Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm

Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation str...

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Autor principal:	Aqeel Sabree Baden
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2017
Materias:	Simulated Annealing Algorithm (SAA) Single Point Incremental Forming (SPIF) Forming Parameters Surface Roughness Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/12e8d44ef22648a496e9abd1e585351b
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spelling	oai:doaj.org-article:12e8d44ef22648a496e9abd1e585351b2021-12-02T07:32:13ZOptimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm10.22153/kej.2016.05.0051818-11712312-0789https://doaj.org/article/12e8d44ef22648a496e9abd1e585351b2017-12-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/322https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess the surface roughness of incremental forming parts along and across tool path direction. The data required has been generate, compare and evaluate to the proposed models that obtained from SPIF experiments. Simulated Annealing Algorithm (SAA) is utilized to develop an effective mathematical model to predict optimum level. In simulated algorithm (SA), an exponential cooling schedule depending on Newtonian cooling process is used and by choosing the number of iterations at each step on the experimental work is done. The SA algorithm is used to predict the forming parameters (speed, feed and step size) on surface quality in forming process of Al 1050 based on Taguchi‘s orthogonal array of L9 and (ANOVA) analysis of variance were used to find the best factors that effect on the surface quality. Aqeel Sabree BadenAl-Khwarizmi College of Engineering – University of BaghdadarticleSimulated Annealing Algorithm (SAA)Single Point Incremental Forming (SPIF)Forming ParametersSurface RoughnessChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 12, Iss 4 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Simulated Annealing Algorithm (SAA) Single Point Incremental Forming (SPIF) Forming Parameters Surface Roughness Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Simulated Annealing Algorithm (SAA) Single Point Incremental Forming (SPIF) Forming Parameters Surface Roughness Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Aqeel Sabree Baden Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
description	Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess the surface roughness of incremental forming parts along and across tool path direction. The data required has been generate, compare and evaluate to the proposed models that obtained from SPIF experiments. Simulated Annealing Algorithm (SAA) is utilized to develop an effective mathematical model to predict optimum level. In simulated algorithm (SA), an exponential cooling schedule depending on Newtonian cooling process is used and by choosing the number of iterations at each step on the experimental work is done. The SA algorithm is used to predict the forming parameters (speed, feed and step size) on surface quality in forming process of Al 1050 based on Taguchi‘s orthogonal array of L9 and (ANOVA) analysis of variance were used to find the best factors that effect on the surface quality.
format	article
author	Aqeel Sabree Baden
author_facet	Aqeel Sabree Baden
author_sort	Aqeel Sabree Baden
title	Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
title_short	Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
title_full	Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
title_fullStr	Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
title_full_unstemmed	Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
title_sort	optimization and prediction of process parameters in spif that affecting on surface quality using simulated annealing algorithm
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2017
url	https://doaj.org/article/12e8d44ef22648a496e9abd1e585351b
work_keys_str_mv	AT aqeelsabreebaden optimizationandpredictionofprocessparametersinspifthataffectingonsurfacequalityusingsimulatedannealingalgorithm
_version_	1718399321491111936

Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm

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