Agile Personal Collaboration Environment