Predictive Maintenance on Batching Plant Machines Using Support Vector Machine (SVM)
Predictive Maintenance pada Mesin Batching Plant Menggunakan Support Vector Machine (SVM)
DOI:
https://doi.org/10.21070/ups.4756Keywords:
Predictive Maintenance, Support Vector Machine, pyhtonAbstract
The escalating demand for enhanced productivity and the integration of advanced technology through machinery usage have led to a growing necessity for maintenance operations. PT. XYZ, a manufacturer of ready mix concrete, is currently facing challenges related to production machinery experiencing excessive engine loads, resulting in operational downtime and process delays, consequently diminishing machine performance. The primary objective of this investigation is to anticipate the occurrence of machinery failures in order to establish a suitable periodic maintenance schedule. The chosen approach for this study involves the application of the Support Vector Machine algorithm, which is executed using the Python programming language. This predictive analysis aims to enhance machine efficiency and performance by forecasting potential damages or malfunctions that could manifest in the future. Where this SVM can predict accurate breakdowns and optimize maintenance schedules proactively at the right time.
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