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Collaborative Research: Maintenance Planning for Complex Systems in Dynamic Environments

协作研究：动态环境中复杂系统的维护规划

基本信息

批准号：
1855408
负责人：
Yisha Xiang
金额：
$ 24.42万
依托单位：
Texas Tech University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855408&HistoricalAwards=false
关键词：
Collaborative Research Maintenance Planning Complex

项目摘要

Equipment failures in capital-intensive industries, such as oil and gas exploration, aerospace, and power generation, may threaten human lives and have significant environmental and economic impact. Many of these equipment failures can be traced to poor equipment maintenance. One criticism of existing maintenance planning is that the existing predictive failure models do not accurately reflect degradation resulting from multiple causes in dynamic environments. This project addresses the need for better planning models and analysis to enhance equipment reliability in capital-intensive industries. The PIs have established collaborations with industrial partners to ensure the relevance of their research. Educational opportunities for students, including outreach to underrepresented minorities, is also supported by the award. This award will support research on a general and systematic methodology for effective reliability modeling and maintenance planning for critical complex systems in capital-intensive industries. To successfully accomplish the goal, four specific objectives will be achieved: (1) developing a broad class of general stochastic models that can integrally handle the complexities of degradation processes under dynamic environments; (2) constructing general stochastic-modulated multi-dimensional stochastic processes to model the multiple dependent degradation processes under dynamic environments; (3) creating a general mixture degradation framework to capture heterogeneities at both population and unit-levels; and (4) developing a unified maintenance decision-making framework that jointly integrates long-term maintenance planning and short-term dynamic decisions. Successful development of these models will lead to fundamentally new perspectives on the application of reliability and maintenance optimization for complex engineered systems.

在资本密集型行业，如石油和天然气勘探、航空航天和发电，设备故障可能会威胁到人类的生命，并对环境和经济产生重大影响。许多这些设备故障可以追溯到设备维护不善。对现有维护计划的一个批评是，现有的预测故障模型不能准确地反映动态环境中由多种原因引起的退化。该项目解决了对更好的规划模型和分析的需求，以提高资本密集型行业的设备可靠性。pi与工业伙伴建立了合作关系，以确保其研究的相关性。该奖项还支持学生的教育机会，包括向未被充分代表的少数民族伸出援手。该合同将支持对资本密集型工业中关键复杂系统的有效可靠性建模和维护计划的通用和系统方法的研究。为了成功地实现这一目标，将实现四个具体目标：(1)发展一类广泛的通用随机模型，这些模型可以综合处理动态环境下退化过程的复杂性；(2)构造一般随机调制的多维随机过程，模拟动态环境下的多重依赖退化过程；(3)创建一个通用的混合降解框架，以捕获种群和单位水平的异质性；(4)建立统一的维修决策框架，将长期维修计划与短期动态决策相结合。这些模型的成功开发将从根本上为复杂工程系统的可靠性和维护优化应用带来新的视角。

项目成果

期刊论文数量（14）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Two-stage Stochastic Programming for Maintenance optimization of Multi-component Systems

多部件系统维护优化的两阶段随机规划

DOI：
10.1109/rams51457.2022.9894017
发表时间：
2022
期刊：
Proceedings of Annual Reliability and Maintainability Symposium
影响因子：
0
作者：
Zhu, Zhicheng;Xiang, Yisha;Liao, Ying
通讯作者：
Liao, Ying

Condition-based maintenance for multi-component systems: Modeling, structural properties, and algorithms

DOI：
10.1080/24725854.2020.1741740
发表时间：
2019-07
期刊：
IISE Transactions
影响因子：
2.6
作者：
Zhicheng Zhu;Yisha Xiang
通讯作者：
Zhicheng Zhu;Yisha Xiang

Redundancy Allocation for Serial-Parallel System Considering Heterogeneity of Components

考虑部件异构性的串并系统冗余分配

DOI：
10.1115/msec2018-6481
发表时间：
2018
期刊：
ASME 2018 13th International Manufacturing Science and Engineering Conference
影响因子：
0
作者：
Zhu, Zhicheng;Xiang, Yisha;Coit, David
通讯作者：
Coit, David

Reliability Analysis of Flow Meters with Multiple Failure Modes in the Process Industry