Date of Award

5-2013

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Mechanical Engineering

Advisor

Summers, Joshua D

Committee Member

Fadel , Georges M

Committee Member

Switzer , Fred S

Abstract

Design reviews are typically used for three types of design activities: 1) identifying errors, 2) assessing the impact of the errors, and 3) suggesting solutions for the errors. This experimental study focuses on understanding the second issue as it relates to the number of errors considered, the existence of controls, and the level of domain familiarity of the assessor. A set of design failures and associated controls developed for a completed industry sponsored project is used as the experimental design problem. Non-domain individuals (psychology class students), domain generalists (first year engineering students), and domain specialists (graduate mechanical students) are provided a set of failure modes and asked to estimate the likelihood that the system would still successfully achieve the stated objectives. Primary results from the study include the following: the confidence level for all domain population decreased significantly as the number of design errors increased (largest p-value=0.0793) and this decrease in confidence is more significant as the design errors increase. The impact on confidence is less when solutions (controls) are provided to prevent the errors (largest p-value=0.0334), the confidence decreased faster for domain general engineers as compared to domain specialists (p= The research presents a study on how estimations are made in design reviews. It answers the question on how individuals assess the performance of systems which is necessary to be addressed in order to evaluate the importance of methods such as design reviews and design review tools (FMEA, DFMEA, FTA) used in design engineering. It addresses the challenges faced by the impact of design errors in the design process and how they affect assessment by different types of designers in predicting successful system performance.

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