How TRIZ can contribute to a paradigm change in R&D practices? - - PowerPoint PPT Presentation

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How TRIZ can contribute to a paradigm change in R&D practices? - - PowerPoint PPT Presentation

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Keynote : Japan TRIZ Symposium Keynote : Japan TRIZ Symposium September 8 th 2012 Tokyo Japan September 8 th 2012 Tokyo Japan Denis Cavallucci, Professor at INSA Strasbourg France Denis Cavallucci, Professor at INSA

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SLIDE 1

Keynote : Japan TRIZ Symposium

September 8th 2012 – Tokyo – Japan Denis Cavallucci, Professor at INSA Strasbourg – France

Keynote : Japan TRIZ Symposium

September 8th 2012 – Tokyo – Japan Denis Cavallucci, Professor at INSA Strasbourg – France

1995 1997 2000 2005 2009 2012

Advanced Master in Industrial engineering PhD in Mechanical engineering Full Professor at INSA Strasbourg Associate Professor at INSA Strasbourg

PhD Thesis : How TRIZ can cooperate with 8

  • ther Engineering Design methodologies

Full Professorship : Inventive Design as a new paradigm change in Engineering Design Master degree : TRIZ, a state of the art

How TRIZ can contribute to a paradigm change in R&D practices?

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SLIDE 2

Outlines

  • f the

Keynote

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SLIDE 3
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

3

Short introduction Our Industrial world is in permanent change, which major challenges await R&D departments in future ? Summary of TRIZ milestones Short overview of a real industrial case study The TRIZ Consortium : 3 worldwide large companies unify their efforts 5 major drawbacks of TRIZ Teaching IDM Some ongoing research Conclusions/Questions Why do we need a “new” software ? From IDM major stages to STEPS software Major STEPS software interface

  • 3. STEPS

20min 20min 10min 10min 15min 15min 5min 5min 10min + 20min Q&A 10min + 20min Q&A

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SLIDE 4

Short introduction

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SLIDE 5
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

5

My past and current “TRIZ” responsibilities

  • 3. STEPS

1998 2000 2004 2006 2008 2018 2012

TRIZ‐France

Founder & president of TRIZ-France association

ETRIA

Founder & past-president of European TRIz Association ETRIA

WG5.4 of IFIP

Founder & Publication Officer of IFIP’s WG 5.4 on CAI

TRIZ Consortium

Founder & current leader of TRIZ Consortium

DEFI project

Scientific director of DEFI project (European funds)

Project InnovENT‐E

Member of the board of directors of the foundation InnovENT-E (Ministery of Industry funds for SME’s)

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SLIDE 6

1946 1976 1985 2012 Origins : Altshuller’s TRIZ

Fundamentals of TRIZ :

  • Notions of contradiction
  • Notions of laws
  • Methods, tools, techniques
  • Meta‐knowledge bases

OTSM : the first attempts to axiomatize

and extend TRIZ

Extensions of TRIZ towards multidisciplinary problematic :

  • Notion of problems
  • Notion of partial solutions
  • Notion of network (PB, CT)
  • Towards an axiomatization of TRIZ

IDM : The first fruits of research and

industrial partnership in Developing TRIZ

Formalization of TRIZ & OTSM for industry

  • Ontology construction,

disambiguation of concepts;

  • Computerization (STEPS)
  • Notion of graphs
  • Notions of TRIZ body of knowledge

completeness

  • Feedback CSPB graph

1998

1995 TRIZ @ INSA

Other researches Researches on TRIZ Researches on OTSM

2007

Researches on IDM

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

6

TRIZ at INSA Strasbourg : from history to now

  • 3. STEPS
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SLIDE 7

What is

the current context in which we intend to contribute

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SLIDE 8
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

8

Our Industrial world is in permanent change, which major challenges await R&D departments in future ?

  • 3. STEPS

1930 1970 1990

  • Answering to demand
  • Organize workshops
  • Improve productivity rates
  • Be competitive
  • Ensure quality
  • Optimize organization
  • Organize innovation
  • Manage knowledge increasing quantity
  • Anticipate product/system’s evolutions

Productivity Quality Innovation

Sum of worries

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SLIDE 9

Time Heresy Theories Methods, tools

(tests & theoretical elaborations)

Methods, tools

(tests & industrial evaluations)

Methods, tools

(mass application)

Norm Law Time for theories Time for methods Time for measurements

Doubt

Confidence

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

9

Our Industrial world is in permanent change, which major challenges await R&D departments in future ?

  • 3. STEPS
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SLIDE 10

Time

Before-hand signs of losses Significant losses End of existing solution’s capacity to solve problems Readiness to observe new « ways » of doing things Readiness to perform some tests Adoption Job creation, services, positions Total control

Time for consciousness Time for trial & errors Time for decisions

Serenity Stress

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

10

Our Industrial world is in permanent change, which major challenges await R&D departments in future ?

  • 3. STEPS
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SLIDE 11

Before‐hand signs of losses Significant losses End of existing solution’s capacity to solve problems Readiness to observe new « ways » of doing things Readiness to perform some tests Adoption Job creation, services, positions Total control

Heresy Theories Methods, tools

(tests & theoretical elaborations)

Methods, tools

(tests & industrial evaluations)

Methods, tools

(mass application)

Norm Law Innovation Quality How to act in anticipation of a more than probable future norm on Innovation ?

How to create a new way

  • f designing inventively

sufficiently robust to be adopted by enterprises ? How to create tools that will enable mass application

  • f new

inventive practices?

Q: 1985 I : 2017

(CEN/TC 389 or ISO?)

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

11

Our Industrial world is in permanent change, which major challenges await R&D departments in future ?

  • 3. STEPS
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SLIDE 12

TRIZ postulates:

A short reminder about fundamentals

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SLIDE 13
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

13

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

First observations (1956):

  • Inventors react according to similar mechanisms when they

invent;

  • These mechanisms are independent of their domain of

expertise;

  • Technical systems are developing in accordance with recurrent

trends;

  • Every step of these developments resulted in the resolution of
  • ne or several contradictions.

First hypothesis:

  • It is possible to define the laws that govern the evolution of

technical systems (help the inventor to anticipate);

  • It is possible to construct methods to invent (help the inventor

to solve its problems). TRIZ : Key facts Around 50 years of research (1946‐1985) – performed in 300 schools/Laboratories (ex‐USSR) Data’s : 300 bio of inventors – 400,000 patents – 1500 Technical systems through their history

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SLIDE 14
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

14

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

Contradiction Laws of engineering systems evolution Ressource Inventive principles 76 Standards Ideality Substances‐Field Pointers to physical effects Separation methods Database of effects Miniture men STC operators Multisceen Trimming techniques ARIZ85C

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SLIDE 15

Methods Meta-Kn bases Tools

Fundamentals

(postulates, axioms)

ARIZ85C, Su‐field modeling, Miniature men, STC operators

  • 9 laws
  • 11 methods for separating physical

contradictions

  • 40 Inventive Principles
  • System of 76 Inventive Standards
  • 1200 Effects (Physical, Chemical, Geometrical)

Matrix, Pointers of Effects, Algorithm for choosing inventive standards,…

  • Technical

systems (artifacts) are governed by

  • bjective laws.
  • An inventive problem, if reformulated in the form of

a dialectical contradiction, can be better solved.

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

15

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS
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SLIDE 16
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

16

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

An attempt of definition : Russian acronym of Theory of Inventive Problem Solving. Theory elaborated by Genrich Altshuller stipulating that technical systems are directed by laws governing their evolutions. To evolve from a generation to another, a technical system solves its contradictions, towards its ideality, while minimizing the use

  • f

available resources. 1st Axiom: The evolution

  • f

technical systems is governed by

  • bjective

laws. These laws are invariants of their evolution. 2nd Axiom: Any problematic situation can be translated in the elementary form

  • f

a contradiction (within the meaning of dialectic).

Corollary 1.1: The laws help to locate the state of maturity

  • f the system and to better anticipate its evolutions.

Corollary 1.2: A direction

  • f

design in accordance with these laws has statistically more chances to appear relevant. Corollary 2.1: An identified and formulated contradiction becomes an inventive

  • pportunity

when its resolution is refusing compromise. Corollary 2.2: Impossibility

  • f

formulating a contradiction indicates that what appears as a problem might not be an Inventive Problem.

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SLIDE 17

TRIZ postulates:

Laws of engineering systems evolution

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SLIDE 18
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

18

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

law 8: Dynamization

In

  • rder

to improve their performance, rigid systems should become more

  • dynamic. By

dynamic we mean: evolve to more flexible and rapidly changing structures, adaptable to changes of working conditions and requirements of the environment.

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SLIDE 19
  • 1. System completeness
  • 2. Efficiency
  • 3. Harmonization
  • 4. Ideality
  • 5. Irregularity
  • 6. Towards Supersystem
  • 7. Towards Microlevel
  • 8. Dynamization
  • 9. Through S‐Field involvement
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

19

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS
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SLIDE 20
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

20

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

9 laws have been disclosed by TRIZ founders,

they can be used to discuss the evolution potential of any technical system

9 laws Maturity statement Evolution potential

  • 1. System completeness
  • 2. Efficiency
  • 3. Harmonization
  • 4. Ideality
  • 5. Irregularity
  • 6. Towards Supersystem
  • 7. Towards Microlevel
  • 8. Dynamization
  • 9. Through S‐Field involvement
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SLIDE 21

TRIZ postulates

Contradiction

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SLIDE 22

thick thin Mechanical resistance transportability

Thickness Platen

AC (administrative): I wish [my table resists to heavy loads] but I don’t know how ! TC (technical): If I improve [mechanical resistance]

  • f

[my table] then [transportability] gets worse ! PC (physical): The [thickness]

  • f

the [platen] must be [thick] for having a statisfactory [mechanical resistance] and [thin] for a satisfactory [transportability].

Contradictions typologies

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

22

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS
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SLIDE 23

TRIZ

when observed as a method

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SLIDE 24
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

24

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

Abstract domain

Technological domain

Real-life domain

MP MS

Model of the Problem Model of the Solution Solution concept

DP IS SC DS

Initial situation Well defined problem Detailed solution Formulate Construct Model Interpret

TRIZ Solving tools Technological transfer

(solution is found somewhere else)

Brainstorming or

  • bvious solution
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SLIDE 25
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

25

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS

MP MS DP IS SC DS

A B

GEP8: Volume Of fixed object GEP33: Convenience

  • f use

SCx: Use

  • f

a mechanically constrained rubber base (in torsion) to switch from fine to large application surface. Ergonomy of make‐up

Space occupancy

Appliction cross‐section

fine large

  • 30. Flexible membrane, thin films
  • a. Replace existing objects with flexible

membranes.

15 – 13 30 - 12
  • 15. Dynamism
  • b. Separate an objet into several
  • nes movable between each others.
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SLIDE 26

Law 3 : Harmonization Law 3 : Harmonization Law 8 : Dynamization Law 8 : Dynamization

Long Short Shirt stability Easyness of hanging

Lenght

Arms

Draw a portrait (face) of the Solution if following the law Draw a portrait (face) of the Solution if following the law

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

26

Short (hopefully different) overview of what TRIZ is

  • 3. STEPS
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SLIDE 27

The TRIZ Consortium

3 Large scale companies interested in TRIZ Decided to unify efforts

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SLIDE 28
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

28

The origins of IDM methodology

  • 3. STEPS

Life Long Learning : IDM

«Inventive Design Method based on TRIZ and its associated software STEPS» 3 weeks training plus a professional project mentored by experts

A network of experts trained

Assisting IDM-TRIZ diffusion in companies worldwide

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SLIDE 29

Understanding

TRIZ limitations

In industrial context

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SLIDE 30

Expert in Plastic manufacturing Mechanical engineer Expert in assembly Expert in marketing

About initial and exhaustive investigations :

  • TRIZ

is not designed to investigate complex initial situations (gathering thoroughly all knowledge necessary and known to document/understand the diversity and the quantity of problems).

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

30

5 major drawbacks of TRIZ

  • 3. STEPS
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SLIDE 31

About contradiction’s quantity… and choice :

  • TRIZ

is designed for solving a single contradiction. How to disclose, represent and chose the most appropriate

  • ne

since contradictions quantity increase exponentially with system’s complexity ?

ease of placing clothes on

stability

Arm’s length

long short

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

31

5 major drawbacks of TRIZ

  • 3. STEPS
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SLIDE 32

About a methodology to disclose a contradiction :

  • There are no accurate ways to disclose appropriately a contradiction.

As you know, I’m a TRIZ expert, therefore I know the truth… The contradiction is…

TRIZ expert
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

32

5 major drawbacks of TRIZ

  • 3. STEPS
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SLIDE 33

About TRIZ corpus consistency :

  • Are

you aware

  • f

any “glossary”

  • r

“ontology”

  • f

TRIZ components ? There are no logical links/coherence between TRIZ components.

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

33

5 major drawbacks of TRIZ

  • 3. STEPS
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SLIDE 34
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

34

5 major drawbacks of TRIZ

  • 3. STEPS

Where is TRIZ’s best solution ?

  • There are no means in TRIZ to help the designer to decide, among

a set of Solution concepts being all inventive, which one is the one to choose.

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SLIDE 35

There is a need to efficiently deploy IDM methodology

The industrial partners proposed :

To build a new software !

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SLIDE 36
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

36

Why do we need a software ?

  • 3. STEPS

A first statement in which industrial and academic partners agreed

  • n

: There is a need for a software :

  • To

assist the animator in conducting inventive activities (to structure, to organize study data’s);

  • To relieve users of tedious tasks;
  • To

ensure minimal (robustness) consistency

  • f

the approach;

  • To permit the sharing of practices inside a community;
  • To

install a spiral

  • f

constant evolution in the development of the software through research.

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SLIDE 37

Stage 1 : Analysis of Initial Situation Stage 1 : Analysis of Initial Situation Stage 2 : Contradiction management Stage 2 : Contradiction management Stage 3 : Solution Concepts synthesis Stage 3 : Solution Concepts synthesis Stage 4 : Solution Concepts selection Stage 4 : Solution Concepts selection To high impact, inventive, solution concepts in which company is ready to invest for further developments To high impact, inventive, solution concepts in which company is ready to invest for further developments

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

37

IDM’s 4 major Sages

  • 3. STEPS
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SLIDE 38
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

38

Starting with an Initial situation

  • 3. STEPS

Step 1 : Analysis of Initial Situation Step 2 : Contradictions management Step 3 : Solution Concepts synthesis Step 4 : Solution Concepts selection

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SLIDE 39
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

39

Starting with an Initial situation Managing populations of contradictions

  • 3. STEPS
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SLIDE 40
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

40

Starting with an Initial situation Managing populations of contradictions

  • 3. STEPS
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SLIDE 41
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

41

Starting with an Initial situation Managing populations of contradictions

  • 3. STEPS
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SLIDE 42
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

42

Fully operated TRIZ techniques

  • 3. STEPS

The Matrix The Matrix Miniature Men Miniature Men Su‐Field Su‐Field Separation methods Separation methods ARIZ85C ARIZ85C

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SLIDE 43
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

43

STEPS’s Solution Concept cards

  • 3. STEPS

A Solution Concept tree is built

(each branch is a solution concept card)

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SLIDE 44

Conducting an industrial case : summary

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SLIDE 45

Day 1 Day 1 Day 2 Day 2 Day 3 Day 3 Day 4 Day 4 Day 5 Day 5 Day 6 Day 6 Day 7 Day 7 Day 8 Day 8 Day 9 Day 9 Day 10 Day 10 Phase consisting in drawing a problem statement through a problem graph and known partial solutions

Problem Statement phase

Phase consisting in entering into the detailed problem description through a key problem and disclosing all its related contradictions

Data’s gathering and Contradiction analysis

Phase consisting in engaging several contradictions (the most relevant ones) into a solving phase using TRIZ techniques. Solution concepts are drawn in this phase.

Contradictions treatment

Phase consisting in engaging R&D means to characterize technologically and qualitatively the solution concept’s feasibility

Calculations & validations of the chosen solution Concepts Flexible schedule consisting in 10 sessions face to face and an equivalent amount of work “off sessions” by both INSA study leader and Company team members (based on a complex case situation)

Solution Concepts analysis

Phase consisting in analyzing Solution Concepts and choosing a reduced set of them for further calculations based on the Problem network shrinkage they provoke

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

45

Summary of a case study

  • 3. STEPS
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SLIDE 46

Crash retention in High speed trains

  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

46

Summary of a case study

  • 3. STEPS
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SLIDE 47

Competing arena in high speed train market Case study in high speed train industry : Crash absorbing system Case study in high speed train industry : Crash absorbing system

Analysis of competition and state of the art of expert knowledge on the topic

All people knowledge and doc. (patents, articles) are studied

Analysis of competition and state of the art of expert knowledge on the topic

All people knowledge and doc. (patents, articles) are studied

Towards calculation and 3D modelling of the solution concept for validation Towards calculation and 3D modelling of the solution concept for validation

Problematic : How to efficiently absorb energy in crash situations? Problematic : How to efficiently absorb energy in crash situations?

Construction of a problem graph Construction of a problem graph Interpreting the graph : define the core problem Interpreting the graph : define the core problem Contradiction extraction & management Contradiction extraction & management

Use of TRIZ techniques for building solution concept Use of TRIZ techniques for building solution concept

Use of Pugh’s matrixes for automatic ranking

  • f solution concepts

Use of Pugh’s matrixes for automatic ranking

  • f solution concepts
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

47

Summary of a case study

  • 3. STEPS
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SLIDE 48

Teaching IDM

to engineers in life-long learning

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SLIDE 49
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

49

Teaching IDM

  • 3. STEPS

All classical components of TRIZ are studied in a comprehensive course with industrial exercises and team working + public presentation of the work (35 hours/5 days) Advanced techniques

  • f TRIZ are applyed

(Su‐Field ; ARIZ) on industrial situations with a mentoring and team working + public presentation of the work (35 hours/5 days) IDM (extensions of TRIZ towards complex and multidisciplinary situations) are studied and applied on a professional basis in a real industrial

  • project. A mentoring on the project is

provided by a IDM‐Expert and specific abilities of animating a team are provided through the exercise (2 x 35 Hours / 70 Hours) An official full version of STEPS software is necessary all along the trainning process

1 2 3 4

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SLIDE 50

Some limitations of in which we are currently conducting research (ongoing PhD)

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SLIDE 51
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

51

  • 3. STEPS

Limit N°2

  • f
  • ur

work :

For a permanently evolving coherence

  • f
  • ur

work and error‐free concepts manipulations, using computers is necessary.

Conclusions

Limit N°3 of our work : There are still no means

  • f

measuring Inventive Efficiency in R&D teams (besides simply counting invested funds

  • r

patents), therefore how can we monitor the effects of IDM adoption ?

Limit N°4

  • f
  • ur

work :

Solution Concepts are always “hard to believe” especially by expert since they are outside what they classically admit as possible. Achille Souilli’s PhD

Limit N°1

  • f
  • ur

work :

Team working for “human‐built” problem graph is too long and not 100% accurate Ali Taheri’s PhD Wei Yan’s PhD Thongchai Chinkatham’s PhD

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SLIDE 52
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

52

  • 3. STEPS

Conclusions

Quantity of scientific papers per years being published and using the keyword TRIZ in the title or the abstract

1997 2011

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SLIDE 53
  • 1. Context
  • 2. From TRIZ to IDM
  • 4. Case example
  • 5. Perspectives

53

Conclusions

  • 3. STEPS

What are we heading towards :

  • Research

: building new knowledge through partnership always keeping in mind its usefulness for society (industry) ;

  • Education

: train people at all levels with academic excellence in mind;

  • Expertise

: create a network of experts, able to practice, teach assist industry with IDM‐TRIZ model;

  • For all these 3 directions, our software STEPS

is at the crossroads :

  • Educating

more efficiently, more rapidly using STEPS;

  • Trying
  • ur

new research findings using proto‐STEPS for research and tests;

  • Practicing

IDM‐TRIZ in industry through a growing community of practice using STEPS as a methodological guideline.

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SLIDE 54