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A methodology for multiple performances optimization of computer numerical controlled (CNC) machining process based on design of experiment, multi-criteria decision-making and multiple regression model
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A methodology for multiple performances optimization of computer numerical controlled (CNC) machining process based on design of experiment, multi-criteria decision-making and multiple regression model
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Journal Article
A methodology for multiple performances optimization of computer numerical controlled (CNC) machining process based on design of experiment, multi-criteria decision-making and multiple regression model
2025
Overview
This paper proposes multiple performances optimization methodology for computer numerical controlled (CNC) machining based on Taguchi method, multi-criteria decision-making (MCDM) and multiple regression (MR) model. It consists of the following steps: (1) setting levels of process parameters and selecting suitable Taguchi orthogonal array (OA), (2) arranging the process parameters on the OA and measuring machining performance values at every trials, (3) calculating comprehensive performance (CP) by integrating the multiple performances using a reasonable MCDM, (4) developing MR model between the CP and the process parameters, (5) analyzing influence of the process parameters based on correlation analysis, and (6) determining the optimal process parameters using grid search method. The methodology was applied to analyze and determine the influence and optimal turning process parameters such as cutting speed (CS), feed rate (FR), cutting depth (CD), cutting environment (CE) and tool nose radius (NR) for optimizing four machining performances such as surface roughness (SR), cutting force (CF), tool life (TL) and power consumption (PC) in the high speed CNC turning of AISI P20 tool steel. As the result, the optimal values of the turning process parameters were determined as CS of 160 m/min, FR of 0.1 mm/r, CD of 0.2 mm, CE of cryogenic environment, and NR of 1.1 mm. The influence analysis and optimization results of the process parameters were compared with the results obtained from the Taguchi method. The proposed methodology could be widely applied to many practical machining process optimization problems in small medium enterprise (SME) or fabrication laboratory (FabLab).
Publisher
Springer Paris,Springer Nature B.V
