A Review of Research on Multi-Objective Process Parameter Optimization Technology for Grinding Machining.

Uložené v:
Podrobná bibliografia
Názov: A Review of Research on Multi-Objective Process Parameter Optimization Technology for Grinding Machining.
Autori: Yang, Xiao, Deng, Zhaohui, Zhu, Decai, Zhuo, Rongjin, Xu, Xipeng, Liu, Wei
Zdroj: Technologies (2227-7080); Jan2026, Vol. 14 Issue 1, p64, 32p
Predmety: MULTI-objective optimization, OPTIMIZATION algorithms, INDUSTRIAL productivity, GRINDING machines, ENERGY consumption, MECHANICAL engineering, PRODUCT quality
Abstrakt: The optimization of grinding is a multi-objective problem characterized by high dimensionality, non-linearity, and complexity. Solving this multi-objective optimization (MOO) problem is one of the most challenging tasks in the field of mechanical engineering. In-depth research on multi-objective parameter optimization technology for grinding is of great significance for improving processing efficiency, optimizing product quality, and reducing energy consumption. This paper takes the multi-objective optimization problem of grinding as its starting point. First, it introduces the basic theory of multi-objective optimization and two primary methods for solving such problems: optimization target dimension reduction and multi-objective optimization. Second, the key technologies of the two methods are reviewed, including the modeling method of the optimization problem, the multi-objective optimization algorithm for solving the optimization model, and the prior and posterior trade-off methods used to obtain the compromised optimal solutions. Finally, the existing problems of the multi-objective optimization methods in grinding processing are summarized and the future development trends are predicted. This paper aims to provide researchers with a comprehensive understanding of the multi-objective optimization technology in grinding processing, enabling them to make more reasonable decisions when dealing with actual multi-objective optimization problems. [ABSTRACT FROM AUTHOR]
Copyright of Technologies (2227-7080) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáza: Complementary Index
Buďte prvý, kto okomentuje tento záznam!
Najprv sa musíte prihlásiť.