Predicting the Warpage of Plastic Products during the Injection Molding Process using the BBM Method

Abstract

During the injection molding process, the warpage prediction plays a significant role in order to improve the quality of a product. This procedure depends on a variety of parameters, such as pressure, melting temperature, packing, and filling time. Polyethylene Terephthalate Glycol (PETG) is a thermoplastic material that exhibits a great bending attribute, heat resistance, and durability. This paper examines a method for predicting the warpage defect using the Box-Behnken Method (BBM). The mathematical model is formed to predict the warpage with high reliability, resulting in R-Sq of 97.81%, R-Sq(adj) of 95.26%, and R-Sq(pred) of 87.39%. The optimal processing parameters are a packing time of 5.5 s, a melting temperature of 270 ᵒC, an injection pressure of 217.4 MPa, and a filling time of 0.8 s. The results show that the proposed method is effective in processing engineering problems related to the prediction and optimization of manufacturing systems for improving sustainability and product quality.