Hot Melt Machine Maintenance Effectiveness Analysis Using Mean Time Between Failures (MTBF) and Mean Time to Repair (MTTR) Methods

Bima Ananto; Afif Fawa Idul  Fata; Priyo Ari  Wibowo

doi:10.54783/influencejournal.v8i3.397

Authors

Bima Ananto Sekolah Tinggi Teknologi Wastukancana, Purwakarta, Indonesia
Afif Fawa Idul Fata Sekolah Tinggi Teknologi Wastukancana, Purwakarta, Indonesia
Priyo Ari Wibowo Sekolah Tinggi Teknologi Wastukancana, Purwakarta, Indonesia

DOI:

https://doi.org/10.54783/influencejournal.v8i3.397

Keywords:

Machine Maintenance Effectiveness; Mean Time Between Failures (MTBF); Mean Time to Repair (MTTR); Fishbone Diagram; Pareto Diagram.

Abstract

Hot Melt Machine 01 at PT. Nutech Pundi Artha Purwakarta is a critical machine in the coating and bonding process of BZ340 Carpet material. However, during the period from September 2025 to February 2026, this machine frequently experienced technical disturbances that caused repeated downtime, while the company had no quantified data to objectively assess its maintenance performance. This study aimed to analyze the machine's operational performance based on failure frequency and interval, evaluate the effectiveness of repair time, identify the causes of damage, and formulate improvement proposals to enhance machine reliability. A quantitative descriptive approach was applied using six months of historical downtime, failure frequency, and repair time data collected through observation, documentation, and interviews, which were processed using the Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR), Availability, Pareto Diagram, and Fishbone Diagram methods with a Man, Method, Material, Machine, and Environment approach. The results showed that the machine experienced fifteen failures over a total operating time of 992 hours, yielding an average MTBF of 69 hours per month and an average Availability of 94%, while the average MTTR was 3.9 hours per occurrence out of a total downtime of 58 hours, with the weakest performance occurring in November and January. Pareto analysis revealed that spray-nozzle replacement, pump-PCB damage, and control-board damage were the dominant causes, with the top ten types of damage contributing nearly 80% of total downtime, while Fishbone analysis identified that the root causes lay in the absence of a daily inspection checklist and inconsistent completion of the maintenance logbook. These findings led to a proposal to develop a daily checklist and optimize the maintenance logbook as early-detection instruments, which are expected to increase MTBF, reduce MTTR, and improve machine Availability.

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