Transactions of FAMENA, Vol. 46 No. 3, 2022.
Original scientific paper
https://doi.org/10.21278/TOF.463042822
Forecasting the Equipment Effectiveness in Total Productive Maintenance Using an Intelligent Hybrid Conceptual Model
A Sivakumar
; Kongu Engineering College, Department of Mechanical Engineering, Tamil Nadu, India
S Saravanakumar
orcid.org/0000-0001-8342-8632
; Thirumagal Polytechnic College, Department of Mechanical Engineering, Tamil Nadu, India
P Sathiamurthi
; Kongu Engineering College, Department of Mechanical Engineering, Tamil Nadu, India
K S KarthiVinith
; Kongu Engineering College, Department of Automobile Engineering, Tamil Nadu, India
Abstract
Production managers are forced to achieve higher levels of operating performance due to the complexity of today's 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.
Keywords
decision support; equipment effectiveness; predictive analysis; firefly algorithm; ANFIS
Hrčak ID:
283973
URI
Publication date:
20.10.2022.
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