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

E. Turanoglu Bekar, M. Cakmakci, Cengiz Kahraman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationIntelligent Systems and Decision Making for Risk Analysis and Crisis Response - Proceedings of the 4th International Conference on Risk Analysis and Crisis Response, RACR 2013
Pages229-235
Number of pages7
Publication statusPublished - 2013
Event4th International Conference on Risk Analysis and Crisis Response, RACR 2013 - Istanbul, Turkey
Duration: 27 Aug 201329 Aug 2013

Publication series

NameIntelligent Systems and Decision Making for Risk Analysis and Crisis Response - Proceedings of the 4th International Conference on Risk Analysis and Crisis Response, RACR 2013

Conference

Conference4th International Conference on Risk Analysis and Crisis Response, RACR 2013
Country/TerritoryTurkey
CityIstanbul
Period27/08/1329/08/13

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