Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—Injection molding provides a convenient approach for manufacturing plastic components with a complex geometry. However, polymer melt is a non-Newtonian fluid with a shear thinning characteristic, and hence its viscosity is highly sensitive to such factors as the shear rate, melt temperature, back pressure, and screw rotational speed during the plasticizing stage. In practical injection molding operations, process variations may have a significant effect on the melt quality, and hence on the quality of the final molded part. As a result, online melt quality monitoring systems are of great practical importance. Accordingly, this study presents a banausic method for monitoring the shot-by-shot variance of the melt quality online using a system of pressure sensors. The feasibility of the proposed method is demonstrated by detecting variations in the melt quality of two acrylonitrile butadiene styrene (ABS) materials with different melt flow indices.
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