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Multi-objective optimization of machining parameters in hybrid powder-mixed EDM process by response surface methodology and normalized fuzzy logic algorithm
Powder-mixed electric discharge machining (PMEDM) technique is an advanced process which is developed to overcome the setbacks of low material removal rate and low surface finish of electric discharge machining(EDM) process. In this technique, semi-conductive powders such as silicon, aluminium, chromium, manganese, etc. are mixed in the dielectric fluid which generates a conductive channel that helps to improve the material removal rate and surface finish. Each powder has certain properties which improve some of the responses but not all of them. Thus to improve major number of responses, hybrid powder mixed EDM technique is developed. In hybrid powder mixed EDM process, two or more powders are mixed together in varying proportion. In this present work, hybrid powder mixed EDM process is studied. The process parameters considered are current, pulse on time and powder proportion. The powders used are silicon, aluminum and chromium. The response variables which are investigated are material removal rate and tool wear rate. Response surface methodology of central composite design is used for design of experiments. Normalized Fuzzy algorithm is used to optimize the process parameters. Confirmation experiments are conducted to validate the results. The optimum specimen is checked for surface hardness, surface roughness, surface crack density, radial overcut and electrode wear ratio. In this paper, new and advanced technique of hybrid powder-mixed EDM process is studied and is compared with Conventional Powder-mixed EDM process and is found that Hybrid powder-mixed EDM process provide better results than Conventional and single powder-mixed EDM process.
Multi-objective optimization of machining parameters in hybrid powder-mixed EDM process by response surface methodology and normalized fuzzy logic algorithm
Powder-mixed electric discharge machining (PMEDM) technique is an advanced process which is developed to overcome the setbacks of low material removal rate and low surface finish of electric discharge machining(EDM) process. In this technique, semi-conductive powders such as silicon, aluminium, chromium, manganese, etc. are mixed in the dielectric fluid which generates a conductive channel that helps to improve the material removal rate and surface finish. Each powder has certain properties which improve some of the responses but not all of them. Thus to improve major number of responses, hybrid powder mixed EDM technique is developed. In hybrid powder mixed EDM process, two or more powders are mixed together in varying proportion. In this present work, hybrid powder mixed EDM process is studied. The process parameters considered are current, pulse on time and powder proportion. The powders used are silicon, aluminum and chromium. The response variables which are investigated are material removal rate and tool wear rate. Response surface methodology of central composite design is used for design of experiments. Normalized Fuzzy algorithm is used to optimize the process parameters. Confirmation experiments are conducted to validate the results. The optimum specimen is checked for surface hardness, surface roughness, surface crack density, radial overcut and electrode wear ratio. In this paper, new and advanced technique of hybrid powder-mixed EDM process is studied and is compared with Conventional Powder-mixed EDM process and is found that Hybrid powder-mixed EDM process provide better results than Conventional and single powder-mixed EDM process.
Multi-objective optimization of machining parameters in hybrid powder-mixed EDM process by response surface methodology and normalized fuzzy logic algorithm
Int J Interact Des Manuf
Kazi, Fahad (Autor:in) / Waghmare, C. A. (Autor:in) / Sohani, M. S. (Autor:in)
01.12.2021
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Powder mixed EDM , Hybrid powder mixed EDM , Material removal rate , Tool wear rate , Response surface methodology , Normalized Fuzzy algorithm Engineering , Engineering, general , Engineering Design , Mechanical Engineering , Computer-Aided Engineering (CAD, CAE) and Design , Electronics and Microelectronics, Instrumentation , Industrial Design
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