Date of Graduation

12-2014

Document Type

Thesis

Degree Name

Master of Science in Mechanical Engineering (MSME)

Degree Level

Graduate

Department

Mechanical Engineering

Advisor/Mentor

Jensen, David C.

Committee Member

Wejinya, Uche C.

Second Committee Member

Millett, Paul C.

Keywords

Design theory and methodology; Failure analysis

Abstract

This paper presents a new failure analysis method, Failure Identification for Mission Analysis (FIMA), which performs a general failure analysis for the overall state of a system, as well as a mission-specific analysis that identifies how failures may have differing effects on the various mission tasks that a system must complete. The FIMA method is capable of being implemented at any point in the design process. During early design stages, the FIMA method will identify various qualitative failure scenarios based on programmed functional relationships and any number of initial failures wished to be simulated. The functional relationships for this method are unique in that along with traditional function-based failure modes, they also include manufacturing-based failure modes in each component's performance model. The models are then used to determine fault propagation paths as well as each failure scenario's criticality on the overall system performance. During later design stages, the FIMA method will introduce the usage of physics-based governing equations to more accurately identify the system's behavior during different failure scenarios. The FIMA method is unique in its ability to identify a specific failure scenario's effects on a system's overall performance and then apply this failure information to specific mission tasks. The FIMA method uses multiple metrics to determine the effects of a given failure scenario on a potential mission plan and then uses other unique metrics to assess and optimize a new mission plan based on the remaining tasks and the remaining functionality of the system's components. This method is demonstrated in two different theoretical case studies with experimental validation to be conducted in the future. The results of the first case study will show how the FIMA method is able to automatically identify a large variety of possible failure scenarios and their varying effects on the overall system's performance, while the second case study will show the FIMA method's mission analysis capabilities by using multiple unique metrics for mission comparisons and optimizations during various potential failure scenarios.

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