Mehdi Dadfarnia , Michael E. Sharp , Jeffrey W. Herrmann
{"title":"Comprehensive evaluations of condition monitoring-based technologies in industrial maintenance: A systematic review","authors":"Mehdi Dadfarnia , Michael E. Sharp , Jeffrey W. Herrmann","doi":"10.1016/j.jmsy.2025.06.015","DOIUrl":null,"url":null,"abstract":"<div><div>Condition monitoring involves detecting, diagnosing, or predicting faults or failures in industrial equipment. Given advances in the underlying artificial intelligence solutions and internet of things-based technologies, condition monitoring has the potential to improve industrial maintenance processes rapidly. Adopting condition monitoring-based technologies requires evaluating their engineering and financial benefits to determine whether the investment is justified. An increasing number of studies describe procedures to evaluate condition monitoring-based maintenance, but the literature lacks a review of these evaluation studies to identify research opportunities and best practices. This systematic review aims to report and analyze the evaluation methods for using condition monitoring-based technologies in industrial maintenance. This review identified 465 relevant peer-reviewed studies between 2001 and 2023, from which 42 articles met the eligibility criteria. For each article, this paper analyzed facets of the evaluation process related to the study’s characterizations of the industrial application, condition monitoring, maintenance deployment, evaluation techniques, performance measures, and economic analysis. Collectively, these results yield several insights. Few condition monitoring evaluation studies exist for manufacturing systems, unlike the domains of energy systems and transportation modes. Also, many studies lack details about condition monitoring and maintenance models. Additionally, the evaluation techniques across most studies can improve with combinations of analytical frameworks, simulation, and expanded sensitivity analysis. Lastly, the reviewed studies are difficult to directly compare due to heterogeneity in economic analysis, performance measures, and uncertainty analysis — indicating an opportunity for future research to structure comprehensive reporting items to enhance the comparability of domain-specific condition monitoring-based maintenance evaluations. Based on the literature review and analyses, this review suggests specific recommendations for future condition monitoring evaluation and opportunities for further research.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 449-477"},"PeriodicalIF":14.2000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0278612525001669","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
Condition monitoring involves detecting, diagnosing, or predicting faults or failures in industrial equipment. Given advances in the underlying artificial intelligence solutions and internet of things-based technologies, condition monitoring has the potential to improve industrial maintenance processes rapidly. Adopting condition monitoring-based technologies requires evaluating their engineering and financial benefits to determine whether the investment is justified. An increasing number of studies describe procedures to evaluate condition monitoring-based maintenance, but the literature lacks a review of these evaluation studies to identify research opportunities and best practices. This systematic review aims to report and analyze the evaluation methods for using condition monitoring-based technologies in industrial maintenance. This review identified 465 relevant peer-reviewed studies between 2001 and 2023, from which 42 articles met the eligibility criteria. For each article, this paper analyzed facets of the evaluation process related to the study’s characterizations of the industrial application, condition monitoring, maintenance deployment, evaluation techniques, performance measures, and economic analysis. Collectively, these results yield several insights. Few condition monitoring evaluation studies exist for manufacturing systems, unlike the domains of energy systems and transportation modes. Also, many studies lack details about condition monitoring and maintenance models. Additionally, the evaluation techniques across most studies can improve with combinations of analytical frameworks, simulation, and expanded sensitivity analysis. Lastly, the reviewed studies are difficult to directly compare due to heterogeneity in economic analysis, performance measures, and uncertainty analysis — indicating an opportunity for future research to structure comprehensive reporting items to enhance the comparability of domain-specific condition monitoring-based maintenance evaluations. Based on the literature review and analyses, this review suggests specific recommendations for future condition monitoring evaluation and opportunities for further research.
期刊介绍:
The Journal of Manufacturing Systems is dedicated to showcasing cutting-edge fundamental and applied research in manufacturing at the systems level. Encompassing products, equipment, people, information, control, and support functions, manufacturing systems play a pivotal role in the economical and competitive development, production, delivery, and total lifecycle of products, meeting market and societal needs.
With a commitment to publishing archival scholarly literature, the journal strives to advance the state of the art in manufacturing systems and foster innovation in crafting efficient, robust, and sustainable manufacturing systems. The focus extends from equipment-level considerations to the broader scope of the extended enterprise. The Journal welcomes research addressing challenges across various scales, including nano, micro, and macro-scale manufacturing, and spanning diverse sectors such as aerospace, automotive, energy, and medical device manufacturing.