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Quantitative Design Tools
Decision Matrices in Engineering Design of Innovative Technology




                       Opti...
Contents

  Quantitative Design Tools

  •     Innovative conceptual design
  •     Case study & matrix methods
  •     Me...
Innovative technology

               Engineering design of a
               system with a new concept
                 Na...
The conceptual design phase

                Problem definition


                Concept generation


               Eval...
Case studies
 Conceptual Process/Product Design


(bio)chemical
 engineering          MSc students
                      P...
Case studies
 Research methods




        Observations of design team
        Following meetings
        Analysing design...
Quantitative design tools

    Decision matrix methods
    Quality function deployment
    Pair-wise comparison charts
   ...
Matrix methods
 Multi-criteria decision analysis




Decision matrix
                                          Solution m
...
Arrowian impossibility theorem

Considering a finite number of evaluation criteria and at
least three alternative design c...
Source of the issues

  Commensurability of criteria
  • Measurability
        (scale of measurement)

  • Comparability
 ...
Measurability

   Scale Type         Admissible Transformation   Example

   Nominal            One to one                ...
Comparability

  Trade-off relation between measures
  • Value comparability
                                             ...
Other issues



  Uncertainty
  • Setting up of full set criteria.
  • Independent criteria.
  • Assigning performance rat...
Example: Weighted objectives
 Convincing the design engineers



                   Option 1     Option 2            …    ...
Grading issue

  Criteria           Weight       Option 1   Option 2    Option 3
  Yield              1               2   ...
Weighting issue

 Criteria           Weight       Option 1   Option 2     Option 3
 Yield              0.1             3  ...
Buridan's paradox

  Criteria           Weight       Option 1   Option 2   Option 3
  Yield              0.1             3...
Irrelevant alternative issue

 Criteria           Weight       Option 1   Option 2    Option 3       Option 4
 Yield      ...
Traded-away criteria


  Criteria           Weight       Option 1     Option 2     Option 3
  Yield              1        ...
How to proceed?


               Many designers utilize
                decision matrices.



                         Wha...
Assessment of design tools

               Theories of truth
Consistent
               • Coherence
with rules
            ...
Pragmatic goals in design practice

 Goals of matrix methods
 • Structuring problem
 • Supports communication
 • Enhance c...
Problem structuring

  Ill-structured design problem
  • No criterion to decide the best solution
  • Not well defined sol...
Facilitating communication

     Visual summary
     Show alternative concepts
     Converting requirements
     Judgement...
Creativity enhancement


                 Option 1        Option 2   Option 3   Option 4   Option 5   Option 6

Criterion ...
Conclusion

                 Option 1   Option 2   Option 3   Option 4   …
   Criterion A      +          -          +    ...
Further research

  Midstream modulation
  • Collaboration with designers
  • Stimulate awareness
  • Motivate to discuss ...
Many thanks!




  PDEng trainees
  MSc students
  Supervisors & Clients



May 20, 2010              28
Quantitative Design Tools
Decision Matrices in Engineering Design of Innovative Technology


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Quantitative Design Tools

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Transcript of "Quantitative Design Tools"

  1. 1. Quantitative Design Tools Decision Matrices in Engineering Design of Innovative Technology Option 1 Option 2 Option 3 … Weight Criterion A ++ - 0 … … Criterion B 1 5 3 … … Criterion C 0.1 m/s 0.4 m/s 0.03 m/s … … … … … … … … Score … … … … ir Urjan Jacobs 10 May 2010 1 Biotechnology and Society - TNW & Philosophy - TPM
  2. 2. Contents Quantitative Design Tools • Innovative conceptual design • Case study & matrix methods • Methodological problems • Examples of issues • A way forwards May 20, 2010 2
  3. 3. Innovative technology Engineering design of a system with a new concept Nanotechnology Biotechnology Chemical technology May 20, 2010 3
  4. 4. The conceptual design phase Problem definition Concept generation Evaluation & selection Detailed design May 20, 2010 4
  5. 5. Case studies Conceptual Process/Product Design (bio)chemical engineering MSc students PDEng trainees 10-12 working weeks May 20, 2010 5
  6. 6. Case studies Research methods Observations of design team Following meetings Analysing design documents Semi-structured interview May 20, 2010 6
  7. 7. Quantitative design tools Decision matrix methods Quality function deployment Pair-wise comparison charts Analytic Hierarchy Process May 20, 2010 7
  8. 8. Matrix methods Multi-criteria decision analysis Decision matrix Solution m rid atrix lect ion g Se Decision grid May 20, 2010 8 Note: Multi-attribute value theory (MAVT) and multi-attribute utility theory (MAUT) have a very different starting point.
  9. 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 theory Voting • • Unrestricted scope • Independence of irrelevant concepts • Weak pareto principle • Non-dominance Social choice theory May 20, 2010 9 K.J. Arrow, Journal of Political Economy 58, 1950, 328-346 A. Hylland, Econometrica 48, 1980, 539-542
  10. 10. Source of the issues Commensurability of criteria • Measurability (scale of measurement) • Comparability (relation between measures) May 20, 2010 10
  11. 11. Measurability Scale Type Admissible Transformation Example Nominal One to one Labels Ordinal Monotonic increasing Mohs scale Interval Positive linear Celsius scale Ratio Positive similarities Miles scale Unknown to Engineers May 20, 2010 11 S.S. Stevens, Science 103, 1946, 677-680
  12. 12. Comparability Trade-off relation between measures • Value comparability Revenues • Technical comparability e tu r Safety p era Pr o d t em uctio tor n vol ume R eac Reliability Sustainability May 20, 2010 12
  13. 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 13
  14. 14. Example: Weighted objectives Convincing the design engineers Option 1 Option 2 … Option n Weight Criterion 1 Performance11 Performance12 … Performance1n w1 w2 Criterion 2 Performance21 Performance22 … Performance2n … … … … … … Criterion m Performancem1 Performancem2 … Performancemn wm Score S1 S2 … Sn m Sj = ∑w i =1 i ⋅ Pij May 20, 2010 14
  15. 15. Grading issue Criteria Weight Option 1 Option 2 Option 3 Yield 1 2 3 1 By-products 1 3 1 2 Safety 1 2 3 1 Controllabity 1 2 3 1 Revenues 1 3 1 2 Score 12 11 7 Grade: 1=worst, 2=neutral, 3=best. Criteria Weight Option 1 Option 2 Option 3 Yield 1 2 5 1 By-products 1 5 1 2 Change grading Safety Controllabity 1 1 2 2 5 5 1 1 (best 3 5) Revenues 1 5 1 2 Score 16 17 7 Grade: 1=worst, 2=neutral, 5=best. May 20, 2010 15
  16. 16. Weighting issue Criteria Weight Option 1 Option 2 Option 3 Yield 0.1 3 2 1 By-products 0.3 1 3 2 Safety 0.2 3 1 2 Controllabity 0.3 3 2 1 Revenues 0.1 1 2 3 Score 2.2 2.1 1.7 Grade: 1=worst, 2=neutral, 3=best. Criteria Weight Option 1 Option 2 Option 3 Yield 0.07 3 2 1 By-products 0.36 1 3 2 Change weighting Safety Controllabity 0.14 0.36 3 3 1 2 2 1 (0.07; 0.14; 0.36) Revenues 0.07 1 2 3 Score 2.14 2.22 1.64 Grade: 1=worst, 2=neutral, 3=best. May 20, 2010 16
  17. 17. Buridan's paradox Criteria Weight Option 1 Option 2 Option 3 Yield 0.1 3 2 1 By-products 0.3 2 3 1 Safety 0.2 1 2 3 Controllabity 0.3 2 1 3 Revenues 0.1 3 2 1 Score 2 2 2 Grade: 1=worst, 2=neutral, 3=best. No rational choice … May 20, 2010 17 Aristotle, De Caelo II (On the Heavens), 350 BC
  18. 18. Irrelevant alternative issue Criteria Weight Option 1 Option 2 Option 3 Option 4 Yield 1 4 3 2 1 By-products 1 2 4 3 1 Safety 1 4 2 1 3 Controllabity 1 4 2 1 3 Revenues 1 2 4 3 1 Score 16 15 10 9 Grade: 1=worst, 2=poor, 3=fine, 4=best. Criteria Weight Option 1 Option 2 Option 3 Yield 1 3 2 1 By-products 1 1 3 2 Safety 1 3 2 1 Controllabity 1 3 2 1 Revenues 1 1 3 2 Remove/not consider Score 11 12 7 poor option Grade: 1=worst, 2=neutral, 3=best. May 20, 2010 18
  19. 19. Traded-away criteria Criteria Weight Option 1 Option 2 Option 3 Yield 1 1 2 3 By-products 1 3 2 1 Safety Controllabity 1 1 1 3 2 1 3 2 Biased on Revenues 1 2 3 1 Sustainability Score 1 3 13 2 12 1 11 sustainability Grade: 1=worst, 2=neutral, 3=best. criterion. Condorcet distortion May 20, 2010 19 M. J.A.N. de Caritat Condorcet, Essai sur l'application de l'analyse à la probabilité des décisions rendues à la pluralité de voix, Paris 1785.
  20. 20. How to proceed? Many designers utilize decision matrices. What is their use if not to find the best option? May 20, 2010 20
  21. 21. Assessment of design tools Theories of truth Consistent • Coherence with rules Checked • Correspondence by facts • Pragmatic • … Facilitate obtaining goals May 20, 2010 21
  22. 22. Pragmatic goals in design practice Goals of matrix methods • Structuring problem • Supports communication • Enhance creativity May 20, 2010 22
  23. 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 23
  24. 24. Facilitating communication Visual summary Show alternative concepts Converting requirements Judgement on performances Supports debate on the choice CSTR Feb-batch Batch Yield - + ++ By-products + 0 -- Safety + ++ - Revenues + - 0 May 20, 2010 24
  25. 25. Creativity enhancement Option 1 Option 2 Option 3 Option 4 Option 5 Option 6 Criterion A + D + ++ + - Criterion B ++ A ++ + - -- Criterion C + T 0 + 0 + Criterion D 0 U - -- ++ 0 Criterion E + M + - -- -- May 20, 2010 25 Controlled convergence method S. Pugh, Total Design, Harlow 1991
  26. 26. Conclusion Option 1 Option 2 Option 3 Option 4 … Criterion A + - + 0 … Criterion B ++ ++ + - … Criterion C 0 - -- ++ … Criterion D + + - -- … … … … … … … Keep using the matrix Hold all options & criteria Never calculate a decision May 20, 2010 26
  27. 27. Further research Midstream modulation • Collaboration with designers • Stimulate awareness • Motivate to discuss ‘soft’ issues • Safety, sustainability, robustness May 20, 2010 27
  28. 28. Many thanks! PDEng trainees MSc students Supervisors & Clients May 20, 2010 28
  29. 29. Quantitative Design Tools Decision Matrices in Engineering Design of Innovative Technology Option 1 Option 2 Option 3 Option 4 Option 5 Criterion A + D ++ 0 -- Criterion B ++ A - + - Criterion C + T 0 + 0 Criterion D 0 U - -- ++ Criterion E + M + - - ir. Urjan Jacobs t: +31 (0)15 278 6626 e: j.f.jacobs@tudelft.nl 29 Biotechnology and Society - TNW & Philosophy - TPM
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