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Diameter prediction and optimization of hot extrusion-synthesized polypropylene filament using statistical and soft computing techniques

Ong, Pauline and Choon, Sin Ho and Vui Sheng ChiG, Desmond Daniel and Chee, Kiong Sia and Chuan, Huat Ng and Wahab, Md Saidin and Bala, Abduladim Salem (2017) Diameter prediction and optimization of hot extrusion-synthesized polypropylene filament using statistical and soft computing techniques. Journal of Intelligent Manufacturing. pp. 1957-1972. ISSN 1572-8145

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Abstract

In this study, statistical and soft computing techniques were developed to investigate effect of process parameters on diameter of extruded filament made of polypropylene in hot extrusion. A multi-factors experiment was designed with process parameters of screw speed, roller speed and die temperature. According to the design matrix, twenty four experiments were conducted. The diameter of the extruded plastic filament was measured in each experiment. Subsequently, statistical analysis was used to identify significant factors on diameter of extruded filament. Predictive models of response surface methodology (RSM) and radial basis function neural network(RBFNN)were applied to predict the diameter of extruded filament. The optimal process parameters to maintain the diameter of the filament closest to the target value were identified using the cuckoo search algorithm (CSA), and particle swarm optimization (PSO). Performance analysis demonstrated the superior predictive ability of both models, in which the prediction errors of 0.0245 and 0.0029 (in terms of mean squared error) were obtained byRSM and RBFNN, respectively. Considering the optimization methods, the optimization approaches of using CSA and PSO were promising, in which average relative error of 1.28% was obtained in confirmation tests.

Item Type: Article
Uncontrolled Keywords: Cuckoo search algorithm; Hot extrusion; Optimization; Particle swarm optimization; Radial basis function neural networ;k Response surface methodology
Subjects: T Technology > T Technology (General)
Depositing User: Mr Abdul Rahim Mat Radzuan
Date Deposited: 29 Nov 2019 21:51
Last Modified: 29 Nov 2019 21:51
URI: http://eprints.uthm.edu.my/id/eprint/11980
Statistic Details: View Download Statistic

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