Equipment Failure Pattern Analysis and Predictive Maintenance Potential Using FOM-Based Integrated 4M Data

This study proposes a maintenance analysis approach using FOM -based 4M integrated data obtained from CMMS and Excel systems in a pharmaceutical manufacturing environment. The maintenance history data were reconstructed from the perspectives of man, machine, material, and method to analyze equipment failure characteristics based on recurrence, conditionality, and periodicity. Machine and man factors significantly affected equipment downtime and operational instability, while material and method factors served as supplementary trigger conditions under specific operating environments. A rule-based analysis framework is proposed to support preventive maintenance and risk identification without additional sensor installation. The proposed approach demonstrates practical utility for leveraging existing maintenance histories within industrial environments.