Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/55857
Title: Optimizing Plastic Extrusion Process via Grey Wolf Optimizer Algorithm and Regression Analysis
Authors: Karaoglan, Aslan Deniz
Keywords: Artificial intelligence;Nature inspired algorithms;Optimization;Plastic cub production
Issue Date: Jan-2021
Publisher: NISCAIR-CSIR, India
Abstract: One of the most widely used methods in the production of plastic products is the extrusion process. There are many factors that affect the product quality throughout the extrusion process. Examining the effects of these factors and determining the optimum process parameters which will provide the desired product characteristics; is important for reducing costs and increasing competitiveness. This study is performed in a manufacturer that produces plastic cups. The aim is to optimize extrusion process parameters of this company in order to achieve 1.15 mm thickness at the produced plastic sheets. For this reason, in order to be able to model the problem as an optimization problem through regression modelling, the thicknesses of the sheet generated with different process parameters were observed during the production processes. Then, considering the desired 1.15 mm sheet thickness, the established model is optimized by running the grey wolf optimizer (GWO) algorithm through the model.
Page(s): 34-41
URI: http://nopr.niscair.res.in/handle/123456789/55857
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.80(01) [January 2021]

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