Production Control Process using Integrated Robust Data Envelopment Analysis and Fuzzy Neural Network

Abstract

Considering the importance of the quality and responsiveness of manufacturing companies to customers, the most important principle can be considered to be the reduction of the cycle time of the production process. Because in the real world due to measurement errors and inaccuracies of information and the uncertainty of processes the concept Fuzzy is used. Therefore, in this study, the parameters for controlling the process of forming are optimized to reduce the cycle time. Since the optimization of an aspect of quality may modify other aspects, so, to overcome this problem, the multi-response method (Taguchi MRT) has been developed. Also, integrated fuzzy-neural network and data envelopment analysis is used for optimization and analysis purposes. Experimental results are done to measure the effectiveness of this approach in a manufacturing company in Iran.