Multiple performance characteristic index optimization of dimensional accuracy and geometrical shape angle in turn-mill multitasking machining. (December 2022)

• Record Type: Journal Article
• Authors: Huang, Wei-Tai; Yang, Shih-Cheng; Ho, Wen-Hsien; Tsai, Jinn-Tsong
• Other Names: Hsieh Wen-Hsiang guest-editor.; Garza-Reyes Jose Arturo guest-editor.; Wong Pak Kin guest-editor.
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 236:Number 14(2022)
• Page Start: 1930
• Page End: 1940
• Publication Date: 2022-12
• Subjects: Turn-mill multitasking machining -- Taguchi method -- fuzzy theory -- multiple performance characteristic index; Mechanical engineering -- Periodicals; Engineering -- Management -- Periodicals; Manufacturing processes -- Periodicals; 629.8
• DOI: 10.1177/09544054211028532
• Languages: English
• ISSNs: 0954-4054

Abstract

Multiple performance objectives in turn-mill multitasking machining are investigated using the Taguchi method combined with the fuzzy theory. Using these two methods, optimized processing parameters can be rapidly identified to obtain optimized dimensional accuracy and geometrical shape angle, thus reducing machining cost and time. Herein, control factors for determining the single objective optimization parameter using the Taguchi robust process L 9 (3 4 ) orthogonal table were spindle speed (rpm), feed (mm/min), C -axis brake pressure (kg/cm 2 ), axial cutting depth (mm), with dimensional accuracy and geometrical shape angle as objective characteristics. Then, signal-to-noise ratios of different groups were generated by gray correlation according to the experimental sequence to obtain the gray correlation coefficient for the calculation of the multiple performance characteristic index (MPCI). The MPCI results demonstrated that optimized dimensional accuracy was 0.005 mm and optimized geometrical shape angle was 0.004°. The optimized MPCI parameters were A3 (4000 rpm), B3 (250 mm/min), C3 (30 kg/cm 2 ), and D3 (1.5 mm). It can reduce the processing for burr elimination and tool wear reduction by MPCI optimized process parameters.