A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System
In this study, the assembly behavior for two injected components made by a family mold system were investigated. Specifically, a feasible method was proposed to evaluate the characteristic length of two components within a family mold system using numerical simulation and experimental validation. Re...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Polymers |
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| Online Access: | https://www.mdpi.com/2073-4360/13/18/3065 |
| _version_ | 1797517498956906496 |
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| author | Chao-Tsai Huang Tsai-Wen Lin Wen-Ren Jong Shia-Chung Chen |
| author_facet | Chao-Tsai Huang Tsai-Wen Lin Wen-Ren Jong Shia-Chung Chen |
| author_sort | Chao-Tsai Huang |
| collection | DOAJ |
| description | In this study, the assembly behavior for two injected components made by a family mold system were investigated. Specifically, a feasible method was proposed to evaluate the characteristic length of two components within a family mold system using numerical simulation and experimental validation. Results show that as the packing pressure increases, the product index (characteristic length) becomes worse. This tendency was consistent for both the simulation prediction and experimental observation. However, for the same operation condition setting through a basic test, there were some differences in the product index between the simulation prediction and experimental observation. Specifically, the product index difference of the experimental observation was 1.65 times over that of the simulation prediction. To realize that difference between simulation and experiment, a driving force index (DFI) based on the injection pressure history curve was proposed. Through the DFI investigation, the internal driving force of the experimental system was shown to be 1.59 times over that of the simulation. The DFI was further used as the basis for machine calibration. Furthermore, after finishing machine calibration, the integrated CAE and DOE (called CAE-DOE) strategy can optimize the ease of assembly up to 20%. The result was validated by experimental observation. |
| first_indexed | 2024-03-10T07:16:27Z |
| format | Article |
| id | doaj.art-7352e9aef59b4981a92c5ca7b94e7670 |
| institution | Directory Open Access Journal |
| issn | 2073-4360 |
| language | English |
| last_indexed | 2024-03-10T07:16:27Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Polymers |
| spelling | doaj.art-7352e9aef59b4981a92c5ca7b94e76702023-11-22T14:55:31ZengMDPI AGPolymers2073-43602021-09-011318306510.3390/polym13183065A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold SystemChao-Tsai Huang0Tsai-Wen Lin1Wen-Ren Jong2Shia-Chung Chen3Department of Chemical and Materials Engineering, Tamkang University, New Taipei City 25137, TaiwanDepartment of Chemical and Materials Engineering, Tamkang University, New Taipei City 25137, TaiwanDepartment of Mechanical Engineering, Chung Yung Christian University, Taoyuan City 32023, TaiwanDepartment of Mechanical Engineering, Chung Yung Christian University, Taoyuan City 32023, TaiwanIn this study, the assembly behavior for two injected components made by a family mold system were investigated. Specifically, a feasible method was proposed to evaluate the characteristic length of two components within a family mold system using numerical simulation and experimental validation. Results show that as the packing pressure increases, the product index (characteristic length) becomes worse. This tendency was consistent for both the simulation prediction and experimental observation. However, for the same operation condition setting through a basic test, there were some differences in the product index between the simulation prediction and experimental observation. Specifically, the product index difference of the experimental observation was 1.65 times over that of the simulation prediction. To realize that difference between simulation and experiment, a driving force index (DFI) based on the injection pressure history curve was proposed. Through the DFI investigation, the internal driving force of the experimental system was shown to be 1.59 times over that of the simulation. The DFI was further used as the basis for machine calibration. Furthermore, after finishing machine calibration, the integrated CAE and DOE (called CAE-DOE) strategy can optimize the ease of assembly up to 20%. The result was validated by experimental observation.https://www.mdpi.com/2073-4360/13/18/3065injection moldingdegree of assemblya family mold systemCAE-DOE optimization |
| spellingShingle | Chao-Tsai Huang Tsai-Wen Lin Wen-Ren Jong Shia-Chung Chen A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System Polymers injection molding degree of assembly a family mold system CAE-DOE optimization |
| title | A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System |
| title_full | A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System |
| title_fullStr | A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System |
| title_full_unstemmed | A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System |
| title_short | A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System |
| title_sort | methodology to predict and optimize ease of assembly for injected parts in a family mold system |
| topic | injection molding degree of assembly a family mold system CAE-DOE optimization |
| url | https://www.mdpi.com/2073-4360/13/18/3065 |
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