Machining process modeling and optimization are two major issues in manufacturing processes. The process modeling and optimization techniques are vital to meet increasing quality demand (high quality, low cost and environmental friendliness) in manufacturing practice. The machining process for a computer numerical controlled (CNC) machine is programmed by process parameters such as cutting speed, feed rate and cutting depth. Traditional trial and error method for determining the machining process parameters based on experience cannot guarantee the optimal machining performance for CNC machines.
Many previous studies on machining processes have applied different modeling, integrating and optimization methods. However, they may have considerable inconsistent and conflicting results, which is one of the drawbacks to be overcome in manufacturing practice.
Ryang Si Ho, a section head at the Faculty of Mechanical Science and Technology, has proposed a multiple performances optimization methodology for computer numerical controlled (CNC) machining based on Taguchi method, multi-criteria decision-making (MCDM) and multiple regression (MR) model.
The proposed method 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 trial, (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 the influence of process parameters based on correlation analysis, and (6) determining the optimal process parameters using grid search method.
In order to verify the effectiveness of the proposed method, he applied it to analysis and determination of 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.
For more information, please refer to his paper “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” in “International Journal on Interactive Design and Manufacturing” (SCI).
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