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Developing Asset Health Monitoring under Ground Loader Equipment using Ordinal Logistic Regression

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  • Sahala David Siregar
  • Nur Budi Mulyono

Abstract

Asset Health Monitoring (AHM) is a new maintenance strategy developed at PT. Freeport Indonesia. One of the AHM strategy is oil analysis. This study aims to develop a degradation state of existing condition of major component in GBC R1600 Loader. The level of severity on oil analysis gives the indicator of severity level related to the health of its components. The study utilizes an Ordinal Logistic Regression method, to develop the category of degradation state. This methodology helps to identify and measure the severity of degradation state based on the wear rate, contamination, and deterioration of oil analysis parameters. The degradation state developed are i) No Action Required, ii) Monitor Compartment, iii) Action Required, the additional category is iv) Urgent Action Required. The findings will provide new understanding of degradation state level of oil analysis. The study finding is helping Operation Maintenance Division to address the issue related degradation state quicker to maintain the degradation. This quick response of intervention will help Operation Maintenance to maintain its major component before catastrophic failure happened.

Suggested Citation

  • Sahala David Siregar & Nur Budi Mulyono, 2025. "Developing Asset Health Monitoring under Ground Loader Equipment using Ordinal Logistic Regression," European Journal of Business and Management Research, European Open Science, vol. 10(3), pages 136-143, May.
  • Handle: RePEc:epw:ejbmr0:v:10:y:2025:i:3:id:52438
    DOI: 10.24018/ejbmr.2025.10.3.2438
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