Multi-Objective Optimization of Cutting Parameters in Turning AISI 304 Austenitic Stainless Steel

Metals

Guoyong Zhao¹  Chunxiao Li¹  Yugang Zhao¹  Jianbing Meng¹  Yu Su¹ 

[1] School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China;

关键词: aisi 304 austenitic stainless steel;    multi-objective optimization;    cutting parameters;    specific energy consumption;    grey relational analysis;    response surface methodology (rsm);   

DOI  :  10.3390/met10020217

来源: DOAJ

【 摘 要 】

Energy conservation and emission reduction is an essential consideration in sustainable manufacturing. However, the traditional optimization of cutting parameters mostly focuses on machining cost, surface quality, and cutting force, ignoring the influence of cutting parameters on energy consumption in cutting process. This paper presents a multi-objective optimization method of cutting parameters based on grey relational analysis and response surface methodology (RSM), which is applied to turn AISI 304 austenitic stainless steel in order to improve cutting quality and production rate while reducing energy consumption. Firstly, Taguchi method was used to design the turning experiments. Secondly, the multi-objective optimization problem was converted into a simple objective optimization problem through grey relational analysis. Finally, the regression model based on RSM for grey relational grade was developed and the optimal combination of turning parameters (a_p = 2.2 mm, f = 0.15 mm/rev, and v = 90 m/s) was determined. Compared with the initial turning parameters, surface roughness (Ra) decreases 66.90%, material removal rate (MRR) increases 8.82%, and specific energy consumption (SEC) simultaneously decreases 81.46%. As such, the proposed optimization method realizes the trade-offs between cutting quality, production rate and energy consumption, and may provide useful guides on turning parameters formulation.

【 授权许可】

Unknown