Using Support Vector Regression to Predict the Overall Equipment Effectiveness Indicator*

Abstract

This study aims to predict the performance of a company measured using the overall equipment effectiveness (OEE), considered one of the key performance indicators used to measure the performance of a manufacturing system. The prediction of the OEE indicator will be done using a supervised learning technique named: support vector regression (SVR), known for its high prediction accuracy and rapid training speed, SVR is an efficient tool in real-value function estimation. A case study is conducted on this work and the model accuracy is 87%.