Adaptive production control system for a flexible manufacturing cell using support vector machine-based approach

Real-time adaptive production control in the flexible manufacturing cell (FMC) is a complex issue that needs to be addressed to realize good performance and high productivity. In this paper, we have considered a support vector machine (SVM)-based simulation approach to resolve a production control problem in an FMC that operates in a dynamic environment. A SVM-based simulation approach chooses the most relevant scheduling rule out of several predefined ones on the basis of the current states of the system. This paper examines and compares the performance of the SVM-based simulation approach with the competent scheduling rules under two different operational environments which are characterized by the uncertainty of demand. We have also developed a Visual Basic-based simulation approach for scheduling of component parts in the context of FMC under different situations. The SVM methodology to control the production offers better performance than the single-rule-based production control system.