A conceptual framework proposal for the implementation of Prognostic and Health Management in production systems

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
Raffaele Abbate, Chiara Franciosi, Alexandre Voisin, Marcello Fera
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引用次数: 0

Abstract

Prognostic and Health Management (PHM) is an emerging maintenance concept that is highly regarded by the scientific community and practitioners, as its adoption can bring economic, technical and environmental benefits to a company. PHM fully reflects the smart maintenance paradigm encompassing data collection, data manipulation, state detection, health assessment, prognostic assessment and advisory generation. Despite the undeniable benefits, there is still a large gap between the scientific and the real world. Several authors have investigated on the barriers to PHM implementation for companies, highlighting among them the lack of systematic approaches to its design and implementation. As a first contribution to this topic, the authors conducted a systematic literature review (SLR) to investigate the use of Decision Support Systems (DSSs) to support the PHM implementation. The SLR highlighted that few DSS had been developed and were limited to critical unit identification, maintenance strategy selection and data acquisition phase of PHM. Therefore, a conceptual framework for PHM implementation was provided as a second contribution. This framework summarises the decisions that should be addressed by a practitioner wishing to implement PHM services; moreover, it could lay the foundations for the development/improvement of the missing/existing DSSs for PHM implementation.

Abstract Image

关于在生产系统中实施预测和健康管理的概念框架建议
预知和健康管理(PHM)是一种新兴的维护理念,受到科学界和从业人员的高度重视,因为采用这种理念可以为企业带来经济、技术和环境效益。PHM 充分体现了智能维护范式,包括数据收集、数据处理、状态检测、健康评估、预后评估和建议生成。尽管PHM具有不可否认的优势,但科学与现实世界之间仍存在巨大差距。有几位作者对企业实施 PHM 的障碍进行了调查,强调了其中缺乏设计和实施 PHM 的系统方法。作为对这一主题的第一个贡献,作者进行了系统的文献综述(SLR),以调查决策支持系统(DSS)在支持 PHM 实施方面的使用情况。系统文献综述强调,已开发的决策支持系统很少,而且仅限于 PHM 的关键单元识别、维护策略选择和数据采集阶段。因此,作为第二项贡献,提供了 PHM 实施的概念框架。该框架总结了希望实施 PHM 服务的从业人员应做出的决定;此外,它还可为开发/改进缺失/现有的 DSS 以实施 PHM 奠定基础。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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