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Machining nickel – iron alloy using tungsten cutting tool and its process parameter optimization using Adam – Gene genetic algorithm
https://orcid.org/http://orcid.org/0000-0002-2441-5329
The machining nickel – iron base alloy is still a challenging process for the past few decades due to their indigenous properties. The nickel – iron alloys are hard and high strength material possess higher mechanical properties. The selection of cutting tool and the process parameters is another tough task to fix in the machining studies. In this paper, tungsten carbide cutting tool is used to machine the alloy by varying the cutting velocity (50,100 and 150 m/min), feedrate (0.075,0.1,0.125 mm/rev) and depth of cut (0.1, 0.2, 0.3 mm). From the analysis the tool wear and machining time are calculated. It has been noticed that the slow speed machining can produce less wear and high-speed machining may consume less time for the process. In addition, from the statistical analysis the feedrate has major contribution with flank wear and cutting velocity has major contribution for time. Considering the tool wear as major problem a single objective function is derived to optimise the process condition using Adam – Gene Algorithm. Based on the optimization suggestions and recommendations are made for the proposed design of experiments.
Machining nickel – iron alloy using tungsten cutting tool and its process parameter optimization using Adam – Gene genetic algorithm
https://orcid.org/http://orcid.org/0000-0002-2441-5329
The machining nickel – iron base alloy is still a challenging process for the past few decades due to their indigenous properties. The nickel – iron alloys are hard and high strength material possess higher mechanical properties. The selection of cutting tool and the process parameters is another tough task to fix in the machining studies. In this paper, tungsten carbide cutting tool is used to machine the alloy by varying the cutting velocity (50,100 and 150 m/min), feedrate (0.075,0.1,0.125 mm/rev) and depth of cut (0.1, 0.2, 0.3 mm). From the analysis the tool wear and machining time are calculated. It has been noticed that the slow speed machining can produce less wear and high-speed machining may consume less time for the process. In addition, from the statistical analysis the feedrate has major contribution with flank wear and cutting velocity has major contribution for time. Considering the tool wear as major problem a single objective function is derived to optimise the process condition using Adam – Gene Algorithm. Based on the optimization suggestions and recommendations are made for the proposed design of experiments.
Machining nickel – iron alloy using tungsten cutting tool and its process parameter optimization using Adam – Gene genetic algorithm
https://orcid.org/http://orcid.org/0000-0002-2441-5329
The machining nickel – iron base alloy is still a challenging process for the past few decades due to their indigenous properties. The nickel – iron alloys are hard and high strength material possess higher mechanical properties. The selection of cutting tool and the process parameters is another tough task to fix in the machining studies. In this paper, tungsten carbide cutting tool is used to machine the alloy by varying the cutting velocity (50,100 and 150 m/min), feedrate (0.075,0.1,0.125 mm/rev) and depth of cut (0.1, 0.2, 0.3 mm). From the analysis the tool wear and machining time are calculated. It has been noticed that the slow speed machining can produce less wear and high-speed machining may consume less time for the process. In addition, from the statistical analysis the feedrate has major contribution with flank wear and cutting velocity has major contribution for time. Considering the tool wear as major problem a single objective function is derived to optimise the process condition using Adam – Gene Algorithm. Based on the optimization suggestions and recommendations are made for the proposed design of experiments.
Machining nickel – iron alloy using tungsten cutting tool and its process parameter optimization using Adam – Gene genetic algorithm
Int J Interact Des Manuf
Nadeem, Mohammed (author) / Jani, S. P. (author) / Reddy, Kunduru Rakesh (author) / Kumar, P. Senthil (author) / Gupta, Manish (author)
2024-07-01
8 pages
Article (Journal)
Electronic Resource
English
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