An Integrated Simulation Optimisation Decision Support Tool for Multi-Product Production Systems

Alvandi, S; Li, W; Kara, S

An Integrated Simulation Optimisation Decision Support Tool for Multi-Product Production Systems

Alvandi, S

Li, W Kara, S

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Publisher:: Canadian Center of Science and Education
Publication Type:: Journal Article
Citation:: Modern Applied Science, 11, (6), pp. 56

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Field	Value	Language
dc.contributor.author	Alvandi, S https://orcid.org/0000-0002-1719-8610
dc.contributor.author	Li, W
dc.contributor.author	Kara, S
dc.date.accessioned	2025-02-19T01:18:52Z
dc.date.available	2025-02-19T01:18:52Z
dc.identifier.citation	Modern Applied Science, 11, (6), pp. 56
dc.identifier.issn	1913-1844
dc.identifier.issn	1913-1852
dc.identifier.uri	http://hdl.handle.net/10453/185188
dc.description.abstract	<jats:p>Over the past decades, the rising energy prices and imposing environmental regulations have motivated manufacturers to improve the energy efficiency of their manufacturing processes. Manufacturers need to also consider energy efficiency in addition to classical performance measures. The additional performance dimension (energy-related indicators) significantly increases the complexity of classical production planning problems (e.g. scheduling), already known as NP-hard problem).To overcome the inherited complexity, an integrated simulation-optimization framework is proposed. The proposed approach tackles scheduling problem in a multi-product/multi-machine manufacturing environment and optimizes several production objectives simultaneously. A case study is presented to demonstrate the applicability of the proposed approach in a real-life industrial facility.</jats:p>
dc.language	en
dc.publisher	Canadian Center of Science and Education
dc.relation.ispartof	Modern Applied Science
dc.relation.isbasedon	10.5539/mas.v11n6p56
dc.rights	info:eu-repo/semantics/openAccess
dc.title	An Integrated Simulation Optimisation Decision Support Tool for Multi-Product Production Systems
dc.type	Journal Article
utslib.citation.volume	11
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Professional Practice and Leadership
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2025-02-19T01:18:51Z
pubs.issue	6
pubs.publication-status	Published online
pubs.volume	11
utslib.citation.issue	6

Abstract:

Over the past decades, the rising energy prices and imposing environmental regulations have motivated manufacturers to improve the energy efficiency of their manufacturing processes. Manufacturers need to also consider energy efficiency in addition to classical performance measures. The additional performance dimension (energy-related indicators) significantly increases the complexity of classical production planning problems (e.g. scheduling), already known as NP-hard problem).To overcome the inherited complexity, an integrated simulation-optimization framework is proposed. The proposed approach tackles scheduling problem in a multi-product/multi-machine manufacturing environment and optimizes several production objectives simultaneously. A case study is presented to demonstrate the applicability of the proposed approach in a real-life industrial facility.

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http://hdl.handle.net/10453/185188