Multi-objective integrated optimization of tool geometry angles and cutting parameters for machining time and energy consumption in NC milling

Zhao, Jinwen; Li, Li; Nie, Hongguang; Chen, Xingzheng; Liu, Jiwei; Shu, Xin

doi:10.1007/s00170-021-07772-2

Cited by 15 publications

(2 citation statements)

References 27 publications

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“…The genetic algorithm is a very effective method for finding optimal solutions and it is used to find optimal solutions [ 29 , 30 , 31 ]. Zhao et al employed NSGA-II to the multi-objective optimization of machining efficiency and energy consumption in CNC milling, which resulted in a reduction of energy consumption by more than eight percent and a significant improvement in machining efficiency [ 32 ]. Tian et al used a genetic algorithm to optimize the deformation of T-joint fillet welds [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

Processing Optimization of Shear Thickening Fluid Assisted Micro-Ultrasonic Machining Method for Hemispherical Mold Based on Integrated CatBoost-GA Model

et al. 2023

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Micro-electro-mechanical systems (MEMS) hemispherical resonant gyroscopes are used in a wide range of applications in defense technology, electronics, aerospace, etc. The surface roughness of the silicon micro-hemisphere concave molds (CMs) inside the MEMS hemispherical resonant gyroscope is the main factor affecting the performance of the gyroscope. Therefore, a new method for reducing the surface roughness of the micro-CM needs to be developed. Micro-ultrasonic machining (MUM) has proven to be an excellent method for machining micro-CMs; shear thickening fluids (STFs) have also been used in the ultra-precision polishing field due to their perfect processing performance. Ultimately, an STF-MUM polishing method that combines STF with MUM is proposed to improve the surface roughness of the micro-CM. In order to achieve the excellent processing performance of the new technology, a Categorical Boosting (CatBoost)-genetic algorithm (GA) optimization model was developed to optimize the processing parameters. The results of optimizing the processing parameters via the CatBoost-GA model were verified by five groups of independent repeated experiments. The maximum absolute error of CatBoost-GA is 7.21%, the average absolute error is 4.69%, and the minimum surface roughness is reduced by 28.72% compared to the minimum value of the experimental results without optimization.

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Section: Introductionmentioning

confidence: 99%

Processing Optimization of Shear Thickening Fluid Assisted Micro-Ultrasonic Machining Method for Hemispherical Mold Based on Integrated CatBoost-GA Model

et al. 2023

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“…Yang et al [9] considered machining time, cost and profit rate and then designed a multi-objective PSO method based on fuzzy global and personal optimization mechanism to solve the multi-objective optimization model. Zhao et al [10] exploited a multi-objective optimization model and solved the model using the non-dominated sorting genetic algorithm to obtain minimum machining time and minimum energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Optimization of parameters for high-quality and high-efficiency milling global process considering stability constraint

Yang

Wang

et al. 2023

Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023)

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Optimization of machining parameters has an important impact on milling efficiency and surface quality. This paper analyzes the change of milling stability with different process parameters, and constructs a 3D stability diagram. Further considering the constraints of machine tool performance, tool life and machining requirements, a multi-objective process parameter optimization model of rough and finish milling machining is established according to the different objectives of different machining stages. Secondly, the particle swarm optimization algorithm is applied to obtain the optimal solution of the model, which includes the axial cutting depth, radial cutting depth, spindle speed and feed rate per tooth in the rough and finish machining stage. Finally, the machining experiment is carried out. Compared with the experimental results based on empirical parameters, the machining time is effectively shortened and the surface quality is improved, which also demonstrate the effectiveness of the proposed method.

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Milling force prediction and optimization of process parameters in micro-milling of glow discharge polymer

Guo

Chen

Wang

et al. 2022

Int J Adv Manuf Technol

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Multi-objective integrated optimization of tool geometry angles and cutting parameters for machining time and energy consumption in NC milling

Cited by 15 publications

References 27 publications

Processing Optimization of Shear Thickening Fluid Assisted Micro-Ultrasonic Machining Method for Hemispherical Mold Based on Integrated CatBoost-GA Model

Processing Optimization of Shear Thickening Fluid Assisted Micro-Ultrasonic Machining Method for Hemispherical Mold Based on Integrated CatBoost-GA Model

Optimization of parameters for high-quality and high-efficiency milling global process considering stability constraint

Milling force prediction and optimization of process parameters in micro-milling of glow discharge polymer

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