Improvement of a Preventive Maintenance Plan for Machinery in the Canned Beverage Production Line

Abstract

This research aims to enhance the reliability and maintenance efficiency of a Tray Packer machine in a canned beverage production line, which was identified as the bottleneck machine with the highest downtime rate through the Weight Score Method. Conventional maintenance approaches that rely solely on manufacturer manuals or operator experience are insufficient for accurately identifying true machine degradation behavior. This study therefore proposes a novel framework by applying reliability engineering principles through Weibull Distribution Analysis, yielding a shape parameter (β) of 2.79, to verify wear-out failure behavior using actual time-to-failure field data. The findings were then integrated with the Total Productive Maintenance (TPM) concept. Unlike conventional TPM applications that depend primarily on operator judgment, this study uniquely employs statistical evidence derived from Weibull analysis as the basis for defining inspection items and maintenance intervals, resulting in a data-driven Preventive Maintenance plan that reflects actual engineering operating conditions. A comparative performance evaluation before and after implementation revealed a statistically significant reduction in total Breakdown Time by 44.03% and Failure Frequency by 35.20%. Furthermore, the Mean Time to Repair (MTTR) decreased by 13.63%, while the Mean Time Between Failures (MTBF) increased by 55.70%, at a statistical significance level of 0.05 (p < 0.05). The findings demonstrate that a data-driven preventive maintenance plan developed through systematic analysis can effectively reduce production losses, enhance machine stability, and serve as a replicable model applicable to other machinery with similar operating characteristics in the production line.