An ANFIS model for forecasting risk by Overall Equipment Effectiveness parameter in Total Productive Maintenance

In this study, Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to obtain forecasted results for Overall Equipment Effectiveness (OEE) parameter in Total Productive Maintenance (TPM) through some predetermined inputs such as availability, performance efficiency and rate of quality. Triangular type of membership functions was determined as low, medium, and high for each input parameter in the ANFIS model. This study is important to forecast the risk by OEE in the TPM. With the predicted results of OEE performance an appropriate maintenance strategy can be developed and the production can be improved. This can also help reducing the risk level of breakdowns or failures at any critical equipment. © 2013 Taylor & Francis Group.