The optimization of accuracy and efficiency for multistage precision grinding process with an improved particle swarm optimization algorithm
| Autor: | Zhanying Chen, Xuekun Li, Zongyu Zhu, Zeming Zhao, Liping Wang, Sheng Jiang, Yiming Rong |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | International Journal of Advanced Robotic Systems, Vol 17 (2020) |
| Druh dokumentu: | article |
| ISSN: | 1729-8814 17298814 |
| DOI: | 10.1177/1729881419893508 |
| Popis: | For metal rolling, the quality of final rolled productions (for instance, metal sheets and metal foils) is affected by steel roll’s cylindricity. In roll grinding process, grinding parameters, which typically involve multiple substages, determine the steel roll’s quality and the grinding efficiency. In this article, a modified particle swarm optimization was presented to dispose of roll grinding multi-objective optimization. The minimization of steel roll’s cylindrical error and maximization of grinding efficiency were optimization objectives. To build the correlation between grinding parameters and cylindrical error, the response surface model of cylindrical error was regressed from the operation data of machine tool. The improved particle swarm optimization was employed to the roll grinding parameter optimization, and the optimal compromise solutions between grinding efficiency and cylindrical error were obtained. Based on the optimal compromise solutions, engineers or computer were capable to determine the corresponding most efficient roll grinding parameters according to the requirement of the final cylindrical error specification. To validate the efficacy of the improved particle swarm optimization, the validation experiment was carried out on the practical roll grinding operation. The error between the calculated optimized cylindrical error and experimental cylindrical error is less than 7.73%. |
| Databáze: | Directory of Open Access Journals |
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