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

Ong, Pauline and Ho, Choon Sin and Chin, Desmond Daniel Vui Sheng and Sia, Chee Kiong and Ng, Chuan Huat and Wahab, Md Saidin and Bala, Abduladim Salem (2019) Diameter prediction and optimization of hot extrusion-synthesized polypropylene filament using statistical and soft computing techniques. Journal of Intelligent Manufacturing, 30. pp. 1957-1972. ISSN 1572-8145

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Official URL: https://doi.org/10.1007/s10845-017-1365-8

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 network; Response surface methodology
Subjects:	Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions:	Faculty of Mechanical and Manufacturing Engineering > Department of Mechanical Engineering
Depositing User:	Miss Afiqah Faiqah Mohd Hafiz
Date Deposited:	02 Dec 2021 04:39
Last Modified:	02 Dec 2021 04:39
URI:	http://eprints.uthm.edu.my/id/eprint/4390

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