Integrated design and operational decision making under uncertainty for enhanced lifecycle performances of engineering systems

Liu, Xinyang

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https://hdl.handle.net/2142/122217 Copy

Description

Title

Integrated design and operational decision making under uncertainty for enhanced lifecycle performances of engineering systems

Author(s)

Liu, Xinyang

Issue Date

2023-11-21

Director of Research (if dissertation) or Advisor (if thesis)

Wang, Pingfeng

Doctoral Committee Chair(s)

Wang, Pingfeng

Committee Member(s)

• Kim, Harrison
• Wang, Qiong
• Shao, Chenhui

Department of Study

Industrial&Enterprise Sys Eng

Discipline

Industrial Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Decision making under uncertainty, operations and maintenance, product design, reliability, sustainability, stochastic optimization

Abstract

With the development of condition monitoring systems and the computational efficiency of health prognosis algorithms, system conditions can be more accurately and efficiently assessed through the operating process. This promotes the adoption of condition-based maintenance and meanwhile brings challenges to evaluate and use the monitoring and prognosis information in operations and design decision-making. This thesis develops prognosis-informed decision-making models for system operations and establishes a framework to integrate operations decisions with design. The main contribution of this thesis is to provide methodologies to evaluate and apply the monitoring information in optimizing operations (e.g., maintenance, end-of-life options) and design (e.g., reliability, warranty service) decisions. To optimize operations decisions with prognosis results, we first develop a new asset management methodology where lifetime prognosis is integrated with parallel asset management to reduce the total lifecycle operating cost including asset purchase cost, operation and maintenance cost, inventory cost, and salvage revenue. We then focus on the maintenance process and establish models to evaluate and optimize the condition-based maintenance strategies for multi-component systems with multiple types of dependencies. To integrate operations decisions with design, we first construct a framework to evaluate the value of continuous monitoring systems and help make optimal decisions on monitoring in the design stage. Then, we integrate the operating stage decisions into the initial system design and jointly optimize reliability, warranty, price, and end-of-life options for product families.

Graduation Semester

2023-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/122217

Copyright and License Information

Copyright 2023 Xinyang Liu

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