Quantitative Design Tools
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1 Quantitative Design Tools Decision Matrices in Engineering Design of Innovative Technology 10 May 2010 ir Urjan Jacobs Biotechnology and Society - TNW & Philosophy - TPM … … … … … … … … … … … … … … Score … 0.03 m/s 0.4 m/s 0.1 m/s Criterion C … 3 5 1 Criterion B … 0 - ++ Criterion A Weight Option 3 Option 2 Option 1
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Urjan Jacobs fPET-2010 presentation
Transcript of Quantitative Design Tools
1
Quantitative Design ToolsDecision Matrices in Engineering Design of Innovative Technology
10 May 2010
ir Urjan Jacobs
Biotechnology and Society - TNW & Philosophy - TPM
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…0.03 m/s0.4 m/s0.1 m/sCriterion C
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…0-++Criterion A
WeightOption 3Option 2Option 1
May 20, 2010 2
Contents
Quantitative Design Tools
• Innovative conceptual design• Case study & matrix methods• Methodological problems• Examples of issues• A way forwards
May 20, 2010 3
Innovative technology
Engineering design of a system with a new concept
Nanotechnology
Biotechnology
Chemical technology
May 20, 2010 4
The conceptual design phase
Problem definition
Concept generation
Evaluation & selection
Detailed design
May 20, 2010 5
Case studiesConceptual Process/Product Design
10-12 working weeks
MSc students
PDEng trainees
(bio)chemicalengineering
May 20, 2010 6
Case studiesResearch methods
Observations of design team
Following meetings
Analysing design documents
Semi-structured interview
May 20, 2010 7
Quantitative design tools
Decision matrix methods
Quality function deployment
Pair-wise comparison charts
Analytic Hierarchy Process
May 20, 2010 8
Note: Multi-attribute value theory (MAVT) and multi-attribute utility theory (MAUT) have a very different starting point.
Decision matrix
Selection grid
Decision grid
Solution matrix
Matrix methodsMulti-criteria decision analysis
May 20, 2010 9
Arrowian impossibility theorem
Considering a finite number of evaluation criteria and at least three alternative design concepts, no method can simultaneously satisfy:
• Global rationality• Unrestricted scope• Independence of irrelevant concepts• Weak pareto principle• Non-dominance
K.J. Arrow, Journal of Political Economy 58, 1950, 328-346A. Hylland, Econometrica 48, 1980, 539-542
Social choice theory
Voting theory
May 20, 2010 10
Source of the issues
Commensurability of criteria• Measurability
(scale of measurement)
• Comparability(relation between measures)
May 20, 2010 11
Measurability
S.S. Stevens, Science 103, 1946, 677-680
Miles scale Positive similaritiesRatio
Celsius scale Positive linearInterval
Mohs scaleMonotonic increasing Ordinal
LabelsOne to oneNominal
ExampleAdmissible TransformationScale Type
Unknown to Engineers
May 20, 2010 12
Comparability
Trade-off relation between measures
• Value comparability
• Technical comparability
SafetyProduction volume
Sustainability
Revenues
Reliability
Reactor temperature
May 20, 2010 13
Other issues
Uncertainty• Setting up of full set criteria.• Independent criteria.• Assigning performance ratings.
Design concepts not at same level of abstraction
Weights dependant on concept performance
May 20, 2010 14
wmPerformancemn…Performancem2Performancem1Criterion m
Sn
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Performance2n
Performance1n
Option n
…S2S1Score
……………
w2…Performance22Performance21Criterion 2
w1…Performance12Performance11Criterion 1
Weight…Option 2Option 1
1
m
j i iji
S w P=
= ⋅∑
Convincing the design engineers
Example: Weighted objectives
May 20, 2010 15
Criteria Weight Option 1 Option 2 Option 3Yield 1 2 3 1By-products 1 3 1 2Safety 1 2 3 1Controllabity 1 2 3 1Revenues 1 3 1 2Score 12 11 7Grade: 1=worst, 2=neutral, 3=best.
Grading issue
Criteria Weight Option 1 Option 2 Option 3Yield 1 2 5 1By-products 1 5 1 2Safety 1 2 5 1Controllabity 1 2 5 1Revenues 1 5 1 2Score 16 17 7Grade: 1=worst, 2=neutral, 5=best.
Change grading(best 3 5)
May 20, 2010 16
Weighting issue
Change weighting(0.07; 0.14; 0.36)
Criteria Weight Option 1 Option 2 Option 3Yield 0.1 3 2 1By-products 0.3 1 3 2Safety 0.2 3 1 2Controllabity 0.3 3 2 1Revenues 0.1 1 2 3Score 2.2 2.1 1.7Grade: 1=worst, 2=neutral, 3=best.
Criteria Weight Option 1 Option 2 Option 3Yield 0.07 3 2 1By-products 0.36 1 3 2Safety 0.14 3 1 2Controllabity 0.36 3 2 1Revenues 0.07 1 2 3Score 2.14 2.22 1.64Grade: 1=worst, 2=neutral, 3=best.
May 20, 2010 17
Buridan's paradox
Criteria Weight Option 1 Option 2 Option 3Yield 0.1 3 2 1By-products 0.3 2 3 1Safety 0.2 1 2 3Controllabity 0.3 2 1 3Revenues 0.1 3 2 1Score 2 2 2Grade: 1=worst, 2=neutral, 3=best.
No rational choice …
Aristotle, De Caelo II (On the Heavens), 350 BC
May 20, 2010 18
Irrelevant alternative issue
Remove/not consider poor option
Criteria Weight Option 1 Option 2 Option 3 Option 4Yield 1 4 3 2 1By-products 1 2 4 3 1Safety 1 4 2 1 3Controllabity 1 4 2 1 3Revenues 1 2 4 3 1Score 16 15 10 9Grade: 1=worst, 2=poor, 3=fine, 4=best.
Criteria Weight Option 1 Option 2 Option 3Yield 1 3 2 1By-products 1 1 3 2Safety 1 3 2 1Controllabity 1 3 2 1Revenues 1 1 3 2Score 11 12 7Grade: 1=worst, 2=neutral, 3=best.
May 20, 2010 19
Traded-away criteria
Criteria Weight Option 1 Option 2 Option 3Yield 1 1 2 3By-products 1 3 2 1Safety 1 1 2 3Controllabity 1 3 1 2Revenues 1 2 3 1Sustainability 1 3 2 1Score 13 12 11Grade: 1=worst, 2=neutral, 3=best.
Condorcet distortion
Biased on sustainability criterion.
M. J.A.N. de Caritat Condorcet, Essai sur l'application de l'analyse à la probabilitédes décisions rendues à la pluralité de voix, Paris 1785.
May 20, 2010 20
How to proceed?
What is their use if not to find
the best option?
Many designers utilize decision matrices.
May 20, 2010 21
Assessment of design tools
Theories of truth
• Coherence
• Correspondence
• Pragmatic
• …
Consistentwith rules
Checkedby facts
Facilitate obtaining goals
May 20, 2010 22
Pragmatic goals in design practice
Goals of matrix methods
• Structuring problem
• Supports communication
• Enhance creativity
May 20, 2010 23
Problem structuring
Ill-structured design problem
• No criterion to decide the best solution
• Not well defined solution space
• No normative framework available
Co-evolution of problem & solution
May 20, 2010 24
Facilitating communication
Visual summary
Show alternative concepts
Converting requirements
Judgement on performances
Supports debate on the choice
0-+Revenues
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Batch
+++Safety
0+By-products
+-Yield
Feb-batchCSTR
May 20, 2010 25
Creativity enhancement
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Option 4
0++-U0Criterion D
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Option 5
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Option 6
0T+Criterion C
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Option 3Option 2Option 1
Controlled convergence methodS. Pugh, Total Design, Harlow 1991
May 20, 2010 26
Conclusion
…
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Option 4
…-++Criterion D
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+++++Criterion B
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Option 3Option 2Option 1
Keep using the matrix
Hold all options & criteria
Never calculate a decision
May 20, 2010 27
Further research
Midstream modulation
• Collaboration with designers
• Stimulate awareness
• Motivate to discuss ‘soft’ issues
• Safety, sustainability, robustness
May 20, 2010 28
Many thanks!
PDEng trainees
MSc students
Supervisors & Clients
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ir. Urjan Jacobst: +31 (0)15 278 6626e: [email protected]
Biotechnology and Society - TNW & Philosophy - TPM
++---U0Criterion D
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Option 5
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Option 3Option 2Option 1
Quantitative Design ToolsDecision Matrices in Engineering Design of Innovative Technology
