Low-Carbon Optimization Design of Grinding Machine Spindle Based on Improved Whale Algorithm

Qi Lu, Xubo Gao and Felix T. S. Chan ()
Additional contact information
Qi Lu: School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Xubo Gao: School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
Felix T. S. Chan: School of Business, Macau University of Science and Technology, Macau, China

Mathematics, 2023, vol. 12, issue 1, 1-19

Abstract: To achieve a fundamental reduction in the carbon emissions associated with grinding machines, it is imperative to systematically explore low-carbon considerations in the design phase. The spindle is a significant contributor to carbon emissions in grinding machines, and an effective approach for reducing carbon emissions is the structural optimization of the spindle. Most of the current optimization methods aim at improving processability without considering the reduction of carbon emissions. In this context, the present study addresses the issue of carbon emissions within the spindle design phase. Initially, the determination of the spindle’s carbon emissions function and the selection of the optimization objective were undertaken. The structural factors that have a significant influence on the optimization objective were identified as optimization variables. Subsequently, the optimization objective function was established through the application of the fitting method. Finally, the proposed model was refined through the utilization of an enhanced whale algorithm. The findings indicate an 8.22% reduction in carbon emissions associated with the spindle, accompanied by marginal enhancements in both static and dynamic spindle performance. The concluding section of this paper deliberates on the impact of structural parameters on the specified objectives, thereby providing insights for the optimal design of the spindle.

Keywords: low-carbon design; spindle; static and dynamic performance; structural optimization; improved whale algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/1/69/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/1/69/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2023:i:1:p:69-:d:1307097

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().