Advances in reliability analysis and health prognostics using probabilistic machine learning

Date
2020-01-01
Authors
Li, Meng
Major Professor
Advisor
Chao Hu
Committee Member
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Altmetrics
Authors
Research Projects
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Mechanical Engineering
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Mechanical Engineering
Abstract

Many system failures can be traced back to various difficulties in evaluating and designing complex systems under highly uncertain manufacturing and operational conditions. To reduce system failures, the goal of this dissertation is to develop advanced algorithms and methods for designing a reliable engineered system during its design stage and achieving high operational reliability during its operation stage. Specifically, this dissertation employs and creates novel probabilistic machine learning algorithms to help improve the performance in reliability analysis, reliability-based design optimization, and health prognostics of engineered systems. The research contributions of this dissertation are in the areas of engineering design under uncertainty and health prognostics.

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