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Double optimization of the mesoscopic geometric parameters of ball-end milling cutters based on interactive experiment
https://orcid.org/http://orcid.org/0000-0003-3541-8362
This study is about basing on the optimized area occupied, which affects cutters’ cutting performance, the cutting performance of the tool is optimized. In order to obtain the best area to be occupied by a micro-texture for cutting performance, a micro-texture area occupancy model for a cutter's rake face was established and finite element simulation was used to analyze the influence of different degrees of micro-texture on the strength of a cutter's structure. The impact of different mesoscopic geometric parameters on the cutting performance was then analyzed. By using an SVR algorithm, the test data was optimized and the best cutter area occupancy was obtained on the basis of the TOPSIS optimization method. The mesoscopic geometric characteristic parameters were then optimized using a Genetic Algorithm. The test results showed that the placement of the micro-texture did not affect the structural strength of the cutter and the optimum area occupancy rate was 18.99%. The optimum diameter for the micro-texture was found to be 59.79 μm, with a spacing of 126.46 μm, a distance from the cutter edge of 100.20 μm, a cutter edge radius of 58.95 μm, and a micro-texture area occupancy of 18.12%. The double optimization of the characteristic parameters enabled them to mutually verify one another, facilitating the rapid design of cutters and indicating the best way of obtaining highly efficient machining for materials such as titanium alloy.
Double optimization of the mesoscopic geometric parameters of ball-end milling cutters based on interactive experiment
https://orcid.org/http://orcid.org/0000-0003-3541-8362
This study is about basing on the optimized area occupied, which affects cutters’ cutting performance, the cutting performance of the tool is optimized. In order to obtain the best area to be occupied by a micro-texture for cutting performance, a micro-texture area occupancy model for a cutter's rake face was established and finite element simulation was used to analyze the influence of different degrees of micro-texture on the strength of a cutter's structure. The impact of different mesoscopic geometric parameters on the cutting performance was then analyzed. By using an SVR algorithm, the test data was optimized and the best cutter area occupancy was obtained on the basis of the TOPSIS optimization method. The mesoscopic geometric characteristic parameters were then optimized using a Genetic Algorithm. The test results showed that the placement of the micro-texture did not affect the structural strength of the cutter and the optimum area occupancy rate was 18.99%. The optimum diameter for the micro-texture was found to be 59.79 μm, with a spacing of 126.46 μm, a distance from the cutter edge of 100.20 μm, a cutter edge radius of 58.95 μm, and a micro-texture area occupancy of 18.12%. The double optimization of the characteristic parameters enabled them to mutually verify one another, facilitating the rapid design of cutters and indicating the best way of obtaining highly efficient machining for materials such as titanium alloy.
Double optimization of the mesoscopic geometric parameters of ball-end milling cutters based on interactive experiment
https://orcid.org/http://orcid.org/0000-0003-3541-8362
This study is about basing on the optimized area occupied, which affects cutters’ cutting performance, the cutting performance of the tool is optimized. In order to obtain the best area to be occupied by a micro-texture for cutting performance, a micro-texture area occupancy model for a cutter's rake face was established and finite element simulation was used to analyze the influence of different degrees of micro-texture on the strength of a cutter's structure. The impact of different mesoscopic geometric parameters on the cutting performance was then analyzed. By using an SVR algorithm, the test data was optimized and the best cutter area occupancy was obtained on the basis of the TOPSIS optimization method. The mesoscopic geometric characteristic parameters were then optimized using a Genetic Algorithm. The test results showed that the placement of the micro-texture did not affect the structural strength of the cutter and the optimum area occupancy rate was 18.99%. The optimum diameter for the micro-texture was found to be 59.79 μm, with a spacing of 126.46 μm, a distance from the cutter edge of 100.20 μm, a cutter edge radius of 58.95 μm, and a micro-texture area occupancy of 18.12%. The double optimization of the characteristic parameters enabled them to mutually verify one another, facilitating the rapid design of cutters and indicating the best way of obtaining highly efficient machining for materials such as titanium alloy.
Double optimization of the mesoscopic geometric parameters of ball-end milling cutters based on interactive experiment
Int J Interact Des Manuf
Tong, Xin (author) / Shen, Jianing (author) / Yu, Song (author)
2022-03-01
11 pages
Article (Journal)
Electronic Resource
English
Micro-texture , Ball-end milling cutter , Area occupancy rate , Cutting performance , TOPSIS algorithm , SVR-genetic 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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