Warpage optimization of a bus ceiling lamp base using neural network model and genetic algorithm
In this study, optimum values of process parameters in injection molding of a bus ceiling lamp base to achieve minimum warpage are determined. Mold temperature, melt temperature, packing pressure, packing pressure time and cooling time are considered as process parameters. In finding optimum values,...
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| Published in | Journal of materials processing technology Vol. 169; no. 2; pp. 314 - 319 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
10.11.2005
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0924-0136 |
| DOI | 10.1016/j.jmatprotec.2005.03.013 |
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| Abstract | In this study, optimum values of process parameters in injection molding of a bus ceiling lamp base to achieve minimum warpage are determined. Mold temperature, melt temperature, packing pressure, packing pressure time and cooling time are considered as process parameters. In finding optimum values, advantages of finite element software MoldFlow, statistical design of experiments, artificial neural network and genetic algorithm are exploited. Finite element analyses are conducted for combination of process parameters designed using statistical three-level full factorial experimental design. A predictive model for warpage is created using feed forward artificial neural network exploiting finite element analysis results. Neural network model is validated for predictive capability and then interfaced with an effective genetic algorithm to find the optimum process parameter values. Upon optimization, it is seen that genetic algorithm reduces the warpage of the initial model of the bus ceiling lamp base by 46.5%. |
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| AbstractList | In this study, optimum values of process parameters in injection molding of a bus ceiling lamp base to achieve minimum warpage are determined. Mold temperature, melt temperature, packing pressure, packing pressure time and cooling time are considered as process parameters. In finding optimum values, advantages of finite element software MoldFlow, statistical design of experiments, artificial neural network and genetic algorithm are exploited. Finite element analyses are conducted for combination of process parameters designed using statistical three-level full factorial experimental design. A predictive model for warpage is created using feed forward artificial neural network exploiting finite element analysis results. Neural network model is validated for predictive capability and then interfaced with an effective genetic algorithm to find the optimum process parameter values. Upon optimization, it is seen that genetic algorithm reduces the warpage of the initial model of the bus ceiling lamp base by 46.5%. (ABS resin.) In this study, optimum values of process parameters in injection molding of a bus ceiling lamp base to achieve minimum warpage are determined. Mold temperature, melt temperature, packing pressure, packing pressure time and cooling time are considered as process parameters. In finding optimum values, advantages of finite element software MoldFlow, statistical design of experiments, artificial neural network and genetic algorithm are exploited. Finite element analyses are conducted for combination of process parameters designed using statistical three-level full factorial experimental design. A predictive model for warpage is created using feed forward artificial neural network exploiting finite element analysis results. Neural network model is validated for predictive capability and then interfaced with an effective genetic algorithm to find the optimum process parameter values. Upon optimization, it is seen that genetic algorithm reduces the warpage of the initial model of the bus ceiling lamp base by 46.5%. |
| Author | Erzurumlu, Tuncay Ozcelik, Babur Kurtaran, Hasan |
| Author_xml | – sequence: 1 givenname: Hasan surname: Kurtaran fullname: Kurtaran, Hasan email: hasan@gyte.edu.tr – sequence: 2 givenname: Babur surname: Ozcelik fullname: Ozcelik, Babur – sequence: 3 givenname: Tuncay surname: Erzurumlu fullname: Erzurumlu, Tuncay |
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| Keywords | Finite element method Warpage Artificial neural network Genetic algorithm Plastic injection molding Optimization |
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| References_xml | – reference: Matlab User Manual, Version 6.5 R13, The Math Works Inc., 2002. – year: 1989 ident: bib11 article-title: Genetic Algorithms in Search, Optimization and Machine Learning – year: 1986 ident: bib1 article-title: Machine Design – reference: MoldFlow Plastic Insight Release 3.0, 2001. – start-page: 687 year: 2000 end-page: 692 ident: bib4 article-title: Shrinkage and warpage analysis of injection-molded parts publication-title: SPE ANTEC Tech. – year: 1987 ident: bib2 article-title: Injection and Compression Molding – volume: 110 start-page: 1 year: 2001 end-page: 9 ident: bib7 article-title: The effective factors in the warpage problem of an injection-molded part with a thin shell feature publication-title: J. Mater. Process. Technol. – volume: 34 start-page: 793 year: 1995 end-page: 811 ident: bib6 article-title: Optimization of part wall thicknesses to reduce warpage of injection-molded parts based on the modified complex method publication-title: Polym. Plast. Technol. Eng. – year: 1995 ident: bib10 article-title: Response Surface Methodology Process and Product Optimization Using Designed Experiments – volume: 20 start-page: 14 year: 2001 end-page: 21 ident: bib3 article-title: Numerical simulation of thermally induced stress and warpage in injection-molded thermoplastics publication-title: Adv. Polym. Technol. – volume: 35 start-page: 1511 year: 1995 ident: bib5 article-title: Modeling and simulation of thermally induced stress and warpage in injection molded thermoplastics publication-title: Polym. Eng. Sci. – year: 1987 ident: 10.1016/j.jmatprotec.2005.03.013_bib2 – volume: 20 start-page: 14 issue: 1 year: 2001 ident: 10.1016/j.jmatprotec.2005.03.013_bib3 article-title: Numerical simulation of thermally induced stress and warpage in injection-molded thermoplastics publication-title: Adv. Polym. Technol. doi: 10.1002/1098-2329(200121)20:1<14::AID-ADV1001>3.0.CO;2-S – start-page: 687 year: 2000 ident: 10.1016/j.jmatprotec.2005.03.013_bib4 article-title: Shrinkage and warpage analysis of injection-molded parts – ident: 10.1016/j.jmatprotec.2005.03.013_bib8 – year: 1995 ident: 10.1016/j.jmatprotec.2005.03.013_bib10 – year: 1986 ident: 10.1016/j.jmatprotec.2005.03.013_bib1 – volume: 110 start-page: 1 year: 2001 ident: 10.1016/j.jmatprotec.2005.03.013_bib7 article-title: The effective factors in the warpage problem of an injection-molded part with a thin shell feature publication-title: J. Mater. Process. Technol. doi: 10.1016/S0924-0136(00)00649-X – volume: 35 start-page: 1511 year: 1995 ident: 10.1016/j.jmatprotec.2005.03.013_bib5 article-title: Modeling and simulation of thermally induced stress and warpage in injection molded thermoplastics publication-title: Polym. Eng. Sci. – volume: 34 start-page: 793 issue: 5 year: 1995 ident: 10.1016/j.jmatprotec.2005.03.013_bib6 article-title: Optimization of part wall thicknesses to reduce warpage of injection-molded parts based on the modified complex method publication-title: Polym. Plast. Technol. Eng. doi: 10.1080/03602559508009600 – ident: 10.1016/j.jmatprotec.2005.03.013_bib9 – year: 1989 ident: 10.1016/j.jmatprotec.2005.03.013_bib11 |
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| SubjectTerms | Artificial neural network Finite element method Genetic algorithm Optimization Plastic injection molding Warpage |
| Title | Warpage optimization of a bus ceiling lamp base using neural network model and genetic algorithm |
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