Predictable Maintenance: A Bayesian Network-based Model
Publish place: International Journal of Reliability, Risk and Safety: Theory and Application، Vol: 5، Issue: 2
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJRRS-5-2_012
تاریخ نمایه سازی: 5 آذر 1402
Abstract:
Industries' increasing progress and complexity has made maintenance and repair tasks very challenging, complex, and time-consuming. Maintenance is one of the important sectors in several industries, and improvement in this sector can have excellent results. This paper develops a new maintenance prediction model based on Bayesian networks (BN) capabilities. The models include several variables that experts determine and their influence on each other's-called conditional probability tables-which are learned from historical data. The model is implemented in an automobile repair department case study to show its performance. The model is evaluated through a sensitivity analysis, and the results show the proficiency of the proposal mode.
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Authors
Mohammad Partovi
School of Industrial Engineering, College of Engineering, University of Tehran, Iran
Mohsen Amra
Department of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran
Mohammadjavad Pahlevanzadeh
Department of Management and Accounting, College of Farabi, University of Tehran, Iran
Abbas Alwardi
Industrial Engineering Department, Faculty of Industry, Management and Accounting, Shahabdanesh University, Qom, Iran
Mohammad Reza Fathi
Associate Professor, College of Farabi, University of Tehran, Iran