Analysis of CNC Lathe Environment with Multi-Performance Characteristics

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Research areas:
Year:
2015
Type of Publication:
Article
Keywords:
Analysis, CNC Machine, Multi Performance, Tool Wear
Authors:
Anas Zaidi; Imtiaz Ali Khan
Journal:
IJAIM
Volume:
4
Number:
3
Pages:
95-99
Month:
November
Abstract:
This work addresses an approach based on the Taguchi method with grey relational analysis for optimizing dry CNC turning process with multi-performance characteristics using EN19 steel as the work piece material. Tool wear and spindle loading are the multi-performance characteristics on the basis of which the machining parameters, spindle speed, feed rate, and depth of cut, are optimized through this study. The experimental layout is designed based on Taguchi’s L16 orthogonal array and analysis of variance (ANOVA) is used to determine the effect of the machining parameters on individual responses and the grey relational grade as well. The simultaneous optimization is done by grey relational analysis approach. The optimization of complicated multi-performance characteristics is simplified through this approach. Four levels of each machining parameter are selected and experiments are done on Model PTC 600, CNC lathe machine tool of PRAGA. The optimum condition for the multi-performance characteristics is obtained at speed of 900 rpm (level 1), feed of 0.23 mm/rev (level 4) and depth of cut of 1.25 mm (level 4). MINITAB-15 software is used to perform design analysis. Main effects plots are used to determine the optimal value for individual responses. Signal-to-noise ratio plots are used to verify the results obtained from main effects plots and also to identify the significant rank’s.
Full text: IJAIM_492_Final.pdf

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