Optimization of condition-based maintenance strategy-prediction for aging automotive industrial equipment using FMEA

Maintenance plays a highly important role in achieving production targets and system performance. Electromechanical equipment and facility infrastructure within motor manufacturing industries are expected to perform at optimal efficiency during the operational phase of production. A major problem in the automotive production plan from motor industry statistics is associated with unexpected downtime, which is largely linked to aging equipment. During production downtime, much time is lost to fault finding, repairs, and replacement of faulty components within production lines. This transforms into low throughput in production, and performance gradually declines during the operational life cycle of the equipment. This paper presents an approach taken to prevent such instances in the automotive manufacturing industry, which considers an optimized condition-based maintenance approach to predict the condition of each component and assembly line using Failure-Mode-and-Effect-Analysis (FMEA). The condition-based performance level prediction is designed to help in formulating maintenance schedules and strategies that eliminate unplanned downtimes. (C) 2021 The Authors. Published by Elsevier B.V.

Automated summary

Maintenance is crucial in achieving production targets and system performance in the automotive manufacturing industry. Condition-based maintenance can predict equipment status and help formulate maintenance schedules to eliminate unplanned downtimes.