Analysis of Cut Size Paper Cutting Machine Performance Using Total Productive Maintenance Concept (Case Study: PT. RST)

  • Rolandi Mustafa Mechanical Engineering Department, University of Riau, Indonesia
  • Anita Susilawati Mechanical Engineering Department, University of Riau, Indonesia
  • Ismet Hari Mulyadi Mechanical Engineering Department, Faculty of Engineering, University of Andalas, West Sumatera, Indonesia

Abstract

PT. RST, a leading paper factory in Indonesia, prioritizes timely production by optimizing productivity, efficiency, and paper quality. This study assesses the reliability of the Cut Size (CS) paper cutting machine, which is enhanced through the implementation of Total Productive Maintenance (TPM) as a management philosophy to ensure high-efficiency operations. To evaluate machine performance, Overall Equipment Effectiveness (OEE) measurement is used. From data collected from January to September 2023, an analysis is conducted to improve the performance of the CS machine, which has not met its set target. The average OEE value of 70.9% falls short of the target of 72%. This research aims to improve the performance of the CS machine through the TPM approach, focusing on the Focused Maintenance pillar. Using tools such as Pareto diagram, why-why analysis, fishbone diagram, and the 5W1H method, several sources of problems causing the decrease in OEE value will be identified and addressed.

##Keywords:## Total Productive Maintenance (TPM), Cut Size (CS), Overall Equipment Effectiveness (OEE), Pareto, Why-why analysis, Fishbone
Published
Jul 30, 2024
How to Cite
MUSTAFA, Rolandi; SUSILAWATI, Anita; MULYADI, Ismet Hari. Analysis of Cut Size Paper Cutting Machine Performance Using Total Productive Maintenance Concept (Case Study: PT. RST). Journal of Ocean, Mechanical and Aerospace -science and engineering-, [S.l.], v. 68, n. 2, p. 64-74, july 2024. ISSN 2527-6085. Available at: <https://isomase.org/Journals/index.php/jomase/article/view/365>. Date accessed: 18 apr. 2026. doi: http://dx.doi.org/10.36842/jomase.v68i2.365.

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