Keywords

Dynamics, Industrial engineering, Reliability (Engineering), Simulation methods, System analysis

Abstract

Any product sold is expected to be reliable and available when the customer wants to operate it. Companies that produce large capital products (LCP), such as rockets, satellites, or large gas turbines to generate electrical energy, tend to shy away from extending their testing and validation method above the requirements by law, mainly due to the very high costs of each additional test and the uncertain return on investment. This research shows that today’s state of the art validation methods for LCP, required by law, or suggested in literature, and adapted by these industries, are not capable of capturing all significant failure modes (or even enough failure modes), with the consequence that the subsequently sold commercial product will still experience failures with significant effects on product reliability, and subsequently on the companies’ bottom line earnings projections. The research determines the type of data (significant variables) necessary to correlate a company’s validation policy to product failures after commercialization, and predicts the financial impact of the current validation policy on the company’s profitability. An optimized validation plan and testing policy is suggested, and its impact on a company’s profitability is demonstrated through simulation. A generic methodology is derived and its viability is illustrated using a specific product and a dynamic model developed with data available to the researcher. The generic method can be applied by any company to develop its own model for optimizing product reliability prior to market introduction. iv

Notes

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Graduation Date

2010

Semester

Fall

Advisor

Malone, Linda

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Format

application/pdf

Identifier

CFE0003413

URL

http://purl.fcla.edu/fcla/etd/CFE0003413

Language

English

Release Date

December 2010

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

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