SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0

Production lines form the backbone of a manufacturing plant while the warehouse is the heart that pumps the supplies through logistics veins. However, logistics issues among manufacturing industries are well known for causing downstream production problems. Non-transparent warehouse operation and in...

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Autores principales:	Ng Sokchoo, Tai Vin Cent, Tan Yong Chai, Abd Rahman Nor Faiza
Formato:	article
Lenguaje:	EN FR
Publicado:	EDP Sciences 2021
Materias:	Social Sciences H
Acceso en línea:	https://doaj.org/article/36c558a722944b809b84008bf6fd80ce
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spelling	oai:doaj.org-article:36c558a722944b809b84008bf6fd80ce2021-12-02T17:15:22ZSFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.02261-242410.1051/shsconf/202112410002https://doaj.org/article/36c558a722944b809b84008bf6fd80ce2021-01-01T00:00:00Zhttps://www.shs-conferences.org/articles/shsconf/pdf/2021/35/shsconf_icmesh2020_10002.pdfhttps://doaj.org/toc/2261-2424Production lines form the backbone of a manufacturing plant while the warehouse is the heart that pumps the supplies through logistics veins. However, logistics issues among manufacturing industries are well known for causing downstream production problems. Non-transparent warehouse operation and inevitable human error in logistics activities seriously jeopardise the entire downstream manufacturing processes. Existing warehouse management solutions require many sensors spanning the warehouse for tracking logistics activities which are cost-ineffective and inflexible. One aspect of intelligent WMS that has not been explored is the integration of computer vision modeling with Artificial Intelligence (AI) to create a more flexible, transparent, and autonomous warehouse management system (WMS). This study aims to devise a Smart and Flexible WMS (SFlex-WMS) to improve logistics operations in terms of operation costs, process time, and space utilisation. The highlight of the proposed framework is the two major work packages (WP) which focus on flexible, autonomous sensing mechanisms for inventory, logistics tracking, and space mapping, as well as reconstructing the warehouse environment model that reflects all physical changes in the warehouse. SFlex-WMS intends to realize real-time transparent monitoring of warehouse operations. By exploiting the outputs from both WPs, SFlex-WMS is expected to achieve more effective and flexible warehouse operations.Ng SokchooTai Vin CentTan Yong ChaiAbd Rahman Nor FaizaEDP SciencesarticleSocial SciencesHENFRSHS Web of Conferences, Vol 124, p 10002 (2021)
institution	DOAJ
collection	DOAJ
language	EN FR
topic	Social Sciences H
spellingShingle	Social Sciences H Ng Sokchoo Tai Vin Cent Tan Yong Chai Abd Rahman Nor Faiza SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0
description	Production lines form the backbone of a manufacturing plant while the warehouse is the heart that pumps the supplies through logistics veins. However, logistics issues among manufacturing industries are well known for causing downstream production problems. Non-transparent warehouse operation and inevitable human error in logistics activities seriously jeopardise the entire downstream manufacturing processes. Existing warehouse management solutions require many sensors spanning the warehouse for tracking logistics activities which are cost-ineffective and inflexible. One aspect of intelligent WMS that has not been explored is the integration of computer vision modeling with Artificial Intelligence (AI) to create a more flexible, transparent, and autonomous warehouse management system (WMS). This study aims to devise a Smart and Flexible WMS (SFlex-WMS) to improve logistics operations in terms of operation costs, process time, and space utilisation. The highlight of the proposed framework is the two major work packages (WP) which focus on flexible, autonomous sensing mechanisms for inventory, logistics tracking, and space mapping, as well as reconstructing the warehouse environment model that reflects all physical changes in the warehouse. SFlex-WMS intends to realize real-time transparent monitoring of warehouse operations. By exploiting the outputs from both WPs, SFlex-WMS is expected to achieve more effective and flexible warehouse operations.
format	article
author	Ng Sokchoo Tai Vin Cent Tan Yong Chai Abd Rahman Nor Faiza
author_facet	Ng Sokchoo Tai Vin Cent Tan Yong Chai Abd Rahman Nor Faiza
author_sort	Ng Sokchoo
title	SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0
title_short	SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0
title_full	SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0
title_fullStr	SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0
title_full_unstemmed	SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0
title_sort	sflex-wms: a novel multi-expert system for flexible logistics and warehouse operation in the context of industry 4.0
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/36c558a722944b809b84008bf6fd80ce
work_keys_str_mv	AT ngsokchoo sflexwmsanovelmultiexpertsystemforflexiblelogisticsandwarehouseoperationinthecontextofindustry40 AT taivincent sflexwmsanovelmultiexpertsystemforflexiblelogisticsandwarehouseoperationinthecontextofindustry40 AT tanyongchai sflexwmsanovelmultiexpertsystemforflexiblelogisticsandwarehouseoperationinthecontextofindustry40 AT abdrahmannorfaiza sflexwmsanovelmultiexpertsystemforflexiblelogisticsandwarehouseoperationinthecontextofindustry40
_version_	1718381254071549952

SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0

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