Engineering optimisation of process parameters for polymers: an overview
by Anuja Agrawal; Raminder Kaur; R.S. Walia
International Journal of Experimental Design and Process Optimisation (IJEDPO), Vol. 6, No. 2, 2019

Abstract: Polymers are one of the most extensively used materials in the manufacturing industry. Modified to the requirement or specification for a particular application, a variety of methods may be used in processing these materials. To fulfil the requirement of the application and improve the performance of end product, an optimal combination of process parameters is required. This may be achieved through optimisation, a promising tool, which provides better performance at a reduced cost. By employing a suitable optimisation technique, the properties of polymers can be predicted without performing experiments, which would be very beneficial in terms of time and money saving by preserving materials normally consumed during the experimental optimisation phase. In this study, different optimisation techniques such as genetic algorithm (GA), artificial neural network (ANN), particle swarm optimisation (PSO), Taguchi method and others, which have been used to optimise the process parameters in polymers, are discussed in detail. In addition, the detailed algorithm and mathematical expressions used to apply these optimisation techniques have also been presented.

Online publication date: Tue, 13-Aug-2019

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