Optimization of process parameters of injection moldings for plastic pallets manufacturing industry
Plastics have been heavily used in industries like automobile, manufacturing, electrical and electronics industry all over the world. Injection molding is one of the ways to process plastics polymers. However, one of the difficulties they have to face is to set the optimal parameter for the injectio...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Penerbit UMP
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/24769/ http://umpir.ump.edu.my/id/eprint/24769/ http://umpir.ump.edu.my/id/eprint/24769/7/Optimization%20of%20Process%20Parameters%20of%20Injection%20Moldings%20for%20Plastic%20Pallets.pdf |
| Summary: | Plastics have been heavily used in industries like automobile, manufacturing, electrical and electronics industry all over the world. Injection molding is one of the ways to process plastics polymers. However, one of the difficulties they have to face is to set the optimal parameter for the injection molding process. Incorrect parameter selection can lead to parts defects such as warpage, shrinkage, sink marks, weld marks and so on. In this study, the optimal process parameter of injection molding for manufacturing of plastic pallets which is used for warehousing was determined by the orthogonal array of Taguchi’s L9 which has 3 factors and 3 levels for each factor, experimental design, and Regression Analysis. The three main parameters such as Mold temperature, holding pressure and charging speed were choosen to study their effect on the Compressive strength. S/N ratios were utilized for determining the optimal set of parameters. According to the results, 230 °C of mold temperature, 98 RPM of charging speed, 25 MPa of Holding pressure make the products in the shape and proportion of the product satisfactory. Statically the most significant parameters were found to be as mold temperature and Charging speed for the Polypropylene moldings, respectively. Holding pressure had the least effect on the compressive strength of PP material. After the degree of significance of the studied process parameters was determined, the linear Regression model was generated and was shown to be an effective predictive tool for Compressive strength. |
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