Abstract
Chapter 2 introduces the reader to multi-objective optimization problems, namely the general approach that is used when complex problems with conflicting objectives are to be faced. This will allow the reader to become confident with the principle of how an optimal solution is to be sought in a scarcity environment where maximum utility decisions are not configurable with the best materials as far as their properties are concerned, and with the best compromises needed, which have to be made so as to compete and succeed on the market. Starting from a general overview of Quality Function Deployment, QFD - a tool historically developed at Mitsubishi's Kobe - we go on to illustrate how this has been developed for the precise purpose of screening and assessing engineering materials to maximize common "utility" as regards "choice in scarcity".
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Notes
- 1.
Ibid. Ashby, 2005
- 2.
Ibid. Ashby, 2005
- 3.
Ibid. Ashby, 2005
- 4.
Ibid. Ashby, 2005
- 5.
Ibid. Ashby, 2005.
- 6.
For the demonstration, you can refer to microeconomics textbooks that deal with the consumer’s problem with indifference curves.
- 7.
In the 1920s the economist Paul Douglas was working on the problem of relating inputs and output at the national aggregate level. A survey by the National Bureau of Economic Research found that during the decade 1909–1918, the share of output paid to labor was fairly constant at about 74 %, despite the fact the capital/labor ratio was not constant. He enquired of his friend Charles Cobb, a mathematician, if any particular production function might account for this. This gave birth to the original Cobb–Douglas production function , where K is factor capital, L is labor and A is a constant that represents productivity efficiency (Cobb, C. W. and P. H. Douglas, 1928).
- 8.
Ibid. Cobb and Douglas, 1928.
- 9.
Ibid. Cobb and Douglas, 1928.
- 10.
Note that computer assisted (and automated) methods we discussed in the Chapter 1 are a valid support in the phase of generating a possible candidate solution like those represented in the plot of Fig. 13.
- 11.
Ibid. Ashby, 2005.
- 12.
Ibid. Ashby, 2005.
- 13.
Ibid. Ashby, 2005.
- 14.
In reality, choosing target values requires you to consider several things, such as the ratings and absolute values determined in the technical comparison with competitors, the importance ratings of the customer requirements you are trying to satisfy along with the associated data from the comparisons the customers have made with the competitors and any positive and negative relationships highlighted in the conflicts matrix.
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D’Errico, F. (2015). Multi-Objective Optimization in Engineering Design. In: Material Selections by a Hybrid Multi-Criteria Approach. SpringerBriefs in Materials. Springer, Cham. https://doi.org/10.1007/978-3-319-13030-9_2
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