Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm
The selection of the optimal metal milling parameters greatly impacts final product quality and production efficiency in modern manufacturing systems. The profit rate is also sensitive to the selected parameters. This research focuses on determining the optimal parameters of a multipass milling proc...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/8545739 |
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| _version_ | 1832562055139295232 |
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| author | Cuiyu Wang Wenwen Wang Yiping Gao Xinyu Li |
| author_facet | Cuiyu Wang Wenwen Wang Yiping Gao Xinyu Li |
| author_sort | Cuiyu Wang |
| collection | DOAJ |
| description | The selection of the optimal metal milling parameters greatly impacts final product quality and production efficiency in modern manufacturing systems. The profit rate is also sensitive to the selected parameters. This research focuses on determining the optimal parameters of a multipass milling process using an improved particle swarm optimization (PSO) method. The objective is to minimize the production time. The proper number of passes, the optimal cut speed, and feed rate are considered as the parameters (the decision variables in the model) which are needed to be optimized. Furthermore, the permissive arbor strength, arbor deflection, and motor power are the constraints of the model. The penalty function method is used as the constraints handling technique to address the constraints efficiently in the proposed method. A case is adopted and solved to evaluate the performance of the proposed method. The experimental part is analyzed and compared with advanced methods. Experimental results show that the proposed method is very effective for parameters optimization of a multipass milling process and outperforms other methods. |
| format | Article |
| id | doaj-art-76e39f308f4f4769a4d79c744fa80df3 |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-76e39f308f4f4769a4d79c744fa80df32025-02-03T01:23:34ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/8545739Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization AlgorithmCuiyu Wang0Wenwen Wang1Yiping Gao2Xinyu Li3School of Mechanical Science and EngineeringSchool of Mechanical Science and EngineeringSchool of Mechanical Science and EngineeringSchool of Mechanical Science and EngineeringThe selection of the optimal metal milling parameters greatly impacts final product quality and production efficiency in modern manufacturing systems. The profit rate is also sensitive to the selected parameters. This research focuses on determining the optimal parameters of a multipass milling process using an improved particle swarm optimization (PSO) method. The objective is to minimize the production time. The proper number of passes, the optimal cut speed, and feed rate are considered as the parameters (the decision variables in the model) which are needed to be optimized. Furthermore, the permissive arbor strength, arbor deflection, and motor power are the constraints of the model. The penalty function method is used as the constraints handling technique to address the constraints efficiently in the proposed method. A case is adopted and solved to evaluate the performance of the proposed method. The experimental part is analyzed and compared with advanced methods. Experimental results show that the proposed method is very effective for parameters optimization of a multipass milling process and outperforms other methods.http://dx.doi.org/10.1155/2022/8545739 |
| spellingShingle | Cuiyu Wang Wenwen Wang Yiping Gao Xinyu Li Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm Discrete Dynamics in Nature and Society |
| title | Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm |
| title_full | Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm |
| title_fullStr | Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm |
| title_full_unstemmed | Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm |
| title_short | Parameters Optimization of Multipass Milling Process by an Effective Modified Particle Swarm Optimization Algorithm |
| title_sort | parameters optimization of multipass milling process by an effective modified particle swarm optimization algorithm |
| url | http://dx.doi.org/10.1155/2022/8545739 |
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