Title:
A computational model of engineering decision making

dc.contributor.advisor German, Brian J.
dc.contributor.author Heller, Collin M.
dc.contributor.committeeMember Feigh, Karen
dc.contributor.committeeMember Paredis, Chris
dc.contributor.department Aerospace Engineering
dc.date.accessioned 2014-01-13T16:21:43Z
dc.date.available 2014-01-13T16:21:43Z
dc.date.created 2013-12
dc.date.issued 2013-08-29
dc.date.submitted December 2013
dc.date.updated 2014-01-13T16:21:43Z
dc.description.abstract The research objective of this thesis is to formulate and demonstrate a computational framework for modeling the design decisions of engineers. This framework is intended to be descriptive in nature as opposed to prescriptive or normative; the output of the model represents a plausible result of a designer's decision making process. The framework decomposes the decision into three elements: the problem statement, the designer's beliefs about the alternatives, and the designer's preferences. Multi-attribute utility theory is used to capture designer preferences for multiple objectives under uncertainty. Machine-learning techniques are used to store the designer's knowledge and to make Bayesian inferences regarding the attributes of alternatives. These models are integrated into the framework of a Markov decision process to simulate multiple sequential decisions. The overall framework enables the designer's decision problem to be transformed into an optimization problem statement; the simulated designer selects the alternative with the maximum expected utility. Although utility theory is typically viewed as a normative decision framework, the perspective in this research is that the approach can be used in a descriptive context for modeling rational and non-time critical decisions by engineering designers. This approach is intended to enable the formalisms of utility theory to be used to design human subjects experiments involving engineers in design organizations based on pairwise lotteries and other methods for preference elicitation. The results of these experiments would substantiate the selection of parameters in the model to enable it to be used to diagnose potential problems in engineering design projects. The purpose of the decision-making framework is to enable the development of a design process simulation of an organization involved in the development of a large-scale complex engineered system such as an aircraft or spacecraft. The decision model will allow researchers to determine the broader effects of individual engineering decisions on the aggregate dynamics of the design process and the resulting performance of the designed artifact itself. To illustrate the model's applicability in this context, the framework is demonstrated on three example problems: a one-dimensional decision problem, a multidimensional turbojet design problem, and a variable fidelity analysis problem. Individual utility functions are developed for designers in a requirements-driven design problem and then combined into a multi-attribute utility function. Gaussian process models are used to represent the designer's beliefs about the alternatives, and a custom covariance function is formulated to more accurately represent a designer's uncertainty in beliefs about the design attributes.
dc.description.degree M.S.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/50272
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Decision making
dc.subject Gaussian process model
dc.subject Utility theory
dc.subject.lcsh Decision making Mathematical models
dc.subject.lcsh Decision making Testing
dc.subject.lcsh Gaussian processes
dc.subject.lcsh Engineering
dc.title A computational model of engineering decision making
dc.type Text
dc.type.genre Thesis
dspace.entity.type Publication
local.contributor.advisor German, Brian J.
local.contributor.corporatename College of Engineering
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.relation.ispartofseries Master of Science in Aerospace Engineering
local.relation.ispartofseries Master of Science in Aerospace Engineering
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relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
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relation.isSeriesOfPublication 09844fbb-b7d9-45e2-95de-849e434a6abc
thesis.degree.level Masters
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