Developing a Predictive Maintenance Tool for the Company ETUSA

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Date

2023-06-10

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University of M'sila

Abstract

This master's dissertation focuses on developing a predictive maintenance tool for ETUSM, a bus company. The research involves data collection and analysis using advanced analytics techniques and machine learning algorithms to forecast potential failures in the bus fleet. The study contributes to enhancing maintenance practices, minimizing downtime, optimizing costs, and improving the reliability and availability of the buses. The developed tool serves as a significant step towards proactive maintenance strategies in the transportation industry, benefiting both ETUSM and its customers.

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Developing Predictive, Maintenance Tool for the Company ETUSA

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