Prediksi Waktu Kerusakan Mesin Batching plant Menggunakan Metode Support Vector Machine untuk Meningkatkan Efisiensi Operasional

Authors

  • Dena Rany Riyantati Program Studi Teknik Industri, Fakultas Sains dan Teknologi, Universitas Muhammadiyah Sidoarjo
  • Tedjo Sukmono Program Studi Teknik Industri, Fakultas Sains dan Teknologi, Universitas Muhammadiyah Sidoarjo

DOI:

https://doi.org/10.30737/jatiunik.v8i1.5543

Keywords:

Batching plant, Operational efficiency, Predictive maintenance, SVM

Abstract

The increasing need for productivity and the use of high technology in the form of machines increases the need for maintenance functions. At PT. XYZ, which produces ready mix concrete  , has problems with the production machine with excess machine load. This results in downtime and delays in the production process, resulting in a decrease in machine operational productivity. The purpose of this study is to predict the time of damage to the engine, so that it can determine the right engine maintenance schedule periodically. In this research, the method used is Support Vector Machine which is implemented to python. This prediction is carried out to improve the efficiency and performance of the machine by predicting damage or failure that may occur in the future. Where this SVM can accurately predict breakdowns and proactively optimize maintenance schedules at the right time. This allows companies to improve efficiency in their operational systems, extend the life of machines, and reduce maintenance costs.

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Published

2024-10-22

How to Cite

Rany Riyantati, D., & Sukmono, T. (2024). Prediksi Waktu Kerusakan Mesin Batching plant Menggunakan Metode Support Vector Machine untuk Meningkatkan Efisiensi Operasional. JATI UNIK : Jurnal Ilmiah Teknik Dan Manajemen Industri, 8(1). https://doi.org/10.30737/jatiunik.v8i1.5543

Issue

Vol. 8 No. 1 (2024): October

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