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

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 experiments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid (PLA), polylactic acid-thermoplastic polyurethane (PLA-TPU) and polylactic acid-thermoplastic starch (PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflow® 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 L27 (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 spurious 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 minimization 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 shrinkage defects compared to the other studied compounds.