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Analysis of machined surface quality for multi-feature standard parts

  • Chongjun Wu*
  • , Cong Chen
  • , Chen Li
  • , Long Wang
  • , Yanquan Geng
  • , Tangyong Zhang
  • *Corresponding author for this work
  • Donghua University
  • Aplos Machines Manufacturing (Shanghai) Co. Ltd.

Research output: Contribution to journalArticlepeer-review

Abstract

Analyzing the machined surface quality of a multi-feature part helps to find out a comprehensive solution for machining quality promotion for complex multi-feature products. It is also significant to detect the machining accuracy and performance of the machine tools. In this paper, the surface of a standard part is adopted to investigate multi-feature part machining application, which has more than 5 types of features, such as plane, bevel, curved, cylindrical, etc. Three groups of finish machining experiments with different parameters are firstly conducted to conclude the effect of features on the machined surfaces. Then, surface roughness and morphology were measured and compared for five features under the same machining parameters to reveal machined quality differences between surfaces. The effects of inclination angle and curvature on the surface quality are also theoretically analyzed. It is found that the contact area between the tool and the part varies with the inclination angle of the bevel, leading to different roughness variations. Between the plane and curved surfaces, the concave surface has the highest roughness, while the convex surface has the lowest. Moreover, the wear of four tools with different machining time is examined. It is shown that, with the increase of machining time, the tool tip wears more severely than the rake and the flank. Furthermore, the correlation between tool wear and surface roughness is also studied by regression analysis, which confirms that the quality difference of some surfaces is related to the tool wear state.

Original languageEnglish
Pages (from-to)452-465
Number of pages14
JournalJournal of Manufacturing Processes
Volume115
DOIs
StatePublished - 15 Apr 2024

Keywords

  • Machined surface quality
  • Multi-feature parts
  • Regression analysis
  • Tool wear

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