Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches

Ong, Pauline and Vui, Desmond Daniel Sheng Chin and Choon, Sin Ho and Chuan, Huat Ng (2018) Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches. Neural Computing and Applications, 29. pp. 1077-1087. ISSN 0941-0643

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Abstract

Obtaining the optimal extrusion process parameters by integration of optimization techniques was crucial and continuous engineering task in which it attempted to minimize the tool load. The tool load should be minimized as higher extrusion forces required greater capacity and energy. It may lead to increase the chance of part defects, die wear and die breakage. Besides, optimization may help to save the time and cost of producing the final product, in addition to produce better formability of work material and better quality of the finishing product. In this regard, this study aimed to determine the optimal extrusion process parameters. The minimization of punch load was the main concern, in such a way that the structurally sound product at minimum load can be achieved. Minimization of punch load during the extrusion process was first formulated as a nonlinear programming model using response surface methodology in this study. The established extrusion force model was then taken as the fitness function. Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. Performance assessment demonstrated the promising results of all presented techniques in minimizing the tool loading. The CSA, however, gave more persistent optimization results, which was validated through statistical analysis

Item Type:	Article
Uncontrolled Keywords:	Cold forward extrusion; Cuckoo search algorithm; Flower pollination algorithm; Optimization; Particle swarm optimization; Response surface methodology
Subjects:	T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures > TS200-770 Metal manufactures. Metalworking
Divisions:	Faculty of Mechanical and Manufacturing Engineering > Department of Mechanical Engineering
Depositing User:	UiTM Student Praktikal
Date Deposited:	17 Jan 2022 01:34
Last Modified:	17 Jan 2022 01:34
URI:	http://eprints.uthm.edu.my/id/eprint/5562

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