Analysis of Machine Performance Using the Overall Equipment Effectiveness and Six Big Losses on Double Saw Machines

  • Muhammad Naufal Nazhif Universitas Pembangunan Nasional Veteran, Jawa Timur, Indonesia
  • Joumil Aidil Saifuddin Universitas Pembangunan Nasional Veteran, Jawa Timur, Indonesia
Keywords: Performance Effectiveness,, Machine Breakdown,, Overall Equipment

Abstract

PT Sumber Mas Indah Plywood is a manufacturing company engaged in the furniture sector with product specialization in plywood manufacturing furniture and plywood furniture. The research was conducted in January-December 2023 using the Overall Equipment Effectiveness (OEE) method to determine the effectiveness value of the machine.The objective of this study is to improve the performance of the double saw machine and propose improvements at PT Sumber Mas Indah Plywood to improve production quality. This study was conducted to measure the effectiveness of the double saw machine to determine its effectiveness value. the Overall Equipment Effectiveness (OEE) method is used here to measure it. The OEE value is affected by three factors, which are the availability, performance, and quality. The results obtained are that the effectiveness of the machine is still quite high, with an OEE value of 83.54% and still below the OEE standard value of 85%. To improve OEE, additional steps could include the identification of emerging problem. This allows improvement efforts to be directed towards addressing major challenges. The recommendation for the proposed repair of the double saw machine owned by PT Sumber Mas Indah Plywood should be used as a preventive maintenance strategy where the strategy can be carried out to monitor the machine so that it is in prime condition and ready to use and preventive steps can be taken before a problem occurs on the double saw machine.

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Published
2025-07-15
How to Cite
Nazhif, M. N., & Saifuddin, J. A. (2025). Analysis of Machine Performance Using the Overall Equipment Effectiveness and Six Big Losses on Double Saw Machines. Journal La Multiapp, 6(3), 646-661. https://doi.org/10.37899/journallamultiapp.v6i3.2024