Law, William Sauway (1996) Evaluating imprecision in engineering design. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-08152006-130539
Imprecision is uncertainty that arises because of vague or incomplete information. Preliminary design information is characteristically imprecise: specifications and requirements are subject to change, and the design description is vague and incomplete. Yet many powerful evaluation tools, including finite element models, expect precisely specified data. Thus it is common for engineers to evaluate promising designs one by one. Alternatively, optimization may be used to search for the single "best" design. These approaches focus on individual, precisely specified points in the design space and provide limited information about the full range of acceptable designs. An alternative approach would be to evaluate sets of designs. The method of imprecision uses the mathematics of fuzzy sets in order to represent imprecision as preferences among designs: • Functional requirements model the customer's direct preference on performance variables based on performance considerations: the quantified aspects of design performance represented by performance variables. • Design preferences model the customer's anticipated preference on design variables based on design considerations: the unquantified aspects of design performance not represented by performance variables. Design preferences provide a formal structure for representing "soft" issues such as aesthetics and manufacturability and quantifying their consequences. This thesis describes continuing work in bringing the method of imprecision closer to implementation as a decision-making methodology for engineering design. The two principal contributions of this work are a clearer interpretation of the elements that comprise the method and a more efficient computational implementation. The proposed method for modeling design decisions in the presence of imprecision is defined in detail. The decision-maker is modeled as a hierarchy of preference aggregation operations. Axioms for rational design decision-making are used to define aggregation operations that are suitable for design. An electric vehicle design example illustrates the method. In particular, the process of determining preferences and a preference aggregation hierarchy is shown to be both feasible and informative. Efficient computational methods for performing preference calculations are introduced. These methods use experiment design to explore the design space and optimization assisted by linear approximation to map preferences. A user-specified fractional precision allows the number of function evaluations to be traded-off against the quality of the answer obtained. The computational methods developed are verified on design problems from aircraft engine development and automobile body design. Procedures for specifying preferences and group decisionmaking are described. These procedures provide not only a pragmatic interpretation of the method, but also an informal solution to the problem of bargaining: prerequisites for bringing the method to design problems in the real world.
|Item Type:||Thesis (Dissertation (Ph.D.))|
|Degree Grantor:||California Institute of Technology|
|Major Option:||Mechanical Engineering|
|Thesis Availability:||Restricted to Caltech community only|
|Defense Date:||23 May 1996|
|Default Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Imported from ETD-db|
|Deposited On:||24 Aug 2006|
|Last Modified:||07 Jul 2015 19:10|
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