Fuzzy model-based optimal energy control during the electrical discharge machining

• Published in: Neural computing & applications Vol. 32; no. 22; pp. 17011 - 17026
• Main Authors: Rodic, Dragan, Gostimirovic, Marin, Madic, Milos, Sekulic, Milenko, Aleksic, Andjelko
• Format: Journal Article
• Language: English
• Published: London Springer London 01-11-2020; Springer Nature B.V
• Subjects: Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Control systems; Data Mining and Knowledge Discovery; Design of experiments; Electric discharge machining; Energy; Fuzzy control; Fuzzy logic; Image Processing and Computer Vision; Interaction parameters; Knowledge based systems; Machine shops; Material removal rate (machining); Mathematical models; Optimal control; Original Article; Probability and Statistics in Computer Science; Pulse duration; Stability; Discharge energy; MIMO fuzzy system; Material removal rate; Optimal control; EDM
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-020-04909-4

This research aimed to describe a fuzzy optimal energy control strategy, so the electrical discharge machining (EDM) process can be optimized as a whole. The purpose is to develop a fuzzy logic-based multi-input–multi-output optimal control system to characterize the discharge energy efficiency of the EDM process. Methodology used in this paper is specific experimental design covering final and rough operations. Two controllable parameters were selected, and they were discharge current and pulse duration. The discharge energy and material removal rate were chosen as quality characteristics. The proposed approach uses the concept of fuzzy optimal control which is formulated on the basis of fuzzy logic technology with the use of knowledge-based system control. The finding that resulted in this research is that the effect of the discharge energy developed was observed on the performance of material removal rate. The material removal of the electrical discharge is directly proportional to the amount of the discharge energy applied during the on time of the pulse. The experimental results revealed that the effect of the EDM is increased as electrical discharge input parameters increase, but their interaction is limited and still somewhat unclear. The fuzzy optimal control model provides a highly advantageous option of the EDM input parameters, to achieve the best machining performance: the minimum discharge energy and the maximum material removal rate.