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Optimization of Low-Carbon and Highly Efficient Turning Production Equipment Selection Based on Beetle Antennae Search Algorithm (BAS).

Authors :
Xiao, Yongmao
Chen, Guohua
Zhang, Hao
Zhu, Xiaoyong
Source :
Processes; Mar2023, Vol. 11 Issue 3, p911, 17p
Publication Year :
2023

Abstract

Reducing carbon emission and raising efficient production are the important goals of modern enterprise production process. The same product can be produced by a variety of equipment, and the carbon emissions and processing time of different equipment vary greatly. Choosing suitable production equipment is an important method for manufacturing enterprises to achieve the efficient emission reduction of production process. However, the traditional production equipment selection mode only gives qualitative results, and it is difficult to provide effective advice for enterprises to choose suitable equipment under the needs of carbon neutrality. To solve this problem, this paper systematically analyzes carbon emission and the time of the turning production process, and a unified calculation model for carbon emission and efficient production of multi-type processing equipment is established. The important point of the article is to research the diversity among between carbon emissions and efficiency levels of the same product produced by different devices. The carbon emissions and efficiency levels of different kinds of equipment can be calculated by the BAS algorithm. By turning a shaft part as an example, the results show that this method can calculate the optimal value of carbon emissions and efficiency of the same product produced by different equipment and can provide suggestions for enterprises to select appropriate equipment for low-carbon and efficient production. This paper provides a reference for further research on the quantitative calculation model for the selection of high-efficiency and low-carbon production equipment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22279717
Volume :
11
Issue :
3
Database :
Complementary Index
Journal :
Processes
Publication Type :
Academic Journal
Accession number :
162809761
Full Text :
https://doi.org/10.3390/pr11030911