'Faculty of Mechanical Engineering and Naval Architecture, Univ. of Zagreb'
Doi
Abstract
Production managers are forced to achieve higher levels of operating performance due to the complexity of today\u27s production environment. The accuracy of manufacturing facilities usually has an impact on productivity. Thus, forecasting machine performance has become an inevitable responsibility of production managers. However, the question of how managers may effectively evaluate the effectiveness of equipment remains unresolved. Although this topic has not been given much consideration in earlier studies, the production environment of today makes it significant. In order to predict the equipment effectiveness, this study proposes two different prediction models. The models are Adaptive Neuro Fuzzy Inference System (ANFIS) and hybrid firefly algorithm-adaptive neuro fuzzy inference system (FA-ANFIS). The equipment effectiveness prediction model has been developed and evaluated using a real-world case from a textile processing industry. As a result, the proposed hybrid FA-ANFIS model outperforms with a high accuracy of 99.1 percent and a low root-mean-square error (RMSE) of 0.090766. Moreover, this proposed model helps production managers in evaluating the equipment effectiveness
