Surface integrity optimization of high speed dry milling UD-CF/PEEK based on specific cutting energy distribution mechanisms effected by impact and size effect. (July 2022)

• Record Type: Journal Article
• Authors: Song, Yang; Cao, Huajun; Qu, Da; Yi, Hao; Kang, Xinzhen; Huang, Xuefeng; Zhou, Jin; Yan, Chunping
• Is Part Of: Journal of manufacturing processes. Volume 79(2022)
• Page Start: 731
• Page End: 744
• Publication Date: 2022-07
• Subjects: Specific cutting energy -- Energy distribution -- Size effect -- Impact -- Optimization -- CF/PEEK; Production management -- Data processing -- Periodicals; Manufacturing processes -- Periodicals; Procestechnologie; Productietechniek; Production -- Gestion -- Informatique -- Périodiques; Fabrication -- Périodiques; Manufacturing processes; Production management -- Data processing; Periodicals; 670.5
• DOI: 10.1016/j.jmapro.2022.05.024
• Languages: English
• ISSNs: 1526-6125

Abstract

Abstract: Carbon fiber-reinforced polymer (CFRP) composites have been widely used in the aerospace industry due to their excellent mechanical properties. Cutting mechanisms of machining CFRP and its effect on machined surface integrity are still unclear due to inhomogeneity and anisotropy. To this end, this paper studied the cutting mechanisms of CFRP by establishing an impact-based Specific Cutting Energy (SCE) distribution prediction model of high speed dry (HSD) milling CFRP which is be an effective and eco-friendly cutting method. SCE is divided into five sub-SCEs affected by shearing, pressing, impacting, bouncing and delamination, respectively. Among them, sub-SCEs generated by pressing and impacting are influenced by carbon fiber distribution due to size effect and material properties, carbon fiber distribution model was introduced into the SCE prediction model. The proposed model was verified with maximum relative error 7.6%, demonstrating that impact and size effect are of great significance in revealing the cutting mechanism of CFRP. To clarify the effect of SCE distribution on surface integrity, three-dimensional (3D) arithmetic mean height and 3D fractal dimension were used to quantitative characterization of the surface integrity and sub-SCEs are diagnosed for obtaining the way of sub-SCE distribution effecting surface integrity by correlation analysis. According to SCE diagnosis, the milling parameters are optimized by removing sub-SCEs unrelated to surface integrity, founding that HSD milling can reduce machining defects.