Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time
This paper presents a framework for optimizing injection molding process parameters for minimum product cycle time subjected to constraints on the product defects. Two product defects, namely, volumetric shrinkage and warpage, as well as seven process parameters including injection speed, injection...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Polymer Technology |
| Online Access: | http://dx.doi.org/10.1155/2020/1309209 |
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| author | Saad M. S. Mukras |
| author_facet | Saad M. S. Mukras |
| author_sort | Saad M. S. Mukras |
| collection | DOAJ |
| description | This paper presents a framework for optimizing injection molding process parameters for minimum product cycle time subjected to constraints on the product defects. Two product defects, namely, volumetric shrinkage and warpage, as well as seven process parameters including injection speed, injection pressure, cooling time, packing pressure, mold temperature, packing time, and melt temperature, were considered. Injection molding experiments were conducted on specifically chosen test points and results were used to compute the volumetric shrinkage and warpage (at each test point). Thereafter, three relationships between the product cycle time (one relationship), the two product defects (two relationships), and the injection molding parameters were constructed using the kriging technique. An optimization problem to minimize the product cycle time (described by the first relationship) subject to constraints on the product defects (described by the latter two relationships) was then formulated. A combination set of points between the lower and upper extreme values of acceptable product defect was generated to serve as constraints for the two product defects. The optimization problem was then solved using the Fmincon function, available in the Matlab optimization toolbox. A plot of the optimization results revealed an appreciable tradeoff between the cycle time and the two product defects. To validate the optimization, an additional injection molding experiment was conducted for one of the optimization results. Results from the additional experiment showed reasonably close agreement with simulation optimization results differing in the cycle time, the warpage and volumetric shrinkage by 6.7%, 3.2%, and 8%, respectively. |
| format | Article |
| id | doaj-art-03a0e13b7b884d73840bc60dd2299d10 |
| institution | Kabale University |
| issn | 0730-6679 1098-2329 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Polymer Technology |
| spelling | doaj-art-03a0e13b7b884d73840bc60dd2299d102025-02-03T01:04:41ZengWileyAdvances in Polymer Technology0730-66791098-23292020-01-01202010.1155/2020/13092091309209Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle TimeSaad M. S. Mukras0Department of Mechanical Engineering, College of Engineering, Qassim University, Buraydah, Qassim, Saudi ArabiaThis paper presents a framework for optimizing injection molding process parameters for minimum product cycle time subjected to constraints on the product defects. Two product defects, namely, volumetric shrinkage and warpage, as well as seven process parameters including injection speed, injection pressure, cooling time, packing pressure, mold temperature, packing time, and melt temperature, were considered. Injection molding experiments were conducted on specifically chosen test points and results were used to compute the volumetric shrinkage and warpage (at each test point). Thereafter, three relationships between the product cycle time (one relationship), the two product defects (two relationships), and the injection molding parameters were constructed using the kriging technique. An optimization problem to minimize the product cycle time (described by the first relationship) subject to constraints on the product defects (described by the latter two relationships) was then formulated. A combination set of points between the lower and upper extreme values of acceptable product defect was generated to serve as constraints for the two product defects. The optimization problem was then solved using the Fmincon function, available in the Matlab optimization toolbox. A plot of the optimization results revealed an appreciable tradeoff between the cycle time and the two product defects. To validate the optimization, an additional injection molding experiment was conducted for one of the optimization results. Results from the additional experiment showed reasonably close agreement with simulation optimization results differing in the cycle time, the warpage and volumetric shrinkage by 6.7%, 3.2%, and 8%, respectively.http://dx.doi.org/10.1155/2020/1309209 |
| spellingShingle | Saad M. S. Mukras Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time Advances in Polymer Technology |
| title | Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time |
| title_full | Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time |
| title_fullStr | Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time |
| title_full_unstemmed | Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time |
| title_short | Experimental-Based Optimization of Injection Molding Process Parameters for Short Product Cycle Time |
| title_sort | experimental based optimization of injection molding process parameters for short product cycle time |
| url | http://dx.doi.org/10.1155/2020/1309209 |
| work_keys_str_mv | AT saadmsmukras experimentalbasedoptimizationofinjectionmoldingprocessparametersforshortproductcycletime |