Optimization of machining process route for internal joint parts using artificial fish swarm algorithm
This paper addresses the issue of low processing efficiency resulting from the intricate process of an internal joint component. To this end, it proposes an optimization of the processing route for the component through the implementation of an artificial fish swarm algorithm based on the existing p...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The Japan Society of Mechanical Engineers
2025-03-01
|
| Series: | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/jamdsm/19/1/19_2025jamdsm0009/_pdf/-char/en |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849767150251671552 |
|---|---|
| author | Jun HAN Junwei ZHU Yang ZHANG Zhenyao ZHAO Zexi AN |
| author_facet | Jun HAN Junwei ZHU Yang ZHANG Zhenyao ZHAO Zexi AN |
| author_sort | Jun HAN |
| collection | DOAJ |
| description | This paper addresses the issue of low processing efficiency resulting from the intricate process of an internal joint component. To this end, it proposes an optimization of the processing route for the component through the implementation of an artificial fish swarm algorithm based on the existing process route. In accordance with the characteristics of the part, the processing element is meticulously delineated, a prudent processing element code is formulated, the adjacent processing elements of the same category are consolidated, and the process constraints of the part are scrutinized before and after the merger. A reasonable constraint matrix model is constructed. The objective function is to determine the minimum number of machine tool, cutting tool, and clamping type changes. The design of prey, swarm, and follow behavioral parameters is conducted in a reasonable manner, as is the optimization and adjustment of the algorithm. By comparing and verifying the pre-optimization and post-optimization process solutions, the study shows that the combined optimized solution reduces the total number of machine tool changes, tool changes, and clamping changes by 43.8% and reduces the total machining time by 7 minutes and 16 seconds, which is more efficient and reasonable. |
| format | Article |
| id | doaj-art-8a10d613a474452c9d070047a9448709 |
| institution | DOAJ |
| issn | 1881-3054 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | The Japan Society of Mechanical Engineers |
| record_format | Article |
| series | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
| spelling | doaj-art-8a10d613a474452c9d070047a94487092025-08-20T03:04:20ZengThe Japan Society of Mechanical EngineersJournal of Advanced Mechanical Design, Systems, and Manufacturing1881-30542025-03-01191JAMDSM0009JAMDSM000910.1299/jamdsm.2025jamdsm0009jamdsmOptimization of machining process route for internal joint parts using artificial fish swarm algorithmJun HAN0Junwei ZHU1Yang ZHANG2Zhenyao ZHAO3Zexi AN4College of Mechanical Engineering, Inner Mongolia University of Science and TechnologyCollege of Mechanical Engineering, Inner Mongolia University of Science and TechnologyCollege of Mechanical Engineering, Inner Mongolia University of Science and TechnologyCollege of Mechanical Engineering, Inner Mongolia University of Science and TechnologyCollege of Mechanical Engineering, Inner Mongolia University of Science and TechnologyThis paper addresses the issue of low processing efficiency resulting from the intricate process of an internal joint component. To this end, it proposes an optimization of the processing route for the component through the implementation of an artificial fish swarm algorithm based on the existing process route. In accordance with the characteristics of the part, the processing element is meticulously delineated, a prudent processing element code is formulated, the adjacent processing elements of the same category are consolidated, and the process constraints of the part are scrutinized before and after the merger. A reasonable constraint matrix model is constructed. The objective function is to determine the minimum number of machine tool, cutting tool, and clamping type changes. The design of prey, swarm, and follow behavioral parameters is conducted in a reasonable manner, as is the optimization and adjustment of the algorithm. By comparing and verifying the pre-optimization and post-optimization process solutions, the study shows that the combined optimized solution reduces the total number of machine tool changes, tool changes, and clamping changes by 43.8% and reduces the total machining time by 7 minutes and 16 seconds, which is more efficient and reasonable.https://www.jstage.jst.go.jp/article/jamdsm/19/1/19_2025jamdsm0009/_pdf/-char/enmanufacturing featuremanufacturing step cellconstraint matrixprocess optimizationartificial fish swarm algorithm |
| spellingShingle | Jun HAN Junwei ZHU Yang ZHANG Zhenyao ZHAO Zexi AN Optimization of machining process route for internal joint parts using artificial fish swarm algorithm Journal of Advanced Mechanical Design, Systems, and Manufacturing manufacturing feature manufacturing step cell constraint matrix process optimization artificial fish swarm algorithm |
| title | Optimization of machining process route for internal joint parts using artificial fish swarm algorithm |
| title_full | Optimization of machining process route for internal joint parts using artificial fish swarm algorithm |
| title_fullStr | Optimization of machining process route for internal joint parts using artificial fish swarm algorithm |
| title_full_unstemmed | Optimization of machining process route for internal joint parts using artificial fish swarm algorithm |
| title_short | Optimization of machining process route for internal joint parts using artificial fish swarm algorithm |
| title_sort | optimization of machining process route for internal joint parts using artificial fish swarm algorithm |
| topic | manufacturing feature manufacturing step cell constraint matrix process optimization artificial fish swarm algorithm |
| url | https://www.jstage.jst.go.jp/article/jamdsm/19/1/19_2025jamdsm0009/_pdf/-char/en |
| work_keys_str_mv | AT junhan optimizationofmachiningprocessrouteforinternaljointpartsusingartificialfishswarmalgorithm AT junweizhu optimizationofmachiningprocessrouteforinternaljointpartsusingartificialfishswarmalgorithm AT yangzhang optimizationofmachiningprocessrouteforinternaljointpartsusingartificialfishswarmalgorithm AT zhenyaozhao optimizationofmachiningprocessrouteforinternaljointpartsusingartificialfishswarmalgorithm AT zexian optimizationofmachiningprocessrouteforinternaljointpartsusingartificialfishswarmalgorithm |