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PROPOSED PROCEDURE FOR OPTIMAL MAINTENANCE SCHEDULING UNDER EMERGENT FAILURES
Author(s) -
Abbas Al–Refaie,
Heba Al-shalaldeh,
Natalija Lepkova
Publication year - 2020
Publication title -
journal of civil engineering and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.529
H-Index - 47
eISSN - 1822-3605
pISSN - 1392-3730
DOI - 10.3846/jcem.2020.12315
Subject(s) - scheduling (production processes) , margin (machine learning) , reliability engineering , operations research , idle , computer science , engineering , operations management , machine learning , operating system
Production lines are usually subjected to emergent machine failures. Such emergent failures disrupt pre-established maintenance schedules, which challenge maintenance engineers to react to those failures in real time. This research proposes an optimization procedure for optimizing scheduling repairs of emergent failures. Three optimization models are developed. Model I schedules failures in newly idle repair shops with the objective of maximizing the number of scheduled repairs. Model II maximizes the number of assigned repairs to untapped ranges. Model III maximizes both the number of assigned failure repairs and satisfaction on regular and emergency repairs by resequencing regular and emergent failures in the shop that contains the largest free margin. A real case study is provided to illustrate the proposed optimization procedure. Results reveal that the proposed models efficiently scheduled and sequenced emergent failures in the idle maintenance shops, the untapped ranges between repairs of regular failures, and in the maintenance shop with the largest free margin. In conclusions, the proposed models can greatly support maintenance engineers in planning repairs under unexpected failures.

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