Decision Making in Predictive Maintenance: Literature Review and Research Agenda for Industry 4.0

被引：57
|
作者：
Bousdekis, Alexandros [1 ]
Lepenioti, Katerina [1 ]
Apostolou, Dimitris [1 ,2 ]
Mentzas, Gregoris [1 ]
机构：
[1] NTUA, ICCS, IMU, Athens, Greece
[2] Univ Piraeus, Dept Informat, Piraeus, Greece
来源：
IFAC PAPERSONLINE | 2019年 / 52卷 / 13期
关键词：
Dynamic decision making; smart factory; real-time; predictive maintenance; survey; PREVENTIVE MAINTENANCE; IMPERFECT MAINTENANCE; SYSTEMS; OPTIMIZATION; POLICY; DEGRADATION; RELIABILITY; INVENTORY; STRATEGY; SUBJECT;
D O I：
10.1016/j.ifacol.2019.11.226
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The emergence of Industry 4.0 has led to a wide use of sensors which have facilitated manufacturing operations. Predictive maintenance has significantly benefited from these technological advancements with the use of real-time detection and prediction algorithms regarding future failures. During the last years, there is also an increasing interest on decision making algorithms triggered by failure predictions. The current paper reviews the literature on decision making in predictive maintenance in the context of smart manufacturing. Moreover, it discusses the results, identifies the existing research gaps and outlines a research agenda on the field. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：607 / 612
页数：6
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