Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process

This paper aims to improve a sustainable cutting process through the integration of energy and cost modeling. The solution is based on the multi-objective optimisation of cutting parameters, including cutting speed, feed rate and cutting depth, based energy, cost and quality processes. The modeling...

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Main Authors:	Bagaber, Salem Abdullah, A. R., Yusoff
Format:	Article
Language:	English
Published:	Elsevier Ltd 2018
Subjects:	TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/24053/ http://umpir.ump.edu.my/id/eprint/24053/ http://umpir.ump.edu.my/id/eprint/24053/ http://umpir.ump.edu.my/id/eprint/24053/1/Energy%20and%20Cost%20Integration%20for%20Multi-Objective1.pdf

id	ump-24053
recordtype	eprints
spelling	ump-240532019-10-15T08:01:03Z http://umpir.ump.edu.my/id/eprint/24053/ Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process Bagaber, Salem Abdullah A. R., Yusoff TS Manufactures This paper aims to improve a sustainable cutting process through the integration of energy and cost modeling. The solution is based on the multi-objective optimisation of cutting parameters, including cutting speed, feed rate and cutting depth, based energy, cost and quality processes. The modeling approach has several notable merits, namely direct energy and indirect energy consumption calculation; a machining cost model for all machining tools including energy cost, production operation cost, cutting tool cost, and cutting fluid cost (dry and wet). Quality is represented by surface roughness. The multi-objective optimisation using Response Surface Methodology (RSM) was compared with the Non-Sorted Genetic Algorithm II (NSGA II) before experimental confirmation tests were made. From the multi-objective optimisation it was found that energy saved can be 9.2% and machining cost can be reduced by 4.6% using RSM. Moreover, the second-generation results of optimisation using NSGA II showed an improvement of more than 70% compared to RSM optimisation. A two-confirmation method validated the optimum point and dry cutting showed lower energy and cost with acceptable quality compared to wet conditions. The model proposed in this study is effective in terms of machining energy, cost and environment so as to be integrated with the sustainable machining. Elsevier Ltd 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24053/1/Energy%20and%20Cost%20Integration%20for%20Multi-Objective1.pdf Bagaber, Salem Abdullah and A. R., Yusoff (2018) Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process. Measurement. pp. 1-35. ISSN 0263-2241 (In Press) https://doi.org/10.1016/j.measurement.2018.12.096 https://doi.org/10.1016/j.measurement.2018.12.096
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TS Manufactures
spellingShingle	TS Manufactures Bagaber, Salem Abdullah A. R., Yusoff Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
description	This paper aims to improve a sustainable cutting process through the integration of energy and cost modeling. The solution is based on the multi-objective optimisation of cutting parameters, including cutting speed, feed rate and cutting depth, based energy, cost and quality processes. The modeling approach has several notable merits, namely direct energy and indirect energy consumption calculation; a machining cost model for all machining tools including energy cost, production operation cost, cutting tool cost, and cutting fluid cost (dry and wet). Quality is represented by surface roughness. The multi-objective optimisation using Response Surface Methodology (RSM) was compared with the Non-Sorted Genetic Algorithm II (NSGA II) before experimental confirmation tests were made. From the multi-objective optimisation it was found that energy saved can be 9.2% and machining cost can be reduced by 4.6% using RSM. Moreover, the second-generation results of optimisation using NSGA II showed an improvement of more than 70% compared to RSM optimisation. A two-confirmation method validated the optimum point and dry cutting showed lower energy and cost with acceptable quality compared to wet conditions. The model proposed in this study is effective in terms of machining energy, cost and environment so as to be integrated with the sustainable machining.
format	Article
author	Bagaber, Salem Abdullah A. R., Yusoff
author_facet	Bagaber, Salem Abdullah A. R., Yusoff
author_sort	Bagaber, Salem Abdullah
title	Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
title_short	Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
title_full	Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
title_fullStr	Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
title_full_unstemmed	Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process
title_sort	energy and cost integration for multi-objective optimisation in a sustainable turning process
publisher	Elsevier Ltd
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/24053/ http://umpir.ump.edu.my/id/eprint/24053/ http://umpir.ump.edu.my/id/eprint/24053/ http://umpir.ump.edu.my/id/eprint/24053/1/Energy%20and%20Cost%20Integration%20for%20Multi-Objective1.pdf
first_indexed	2023-09-18T22:36:14Z
last_indexed	2023-09-18T22:36:14Z
_version_	1777416614172426240

Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process

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