Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316

The machinability of stainless steel has attracted considerable interest because of its medium strength, low carbon and corrosion resistance. Cutting fluids that are oil-based are unsustainable as the machining process has an environmental impact. Dry machining is a sustainable solution that reduces...

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Main Author:	Bagaber, Salem Salah Abdullah
Format:	Thesis
Language:	English
Published:	2019
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/30007/1/Energy%20and%20cost%20integration%20model%20for%20multi-objective%20optimisation%20in%20turning%20process.pdf
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spelling	my-ump-ir.300072020-11-23T04:18:20Z Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316 2019-08 Bagaber, Salem Salah Abdullah TJ Mechanical engineering and machinery The machinability of stainless steel has attracted considerable interest because of its medium strength, low carbon and corrosion resistance. Cutting fluids that are oil-based are unsustainable as the machining process has an environmental impact. Dry machining is a sustainable solution that reduces both energy consumption and machining cost. This study aims to optimize an integrated mathematical model for both energy and cost in the turning process of stainless steel 316 (SS316). It is set out to optimize power consumption, machining cost and the traditional machining responses of surface roughness and tool wear by adjusting machining parameters. Stainless steel 316 was turned with different cutting tool types of uncoated carbide and coated tools. Three factors are associated with cutting parameters, namely cutting speed, feed rate, and depth of cut. Analysis of variance and the regression model was used to analyze the machining parameters and responses. A multi-objective optimization method was employed to optimize machining parameters in terms of energy and cost models. With a simulation in Design Expert and Matlab, the multi-response optimization problems were solved with a response surface methodology (RSM) and non-dominated sorting genetic algorithm (NSGA II), as well as integration between them. Results indicated that the minimum power consumption was obtained at the lowest cutting speed value and at the greatest values of feed rate and depth of cut, which contributed 37.43% and 20.5%, respectively. Surface roughness was minimized when feed rate and depth of cut were at their lowest levels, whereas the cutting speed was the most significant factor on tool wear, with a contribution of 39%, followed by depth of cut at 14.3%, although there was no influence by feed rate. Results also showed an improvement in power consumption under dry conditions, at 6.78%, whereas machining cost was better by 11.89% and there was acceptable quality compared to flood conditions. For the RSM method, the desirability value (0.885) and the minimum value of responses can be achieved at a cutting speed of 110 m/min, feed rate of 0.192 mm/rev, and 0.8 mm for depth of cut. This parameter combination results in an energy saving of 9.2% and reduced machining cost of 4.6%. For the integrated (RSM-NSGA II) method, the optimum objective values are 0.57-3.84 kWh and RM 8.94-9.78 for dry and flood, respectively. The results showed an improvement in energy saving of 14.94%, surface roughness of 4.71%, tool wear of 13.98%, and decreased machining cost of 4.6%. A three-confirmation method was used to validate the optimum point. Moreover, the second-generation results of optimization using NSGA II showed an improvement of more than 70% compared with that of RSM optimization. Therefore, this method also effectively reduces the effects and costs of the machining process and preserves the environment, which results in an overall enhancement of sustainable machining. 2019-08 Thesis http://umpir.ump.edu.my/id/eprint/30007/ http://umpir.ump.edu.my/id/eprint/30007/1/Energy%20and%20cost%20integration%20model%20for%20multi-objective%20optimisation%20in%20turning%20process.pdf pdf en public phd doctoral Universiti Malaysia Pahang Faculty of Mechanical and Manufacturing Engineering
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Bagaber, Salem Salah Abdullah Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
description	The machinability of stainless steel has attracted considerable interest because of its medium strength, low carbon and corrosion resistance. Cutting fluids that are oil-based are unsustainable as the machining process has an environmental impact. Dry machining is a sustainable solution that reduces both energy consumption and machining cost. This study aims to optimize an integrated mathematical model for both energy and cost in the turning process of stainless steel 316 (SS316). It is set out to optimize power consumption, machining cost and the traditional machining responses of surface roughness and tool wear by adjusting machining parameters. Stainless steel 316 was turned with different cutting tool types of uncoated carbide and coated tools. Three factors are associated with cutting parameters, namely cutting speed, feed rate, and depth of cut. Analysis of variance and the regression model was used to analyze the machining parameters and responses. A multi-objective optimization method was employed to optimize machining parameters in terms of energy and cost models. With a simulation in Design Expert and Matlab, the multi-response optimization problems were solved with a response surface methodology (RSM) and non-dominated sorting genetic algorithm (NSGA II), as well as integration between them. Results indicated that the minimum power consumption was obtained at the lowest cutting speed value and at the greatest values of feed rate and depth of cut, which contributed 37.43% and 20.5%, respectively. Surface roughness was minimized when feed rate and depth of cut were at their lowest levels, whereas the cutting speed was the most significant factor on tool wear, with a contribution of 39%, followed by depth of cut at 14.3%, although there was no influence by feed rate. Results also showed an improvement in power consumption under dry conditions, at 6.78%, whereas machining cost was better by 11.89% and there was acceptable quality compared to flood conditions. For the RSM method, the desirability value (0.885) and the minimum value of responses can be achieved at a cutting speed of 110 m/min, feed rate of 0.192 mm/rev, and 0.8 mm for depth of cut. This parameter combination results in an energy saving of 9.2% and reduced machining cost of 4.6%. For the integrated (RSM-NSGA II) method, the optimum objective values are 0.57-3.84 kWh and RM 8.94-9.78 for dry and flood, respectively. The results showed an improvement in energy saving of 14.94%, surface roughness of 4.71%, tool wear of 13.98%, and decreased machining cost of 4.6%. A three-confirmation method was used to validate the optimum point. Moreover, the second-generation results of optimization using NSGA II showed an improvement of more than 70% compared with that of RSM optimization. Therefore, this method also effectively reduces the effects and costs of the machining process and preserves the environment, which results in an overall enhancement of sustainable machining.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Bagaber, Salem Salah Abdullah
author_facet	Bagaber, Salem Salah Abdullah
author_sort	Bagaber, Salem Salah Abdullah
title	Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
title_short	Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
title_full	Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
title_fullStr	Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
title_full_unstemmed	Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
title_sort	energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Mechanical and Manufacturing Engineering
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/30007/1/Energy%20and%20cost%20integration%20model%20for%20multi-objective%20optimisation%20in%20turning%20process.pdf
_version_	1783732128849068032

Energy and cost integration model for multi-objective optimisation in turning process of stainless steel 316

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