Virtual Prototypes: what’s next? - Unibg · 2018-05-20 · Virtual Prototypes: what’s next? Umberto Cugini Fondazione Politecnico di Milano ... Open Innovation Optimization PDM

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EngineeringManufacturing

and Related

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Virtual Prototypes: what’s next?

Umberto Cugini

Fondazione Politecnico di Milano

Centro di Competenza per l’Innovazione Sistematica

[email protected]://www.kaemart.it

Corso Virtual PrototypingBergamo, 24 aprile e 8 maggio 2018

KAEMaRT © Umberto Cugini

2Outline

• The current scenario: Everything is changing

• The evolution of the target of design

• The evolution of Methods and Tools

• The future perspectives

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Keywords, hot words or buzzwords ?

3D Printing

4th Industrial Revolution

Additive Manufacturing

AGILE

AR and VR

CAD

CIM

Circular Economy

Cloud

Common Research

Complexity

Connectivity

Continuous

Change

Cooperation

Cyber-Physical Systems

Digital Enterprise

Digital Manufacturing

Eco Design

Exponential Evolution

Federation

Functional Modeling

Globalization

Horizon 2020

Human resources

Hybrid Manufacturing

Incubators

Industry 4.0

Innovation Rate

Internal Knowledge exploitation

IoE

IoT

M&A

Mobility

Multi-

Open Innovation

Optimization

PDM

Platform-based SW

PLM

Regional programs

Shared Knowledge

Simulation Based Design

Singularity

Smart Factory

Smart Manufacturing

Start Up

System > Product > Service

TRIZ

User Centered Design

UX Design

Virtual Prototyping

Virtualization

…......

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4th Industrial Revolution 4

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4th Industrial Revolution and Industry 4.0 5


4th Industrial Revolution and Industry 4.0 6

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Smart manufacturing 7


G.E. speech 8

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G.E. speech 9


The reference scenario at large 10

Global Context : Population Growth Urbanization Globalization Customization Business models change

Specific Context : Exponential growth ( Moore’s law ) Virtualization Connectivity Mobility IoE Multi-domain simulation Additive Manufacturing Singularity …

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Population of the Earth 11

http://population.io


UN - World Urbanization Prospects ( 2014 Revision ) 12

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Today..

An awful lot, mobile, connected, social

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14

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TodayCommunication …

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Top 10 skills 16

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Improve

Security

Improve Energy

Production

Improve the

Environment

Improve

Health Care

Improve Learning

and Discovery

NAE Grand Challenges 2020

1. Make solar energy economical

2. Provide energy from fusion

3. Develop carbon sequestration methods

4. Manage the nitrogen cycle

5. Provide access to clean water

6. Restore and improve urban infrastructure

7. Advance health informatics

8. Engineer better medicines

9. Reverse-engineer the brain

10. Prevent nuclear terror

11. Secure cyberspace

12. Enhance virtual reality

13. Advance personalized learning

14. Engineer the tools of scientific discovery

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National Academy of Engineering : Grand Challenges of Engineering 2011


Deep Shift: Technology tipping points and Societal Impact ( WEF 2015 )

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Top 10 Strategic Trends ( Gardner 2018) 19


Technology evolution

Time/Resource

Functionality

3° generation

2° generation

1° generation

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Innovation: Rogers’s Market Segments 21

Ref. E.Rogers “Diffusion of Innovation”


From Hype ……

….to shark fin

… but Business Model are changing … 22

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The mythical “Moore’s Law” 23


Ray Kurzweil

“The Law of Accelerating Returns”, 2001http://www.kuzweilai.net/the-law-of-accelerating-returns

“The Singularity is near”, Viking 2005

“How to create a mind”, Viking 2012

2014 Head of Engineering @ GOOGLE

Kurzweil Accelerating Intelligence

http://www.kurzweilai.net

Singularity University

http://singularityu.org

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13


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http://www.kuzweilai.net/the-law-of-accelerating-returns


Exponential evolution in Biology 26

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Market Cap 27


How evolution progress 28

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How we make forecasts ( linear ) 29

Our experience is linear, so…


The A.I. Revolution 30

ANI Artificial Narrow Intelligence

AGI Artificial General Intelligence

ASI Artificial SuperIntelligence

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Where we are 31

Today we are here, and so ..,?


We must decide … 32

…. rather quickly ... I presume

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What are the real problems ?

• Acceleration of the change pace

• Competence life:

• From > of the professional life …

… to < and more and more<< of the professional life …

• From generations …

… 1.0, 2.0, 3.0, 4.0 …

... to a continuous &/or a disruption

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An example: the Automotive Industry 34

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Once upon a time…… 35


The Ford T ( 1905 ) 36

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Today cars are systems of systems 37


Today cars are systems of systems 38

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The TABBY ( 2013 ) 39


The Strati ( sept. 2014 ) 40

“The Strati” the World’s First 3D Printed Car built by Local Motors in 44 hours

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…up to Olli & IBM Watson ( june 2016 ) 41

• The electric vehicle can carry up to 12 people and promises to offer a much-needed safe and clean transportation.

• Olli is the first vehicle to utilise the cloud-based cognitive computing capability of IBM.

• Local Motors has partnered with IBM’s Watson platform to launch its self-driving electric buses.

• These on-demand buses are now running on the roads of Washington DC, providing a natural and interactive experience to the passengers using Watson’s APIs.

• Later this year, Olli is supposed to rule the roads of Vegas and Miami-Dade county.


The Automotive Industry 42

The CHANGE

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The importance of the Automotive Industry 43


Evolution from wagon to mobility 44

6 Millennia

1 Century

5 Years

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Who will drive the vehicle ? …. IBM 45


How the business model could be disrupted 46

Servizio Disponibilità Possesso

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Let’s go back to our context …

• The product development process

• The methods and tools to support all that

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Product Development Process - PDP

PDP Scenario

DesignersMarketing people

Customers

Average customer

Define

Examine &

Analyse

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PDP Scenario

DesignersMarketing people

Define Interpret

Average customer

Needs and Desires

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PDP Scenario

Designers

Marketing people

ValidateGenerate

Average customer

Tested with

EngineersSpecsProduct

concept

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Product Development Process – PDP

PDP Scenario

Engineers

Average customer

for

Product

With variants

DesignersFinal

solution

Choose & Refine

Marketing people Approve

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Considerations about the PDP

Customers’ needs and desires

Average needs and desires of an average

customer

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The evolution of the design domain ( 1 )

The target ( seen from the designer’s pov )

• Machine

The main design function

• Seizing

The reference method

• Structural design

The result ( seen from the user’s pov )

• Doesn’t break

The main actor

• Engineer

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The traditional approach, currently used

Validation

Design >> PMU >> Testing (of target performances)

Use

Issues : High cost & long time Uniqueness No flexibility

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Requests

for

changes

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The CAD-based current approach

Validation (based on nominal geometry)

Design >> CAD >> DMU >> Testing ( via Simulation )

Use ( via digital manikins )

Issues : No flexibility for quick changes Use

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Requests

for

changes


Machine, System or what .. ?

What is this ?

A mobile phone? A camera? A computer ? A navigator? A games console ? ….?

To which “need” is it answering ?

Functions integration ? Socialization ? Communication & connectivity ? ….?

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The target ( seen from the designer’s pov )

• Machine > System > Product

The main design function• Seizing > Architecture > Problem solving

The reference method• Structural design > System design > Systematic innovation

The result ( seen from the user’s pov )

• Doesn’t break > works well > it’s new

The main actor• Engineer > System engineer > Industrial Designer

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Initial statement

the PRODUCT

… today means a successful PRODUCT :

Innovative

Customized

Easy to use

Cool

Emotional

Success means OPTIMIZE the solution

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The keywords in Virtual Prototyping

• Simulation

• Interaction

• Optimization

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Simulation

When• After design (validation)• Before design (generative/suggesting )

How• Mono-physics. • Multi-physics

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Mono-physics Simulation (courtesy of Ferrari)

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Validation of simulation (courtesy of Ferrari)

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Interaction

• When verifying and validating a concept, one key point is the interaction with the future product ( its use )

• This is fundamental for consumer products …...…. but more and more products are becoming as consumer products

• Interaction is always multisensory• Interaction is always an experience• Experiences are always emotional

….. So all perceptual and cognitive aspects related to interaction and experience become important

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iVP ( interactive Virtual Prototype )

Looking specifically to consumer products we propose a new category of Virtual Prototype :

iVP = interactive Virtual Prototype :• To be used• Living in a context that can be changed• Highly interactive implying to have a human in the loop• Centered on simulating the interaction performance• Highly parametric and flexible in real-time• Multimodal and multisensory

iVP can be used both for:• capturing the best perceived characteristics in a

quantitative way specific for each sensory aspect• verifying and validating target design specs with final users

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iVP: a new design process 65

New proposed Design Flow

FMUFunctionalMock Up

Multi-domainFunctional

Model

Multi-physicsFunctionalSimulation

Parametric Visual

Functional Model

Parametric Sound

Functional Model

Parametric Haptic

Functional Model

Interactive Virtual Prototype

Mapping

USER

Multimodal Environment

VisualizationDevice

AuditoryDevice

HapticDevice

ACTION

PERCEPTION

PERCEPTION

PERCEPTION

CHANGE PARAMETERS VARIANTS

FMU > iVP > CAD > VP (for final validation)


Functional Modeling

• Traditional process : • Design > CAD > DMU > VP (for functional validation)

• New proposed process• Concept > FMU > iVP (use validation) > CAD > VP (final

validation)

The key point > FMU = Functional Mock Up

• Functional Modeling : • “Modelica® is a non-proprietary, object-oriented, equation based

language to conveniently model complex physical systems containing, e.g., mechanical, electrical, electronic, hydraulic, thermal, control, electric power or process-oriented subcomponents.” (since 1997)

• https://www.modelica.org/

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An example: hinge and door ( 1 )

Smove

Gas piston

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User inputRotational limits

Gas piston

Smove

Hinge

Door

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An example : car

Velocità: V = 18 m/s superficie ad alta aderenza

Trajectory ESP ON

Velocità di imbardata

ESP ON

ESP OFF

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An example : comparison of two set ups 71


Real Products and Virtual Prototypes

Virtual Prototypes >> simulation driven

What is simulated?• Shape? Appearance? Behavior?

• For which human senses ?

• How perceived, tested, used?

Why? • To predict?

• To compare?

• To optimize?

• To verify ?

• To evaluate ?

• To experience ?

Which target/goal?• Quantitative or qualitative?

• Single, multiple or global?

Real Products >> Context and Users

Products not machines or systems, implying not only HW and SW but also : support, service, image, experience …

Consumers context ( B2C ) characterized by many alternatives, so…

… choice based on :• Perceived value :

– Pleasantness

– Prestige

– Usability

The golden rule : “Design for value”

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Optimization

… of the current solution

…………. or of the PROBLEM ?

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Topology Optimization

What changes is the method and the design process

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solidThinking INSPIRE 75


Topological Optimization

Paradigm shift :

Explore the solution’s space acting on constraints and boundary conditions

Understand relations and sensitivity among goals, constraints and shapes

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The actual disruptions

Additive Manufacturing

Cooperation

Open Source Hardware

Crowd funding

Cognitive computing

the technology

the approach

the process

the business model

the “smartness”

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AM Additive Manufacturing

La storia ( dal 1984 )

RP Rapid Prototyping

3D Printing

Le tecnologie per AD :

SLS ( Selective Laser Sintering )

SLM ( Selective Laser Melting )

DMLS ( Direct Metal Laser Sintering )

EBM ( Electron Beam Melting )

LENS ( Laser Engineered Net Shaping )

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Sciaky 87


Sciaky 88

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DMG Mori 89


DMG Mori 90

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DMG Mori 91


DMG Mori 92

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AM technology can be bought ..

Sciaky

http://www.sciaky.com/additive_manufacturing.html

DMG Mori

https://www.youtube.com/watch?v=L3CkzQQFZXs

……

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…. to make things unthinkable up to now 95


Topology Optimization

Strenghts Input dal progettista limitato

Possibilità di ottenere progetti radicalmente nuovi

Un modo sistematico per affrontare problemi complessi di progettazione

Challenges Difficoltà di fabbricazione di

geometrie ottimizzate complesse

Necessario un post-processing

Interfacce con altri CAD tools poco sviluppate

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Sinergie tra T.O. e A.M.

• Generano progetti che sfruttano al meglio il potenziale di A.M.

• Permettono la creazione di parti ottimizzate su misura

• Riducono le iterazioni di progetto e si riduce il TTM

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AM : how can impact on design methods?

it is possible to make “traditional” parts in a different way:

• The manufacturing process changes but, in principle, not the design process..

• You can have much more freedom for what concerns shapes ( “Complexity comes free of charge” )

• …and different physical characteristics an so sizing and verification criteria

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AM : how can impact on design methods?

it is possible to make and so to think about “non traditional”parts because:

Basic fundamental constraints disappear:

• Material omogeneity

• Morphology limited ( for milling or deforming )

This second point is definitely disruptive

…….. If we refer to the current practice.

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The disruption on design method and tools

Impacts on shape, and on local physical characteristics

…… and so new tools ?

No ! …. they already exist

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Density = 1

Density = 0


These methods exist but are not much used

• Multimodal and Multisensory Interfaces• Augmented Reality• Topology Optimization• FMU and Modelica

Why are not used ?

Not known ? Mental inertia ? Specific role in the Company ? What else ??

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100

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… but the evolution is not obvious ! 101


Tornando all’ Additive Manufacturing …

Quale impatto sulla progettazione ?

Sulle fasi a monte del manufacturing :• L’ideazione

• La progettazione

• La simulazione

Comunque cambia il paradigma e quindi la gerarchia:

Non si progetta quello che si può costruire…

…. ma si può costruire quello che serve, grazie alla

nuova tecnologia di manufacturing

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Esempi da fornitori ( 2 ) 103



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Optisys LLC example

Optimizing the Design for 3D printing let the company :

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from “GE Reports” Jan. 2, 2018


Una riflessione a livello nazionale

L ‘ Additive Manufacturing non è una novità…

1984 primi brevetti sui metodi additivi ( Rapid Prototyping )

1994 SPI Sistemi di Produzione Innovativi• 11 progetti finanziati al 100% per 125 mil.di di Lire

2005 1st Int Conference on Additive Manufacturing, Nottingham

2007 AM Platform

2007-2013 7FP 60 progetti finanziati con 160 m€

Più recentemente ……

2010 Industrie 4.0 Concept R. Berger ( Germania )

2011 Industrie 4.0 piano pubblico ( Hannover Messe )

2012 feb. National Strategic Plan for Advanced Manufacturing ( USA )

2013 jan. NNMI National Network for Manufacturing Innovation ( USA )

2014 prime macchine ibride sul mercato ( DMG Mori, Sciaky … )

2015 AITA ( Ucimu )

2015 EMO …..diverse macchine presenti ( DMG Mori, MAZDA, .... )

2017 Industria 4.0

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Evoluzione del processo NPD

Da function centric ( Push ) a user/customer centric ( Pull )

Function centric

Il processo è pilotato da innovazione incrementale ( che non è disruptive e non crea necessariamente nuovo mercato )

User/Customer centric

Cambio di paradigma:

Da progettare la soluzione e poi validarla …

…. a validare la soluzione e poi progettarla

Cambia la tecnologia di supporto :

Progettazione >> CAD + CAM / AM

Simulazione contestuale e d’uso >> FMU + iVP + Multiphysics simulation

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… e i tools di sviluppo prodotto ?

Da…

specifica di come deve essere fatto ( CAD )

a…

come deve essere fatto e/o comportarsi (CAD + Simul.= VP)

a…

come può essere usato, come ci si può interagire e come si comporta non solo funzionalmente ma anche fisicamente (iVP)

a…

Come potrebbe cambiare e comportarsi per modifiche e/o variazioni ( Digital Twin )

Quindi enfasi sul contesto in cui si inserisce quello che si vuole progettare

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The target ( seen from the designer’s pov )• Machine > System > Product > Service

The main design function• Seizing > Architecture > Problem solving > Problem setting

The reference method• Structural design > System design > Systematic innovation >

Emotional Design & Engineering

The result ( seen from the user’s pov )• Doesn’t break > works well > it’s new > I like it

The main actor• Engineer > System engineer > Industrial Designer > D&E

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..so What’s next ?

Everything is changing at increasing pace…

The market and the customer …… from “must have” to access and/or availability

The target …… from machine to access/availability

The Methods …… from function design to experience design

The Tools …… from virtual prototypes to digital twin

The future perspectives :•Knowledge exploitation using A.I.•Skill development using A.I.•….

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Documents

Virtual Prototypes: what’s next? - Unibg · 2018-05-20 · Virtual Prototypes: what’s next? Umberto Cugini Fondazione Politecnico di Milano ... Open Innovation Optimization PDM