Title: A systematic literature review on applications of condition-based maintenance strategy

Authors: Mohammed A. Noman; Emad S. Abouel Nasr; Adel Al-Shayea; Fawaz M. Abdullah; Husam Kaid; Mohammed Alnahari

Addresses: Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia; Department of Industrial and Manufacturing System Engineering, Faculty of Engineering, Taiz University, P.O. Box 6169, Taiz, Yemen ' Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia; Faculty of Engineering, Mechanical Engineering Department, Helwan University, Cairo 11732, Egypt ' Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia ' Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia ' Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia ' Civil Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia

Abstract: Condition-based maintenance (CBM) is a maintenance program that recommends maintenance decisions based on collected data through condition monitoring. The aim of this paper is to come out with a brief summary of CBM with definitions of different terms, history, recent developments, and applications of the CBM domain. This paper also presents a literature review on the reported articles on CBM. The concept of CBM includes different fields of study such as data mining, artificial intelligence, and statistics to enable any systems to be maintenance smart. Based on the review, the typical new approaches and methods were introduced; the advantages and disadvantages of these approaches were discussed.

Keywords: condition-based maintenance; CBM; reliability-centred maintenance; RCM; CBM+; data mining.

DOI: 10.1504/IJCENT.2020.110209

International Journal of Collaborative Enterprise, 2020 Vol.6 No.2, pp.105 - 133

Received: 12 Dec 2018
Accepted: 10 Dec 2019
Published online: 09 Oct 2020 *

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