A novel hybrid ICA-ANFIS model for prediction of manufacturing processes performance

作者：Baseri Hamid^*; Belali Owsia Moosa

来源：Proceedings of the Institution of Mechanical Engineers Part E-Journal of Process Mechanical Engineering, 2017, 231(2): 181-190.

DOI：10.1177/0954408915585256

• Combined algorithm
• imperialistic competitive algorithm
• adaptive neuro-fuzzy inference system
• optimization

In order to reduce the manufacturing process variability and improve the production yield, it is important to predict the performance of manufacturing process. The adaptive neuro-fuzzy inference system (ANFIS) is a powerful network which can predict the output parameters of manufacturing process. However, design of ANFIS needs trial and errors to select the best structure. In this study, an imperialistic competitive algorithm has been used to determine the ANFIS architecture to reach minimum values of the prediction error. In order to evaluate the performance of this combined method, two illustrative examples of manufacturing processes have been used. Results indicated that the combined method has superiority in prediction of output, rather than previous developed ANFIS models and so it can be applied for modeling of the other manufacturing processes.

• 出版日期2017-4