An intelligent fuzzy approach for controlling electrochemical machining in computer based concurrent engineering environment engineering environment
Morteza Sadegh Amalnik
Electrochemical machining (ECM) uses electrical energy to remove material. An electrolytic cell is created in an electrolyte medium, with the tool as the cathode and the workpiece as the anode. A high-amperage, low-voltage current is used to dissolve the metal and to remove it from the work piece, which must be electrically conductive. Material is removed from the work piece and the flowing electrolyte solution washes the ions away. These ions form metal hydroxides which are removed from the electrolyte solution by centrifugal separation. Both the electrolyte and the metal sludge are then recycled. Unlike traditional cutting methods, work piece hardness is not a factor, making ECM suitable for difficult-to-machine materials. Recent developments, new trends and the effect of key factors influencing the quality of the holes produced by ECM processes. Researchers developed of a fuzzy logic controller to add intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An experimental ECM drilling, was improved through the integration of a fuzzy logic controller into the existing control system. Matlab (Fuzzy Logic Toolbox) was used to build a fuzzy logic controller system, which controls the feed rate of the tool and the flow rate of the electrolyte. The objective of the fuzzy logic controller was to improve machining performance and accuracy by controlling the ECM process variables. The results serve to introduce innovative possibilities and provide potential for future applications of fuzzy logic control (FLC) in ECM. Hybrid controllers that integrate fuzzy logic into the control system allow for "human like" decision-making intelligence to be incorporated into ECM controllers.
Morteza Sadegh Amalnik. An intelligent fuzzy approach for controlling electrochemical machining in computer based concurrent engineering environment engineering environment. International Journal of Advanced Engineering and Technology, Volume 1, Issue 2, 2017, Pages 06-12