Predictable Maintenance: A Bayesian Network-based Model

Partovi, Mohammad; Amra, Mohsen; Pahlevanzadeh, Mohammadjavad; Alwardi, Abbas; Fathi, Mohammad Reza

doi:10.30699/IJRRS.5.2.10

Predictable Maintenance: A Bayesian Network-based Model

Document Type : Original Research Article

Authors

Mohammad Partovi ¹

Mohsen Amra ²

Mohammadjavad Pahlevanzadeh ³

Abbas Alwardi ⁴

Mohammad Reza Fathi ⁵

¹ School of Industrial Engineering, College of Engineering, University of Tehran, Iran

² Department of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran

³ Department of Management and Accounting, College of Farabi, University of Tehran, Iran

⁴ Industrial Engineering Department, Faculty of Industry, Management and Accounting, Shahabdanesh University, Qom, Iran

⁵ Associate Professor, College of Farabi, University of Tehran, Iran

10.30699/IJRRS.5.2.10

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.

Keywords

Maintenance

Prediction

Bayesian Networks

Conditional Probability

Subjects

Maintenance engineering

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