IMPROVE THE KINETIC PERFORMANCE OF THE PUMP CONTROLLED CLAMPING UNIT IN PLASTIC INJECTION MOLDING MACHINE WITH ADAPTIVE CONTROL STRATEGY

The kinetic characteristics of the clamping unit of plastic injection molding machine that is controlled by close loop with newly developed double speed variable pump unit are investigated. Considering the wide variation of the cylinder equivalent mass caused by the transmission ratio of clamping unit and the severe instantaneous impact force acted on the cylinder during the mold closing and opening process, an adaptive control principle of parameter and structure is proposed to improve its kinetic performance. The adaptive correlation between the acceleration feedback gain and the variable mass is derived. The pressure differential feedback is introduced to improve the dynamic performance in the case of small inertia and heavy impact load. The adaptation of sum pressure to load is used to reduce the energy loss of the system. The research results are verified by the simulation and experiment, The investigation method and the conclusions are also suitable for the differential cylinder system controlled by the traditional servo pump unit.

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 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.