scholarly journals Multi-Objective Optimization of CNC Turning Process Parameters Considering Transient-Steady State Energy Consumption

2021 ◽  
Vol 13 (24) ◽  
pp. 13803
Author(s):  
Shun Jia ◽  
Shang Wang ◽  
Jingxiang Lv ◽  
Wei Cai ◽  
Na Zhang ◽  
...  

Energy-saving and emission reduction are recognized as the primary measure to tackle the problems associated with climate change, which is one of the major challenges for humanity for the forthcoming decades. Energy modeling and process parameters optimization of machining are effective and powerful ways to realize energy saving in the manufacturing industry. In order to realize high quality and low energy consumption machining of computer numerical control (CNC) lathe, a multi-objective optimization of CNC turning process parameters considering transient-steady state energy consumption is proposed. By analyzing the energy consumption characteristics in the process of machining and introducing practical constraints, such as machine tool equipment performance and tool life, a multi-objective optimization model with turning process parameters as optimization variables and high quality and low energy consumption as optimization objectives is established. The model is solved by non-dominated sorting genetic algorithm-II (NSGA-II), and the pareto optimal solution set of the model is obtained. Finally, the machining process of shaft parts is studied by CK6153i CNC lathe. The results show that 38.3% energy consumption is saved, and the surface roughness of workpiece is reduced by 47.0%, which verifies the effectiveness of the optimization method.

IARJSET ◽  
2017 ◽  
Vol 4 (6) ◽  
pp. 131-139
Author(s):  
K. Kushal Kumar ◽  
Asst. Prof. Gangadhar Biradar ◽  
Asst. Prof. MD. Ashfaq Hussain

2020 ◽  
Vol 21 ◽  
pp. 1013-1021 ◽  
Author(s):  
S.P. Palaniappan ◽  
K. Muthukumar ◽  
R.V. Sabariraj ◽  
S. Dinesh Kumar ◽  
T. Sathish

2020 ◽  
Vol 44 (4) ◽  
pp. 592-601
Author(s):  
S.R. Sundara Bharathi ◽  
D. Ravindran ◽  
A. Arul Marcel Moshi

Extensive research has been carried out to optimize the process parameters of several machining processes. Optimizing the influencing parameters of the turning operation is a precise action that determines the desired level of quality. This study focuses on the multi-criteria optimization of the CNC turning process parameters of stainless steel 303 (SS 303) material to achieve minimum surface roughness (Ra) with maximum material removal rate (MRR) by means of Taguchi-based grey relational analysis. A CNC machine was tested following Taguchi’s L9 orthogonal array design. Grey relational analysis was used as the multi-criteria optimization tool. The significance of each individual process parameter on the overall characteristics of the turned specimen was estimated using analysis of variance (ANOVA). Regression equations were generated using the input factors with the selected output parameters. In addition, a morphological study of the chips produced by the turning process was carried out using SEM images in order to relate the chip geometry with the output responses.


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