Implementasi SAP Plant Maintenance dalam Strategi Predictive Maintenance untuk Efisiensi Biaya dan Optimalisasi Kinerja Aset

Authors

  • Ibra Agus Prayoga Universitas Pembangunan Nasional “Veteran” Jawa Timur
  • Raden Johnny Hadi Raharjo Universitas Pembangunan Nasional "Veteran" Jawa Timur

DOI:

https://doi.org/10.55606/jurrie.v5i1.7952

Keywords:

Predictive Maintenance, SAP PM, Cost Efficiency, Downtime, OEE

Abstract

The implementation of predictive maintenance supported by SAP Plant Maintenance (SAP PM) at PT Xyz has proven to be effective in reducing machine downtime, lowering maintenance costs, and improving asset reliability. The integration of SAP PM with Industry 4.0 technologies such as IoT sensors, AI-based analytics, and real-time notification systems strengthens operational efficiency and ensures continuous performance. Empirical results show improvements in key performance indicators, including a 20-25% reduction in downtime, a 30% reduction in maintenance costs, an increase in asset availability to 97%, an MTBF extension of up to 511 hours, and an OEE rate of 92.1%. These findings highlight the strategic role of digital predictive maintenance in increasing competitiveness and supporting long-term sustainability in manufacturing operations.

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References

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Published

2026-04-30

How to Cite

Prayoga, I. A., & Raharjo , R. J. H. (2026). Implementasi SAP Plant Maintenance dalam Strategi Predictive Maintenance untuk Efisiensi Biaya dan Optimalisasi Kinerja Aset. Jurnal Riset Rumpun Ilmu Ekonomi, 5(1), 513–526. https://doi.org/10.55606/jurrie.v5i1.7952

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