Recent Methods for Optimization of Plastic Extrusion Process: A Literature Review

Plastic extrusion has been a challenging process for many manufacturers and researchers to produce products meeting requirements at the lowest cost. Faced with global competition in plastic-products industry, using the trial-anderror approach to determine the process parameters for plastic extrusion is no longer good enough. During production, quality characteristics may deviate due to drifting or shifting of processing conditions caused by machine wear, environmental change or operator fatigue. Determining optimal process parameter settings critically influences productivity, quality, and cost of production in the plastic related industries. The aim of this article is to review the research of the determination of process parameters and die design for plastic extrusion. Research based on various approaches, including Taguchi technique, artificial neural networks (ANN), fuzzy logic, genetic algorithms (GA), non-linear modeling, and response surface methodology are discussed.