Title: Analytical Study on the Implementation of Total Productive Maintenance (TPM) in CNC Machines - A Case Study: PT XYZ
Authors: Naniek Utami Handayani and Moza Mujahida Rassuna
Volume: 9
Issue: 4
Pages: 90-97
Publication Date: 2025/04/28
Abstract:
Ensuring machine efficiency is essential for maintaining optimal productivity in manufacturing industries. This study investigates the implementation of Total Productive Maintenance (TPM) in CNC Milling machines at PT XYZ, aiming to assess machine effectiveness through Overall Equipment Effectiveness (OEE), analyze production losses using the Six Big Losses framework, and identify failure modes via Failure Mode and Effects Analysis (FMEA). The research methodology includes data collection from February 2023 to January 2024, statistical analysis of machine performance, and root cause identification. The results indicate that the average OEE value for CNC Milling machines is 66.335%, which falls within the industry-standard range but does not meet world-class benchmarks. Reduced Speed Losses (26.653%) is the primary contributor to inefficiencies, followed by Idling and Minor Stoppages (6.397%). The FMEA analysis identifies the damaged spindle bearing as the most critical failure mode, with an RPN value of 320, primarily caused by excessive workload and inadequate maintenance. This study highlights the necessity of improving key TPM pillars, including Autonomous Maintenance, Planned Maintenance, and Training & Education, to enhance machine effectiveness. The company can reduce downtime, improve OEE, and increase overall production efficiency by addressing these areas. Future research should explore advanced predictive maintenance techniques like IoT-based monitoring to optimize machine performance.