Warpage and Shrinkage Optimization of Injection-Molded Plastic Spoon Parts for Biodegradable Polymers Using Taguchi, ANOVA and Artificial Neural Network Methods  被引量:28

Warpage and Shrinkage Optimization of Injection-Molded Plastic Spoon Parts for Biodegradable Polymers Using Taguchi, ANOVA and Artificial Neural Network Methods

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作  者:Erfan Oliaei Behzad Shiroud Heidari Seyed Mohammad Davachi Mozhgan Bahrami Saeed Davoodi Iman Hejazi Javad Seyfi 

机构地区:[1]Applied Science Nano Research Group, ASNARKA, P.C. 1619948753, Tehran, Iran [2]Macromolecular Science and Engineering University of Michigan, Ann Arbor, Michigan 48109-2136. United States [3]Department of Chemical Engineering, Shahrood Branch, Islamic Azad University, RO. Box 36155-163, Shahrood, lran

出  处:《Journal of Materials Science & Technology》2016年第8期710-720,共11页材料科学技术(英文版)

摘  要:In this study, it is attempted to give an insight into the injection processability of three self-prepared polymers from A to Z. This work presents material analysis, injection molding simulation, design of ex- periments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid (PLA), polylactic acid-thermoplastic poly- urethane (PLA-TPU) and polylactic acid-thermoplastic starch (PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflov~~ in order to minimize warpage and volumetric shrinkage for each of the mentioned systems. The analysis was conducted by changing five significant processing parameters, including coolant temperature, packing time, packing pressure, mold temperature and melt temperature. Taguchi's [.27 (35) orthogonal array was selected as an efficient method for design of simulations in order to consider the interaction effects of the parameters and reduce spu- rious simulations. Meanwhile, artificial neural network (ANN) was also used for pattern recognition and optimization through modifying the processing conditions. The Taguchi coupled analysis of variance (ANOVA) and ANN analysis resulted in definition of optimum levels for each factor by two completely different methods. According to the results, melting temperature, coolant temperature and packing time had significant influence on the shrinkage and warpage. The ANN optimal level selection for minimiza- tion of shrinkage and/or warpage is in good agreement with ANOVA optimal level selection results. This investigation indicates that PLA-TPU compound exhibits the highest resistance to warpage and shrink- age defects compared to the other studied compounds.In this study, it is attempted to give an insight into the injection processability of three self-prepared polymers from A to Z. This work presents material analysis, injection molding simulation, design of ex- periments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid (PLA), polylactic acid-thermoplastic poly- urethane (PLA-TPU) and polylactic acid-thermoplastic starch (PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflov~~ in order to minimize warpage and volumetric shrinkage for each of the mentioned systems. The analysis was conducted by changing five significant processing parameters, including coolant temperature, packing time, packing pressure, mold temperature and melt temperature. Taguchi's [.27 (35) orthogonal array was selected as an efficient method for design of simulations in order to consider the interaction effects of the parameters and reduce spu- rious simulations. Meanwhile, artificial neural network (ANN) was also used for pattern recognition and optimization through modifying the processing conditions. The Taguchi coupled analysis of variance (ANOVA) and ANN analysis resulted in definition of optimum levels for each factor by two completely different methods. According to the results, melting temperature, coolant temperature and packing time had significant influence on the shrinkage and warpage. The ANN optimal level selection for minimiza- tion of shrinkage and/or warpage is in good agreement with ANOVA optimal level selection results. This investigation indicates that PLA-TPU compound exhibits the highest resistance to warpage and shrink- age defects compared to the other studied compounds.

关 键 词:Injection molding simulation Yaguchi Artificial neural networks Biodegradable plastic Disposable spoons 

分 类 号:TQ320.662[化学工程—合成树脂塑料工业]

 

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