Design evaluation of disk-type milling cutter with special inserts applying analytical simulation and the experimental verification in screw rotor milling

Arifin, Achmad; Wu, Yuh-Renn; Andrianto, Moeso

doi:10.1016/j.mechmachtheory.2022.105128

Cited by 5 publications

(1 citation statement)

References 33 publications

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“…Therefore, there is a pressing need to develop a fast, e cient, and accurate tool edge design method. Ari n et al [3] investigated the design of a non-standard disc milling tool for machining screw rotors, considering the curvature of the tool edge and validating it through experiments. MU et al [4] proposed tooth surface shaping method based on the tool edge design and the principles of differential geometry theory and gear meshing, substantiating it using nite element analysis.…”

Section: Introductionmentioning

confidence: 99%

Research on cutting tool edge geometry design based on SVR-PSO

Jiang,

Huang,

Tian

et al. 2024

Int J Adv Manuf Technol

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In order to optimize the design of tool edge, an intelligent method was used for modeling and optimization. The tool edge design method based on Support Vector Regression (SVR) and Particle Swarm Optimization (PSO) was proposed. By combining tool edge parameters and processing condition parameters, and learning from empirical data, a functional model was established between tool life, edge parameters, and processing condition parameters. Taking the tool life as the objective function, the optimal edge pro le design parameters were solved under different processing condition parameters. The T-shape tool validates was taken as a case for veri cation. The SVR-PSO function model was established and solved based on the processing condition parameters, and the optimized edge design parameters and predicted tool life were obtained. The results showed that the deviation between the calculated and actual tool life was less than 6.4%. This method was feasible and practical, and has been applied in the design department of tool manufacturing companies.

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Section: Introductionmentioning

confidence: 99%