Upaya Peningkatan Productivity Mesin Extrusion 2500 Menggunakan Metode Overall Equipment Effectiveness (OEE) dan Six Big Losses Studi Kasus PT XYZ

Authors

  • Arif Nuryono, S.T., M.T. Author
  • Alloysius Vendhi Prasmoro, S.T., M.T. Author
  • Gusti Andhika Aji Author

DOI:

https://doi.org/10.31599/pv3pam75

Keywords:

Productivity, OEE (Overall Equipment Effectiveness), six big losses, Brainstorming, 5W + 1H

Abstract

  1. XYZ is engaged in manufacturing in making aluminum profile products during the last one year period. XYZ company did not reach its production target by an average of 6.24%. As for the reasons why the production target did not reach the target, one of them was due to the high downtime of the extrusion machine 2500 which exceeded the company standard, namely 7800 minutes per year, the downtime of the extrusion machine 2500 in the last year was 9807 minutes. The purpose of this study is to reduce the downtime value of the extrusion machine using the OEE method (overall equipment effectiveness), to increase the productivity of the extrusion machine 2500 from the results of the analysis of six big losses and identify the main causes of downtime of the extrusion 2500 machine. The results show that the OEE value of the extrusion machine. 2500 by 45. 61% where this value is still below the ideal OEE average standard, namely 85%. The main cause of downtime is due to seven factors that dominate the causes of downtime, namely log heater 2230 minutes with 11 events, puller 1740 minutes with 11 events, dummi block 1390 with 4 events, loader 710 minutes with 4 events, finish cut 540 minutes with 3 events, stem 450 minutes with 2 events, 360 minutes table with 1 event. Based on the results of the calculation of six big losses, the results of downtime values: equipment failure losses 3,81%, setup and adjustment losses 3,95%, speed losses: idle and minor stoppage 3,03%, reduced speed losses 46,51, quality losses: defect losses 0,13%, reduced yield 0 %. The recommendation for improvement is to conduct special training, give warnings to operators who are not disciplined.

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Published

2024-05-30

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Section

Articles