Predictive Maintenance on Dry 8 Production Machine Line Using Support Vector Machine (SVM)
Predictive Maintenance pada Line Mesin Produksi Dry 8 Menggunakan Support Vector Machine (SVM)
DOI:
https://doi.org/10.21070/ups.5111Keywords:
Confusion Matrix, Machine Learning, Predictive Maintenance, Support Vector MachineAbstract
Machines are the main element in manufacturing companies, the role of machine performance is vital in the production process. Downtime problems caused by machine damage can have a major effect on company productivity. This research implements the support vector machine (SVM) method for the prediction of Dry 8 production machine line maintenance, which aims to reduce downtime and increase productivity. The SVM method is known for its high accuracy and low error rate. The evaluation process used four kernel functions: linear, radial basis function (RBF), polynomial and sigmoid. The linear kernel function showed the best performance with 99.8% accuracy, 83% precision, recall and f1-score. These results show that the SVM method can be a viable solution to improve the efficiency of machine maintenance.
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