Comprehensive evaluations of condition monitoring-based technologies in industrial maintenance: A systematic review

IF 14.2 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Mehdi Dadfarnia , Michael E. Sharp , Jeffrey W. Herrmann
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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.
工业维修中基于状态监测技术的综合评价:系统综述
状态监测包括检测、诊断或预测工业设备的故障或失效。鉴于底层人工智能解决方案和基于物联网的技术的进步,状态监测有可能快速改善工业维护过程。采用基于状态监测的技术需要评估其工程和经济效益,以确定投资是否合理。越来越多的研究描述了评估基于状态监测的维护的程序,但文献缺乏对这些评估研究的回顾,以确定研究机会和最佳实践。本文系统综述了基于状态监测技术在工业维修中的评价方法。本综述确定了2001年至2023年间465项相关的同行评议研究,其中42篇文章符合入选标准。对于每篇文章,本文分析了与工业应用特征、状态监测、维护部署、评估技术、性能度量和经济分析相关的评估过程的各个方面。总的来说,这些结果产生了一些见解。与能源系统和运输方式不同,针对制造系统的状态监测评价研究很少。此外,许多研究缺乏关于状态监测和维护模型的细节。此外,大多数研究的评估技术可以通过分析框架、模拟和扩展敏感性分析的组合来改进。最后,由于经济分析、性能测量和不确定性分析的异质性,所回顾的研究很难直接进行比较,这表明未来的研究有机会构建综合报告项目,以增强基于特定领域状态监测的维护评估的可比性。在文献回顾和分析的基础上,本文提出了未来状态监测评估的具体建议和进一步研究的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Manufacturing Systems
Journal of Manufacturing Systems 工程技术-工程:工业
CiteScore
23.30
自引率
13.20%
发文量
216
审稿时长
25 days
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.
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