Abstract
Residual stresses can reduce the reliability of plastic injection molding parts. This work is an attempt to model the residual stresses as a function of injection molding parameters. More stress is placed on reducing the number of input factors and to include all possible interactions. For this purpose, two-stage experimentation is suggested: a factor screening stage and Response Surface optimization stage. In screening stage Taguchi 3 level experimental design is used to classify the input parameters as significant and non-significant factors. Eight input variables were classified into 3 non-significant and 5 significant factors using this screening stage. Thus for the Response Surface optimization stage: instead of doing 160 experiments in Central Composite, 56 are only needed after the screening stage in half Central Composite Design. The best subset and regression model fitting tools in addition to model verification using randomly selected input setting were used to select a model for predicting residual stresses with a verified Root Mean Square Error (RSME) of nearly 0.93 MPa.
Highlights
The plastic injection molding process is a widely used polymer processing operation [1]
This work suggests an intermediate approach that uses both advantages of two main experimentation types whereby, Taguchi Experimental Design (TED) is used for significant factor determination and Response Surface is used for modeling the process residual stresses
This study introduces an innovative method to model the residual stresses based on injection molding process settings; namely filling time, melt temperature, mold temperature, switch to pack (%), pressure holding time, holding pressure magnitude, cooling time, and cooling inlet temperature
Summary
The plastic injection molding process is a widely used polymer processing operation [1]. A widely DOE methodology is Taguchi Experimental Design (DOE), which various industries have used over the years to improve products or manufacturing processes It is a powerful and effective method to solve challenging quality problems [16]. This work suggests an intermediate approach that uses both advantages of two main experimentation types whereby, Taguchi Experimental Design (TED) is used for significant factor determination and Response Surface is used for modeling the process residual stresses. This study introduces an innovative method to model the residual stresses based on injection molding process settings; namely filling time, melt temperature, mold temperature, switch to pack (%), pressure holding time, holding pressure magnitude, cooling time, and cooling inlet temperature This method firstly, uses experiment runs based on Taguchi Orthogonal Array (OA) with only main effects of the input variables included. The number of experiments and time to design and time to customer can be reduced appreciably by this technique
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