Optimization method for rough-finish milling allowance based on depth control of milling affected layer

Hongmin Xin, Maiming Dong, Chao Xian, Qingsi Cheng, Hui Dai, Changfeng Yao, Minchao Cui, Xingtong Li

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The optimization of machining allowance has an important influence on the machining quality of workpieces. This paper determined an optimization method for rough-finish milling allowance based on depth control of milling affected layer. Firstly, the coupling influence of rough-finish milling cutting depth on milling affected layer depth was studied by experiment. Secondly, the influence rule of rough milling and finish milling on the affected layer depth was studied by experiment, and the prediction model of the milling affected layer depth based on the cutting depth of rough milling and finish milling was established, as well as the surface roughness prediction model of the finish milling cutting depth. Finally, the effectiveness of the optimization results was verified by experiments. The experimental results show the optimized machining parameters can increase the machining efficiency by 31.2%, and the milling affected layer is 91 μm, which indicates that the depth of milling affected layer is effectively controlled.

Original languageEnglish
Pages (from-to)2083-2095
Number of pages13
JournalInternational Journal of Advanced Manufacturing Technology
Volume126
Issue number5-6
DOIs
StatePublished - May 2023

Keywords

  • Depth control of milling affected layer
  • Influence rule
  • Optimization method
  • Prediction model

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