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Article: Mass Personalisation as a Service in Industry 4.0: A Resilient Response Case Study

TitleMass Personalisation as a Service in Industry 4.0: A Resilient Response Case Study
Authors
KeywordsIndustry 4.0
Internet of Things
Cloud Manufacturing
Additive Manufacturing
Personalisation
Issue Date2021
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/aei
Citation
Advanced Engineering Informatics, 2021, v. 50, p. article no. 101438 How to Cite?
AbstractThe Fourth Industrial Revolution (Industry 4.0) leads to mass personalisation as an emerging manufacturing paradigm. Mass personalisation focuses on uniquely made products to individuals at scale. Global challenges encourage mass personalisation manufacturing with efficiency competitive to mass production. Driven by individualisation as a trend and enabled by increasing digitalisation, mass personalisation can go beyond today’s mass customisation. This paper aims to introduce Mass Personalisation as a Service (MPaaS) to address unique and complex requirements at scale by harnessing Industry 4.0 technologies, including Internet of Things, Additive Manufacturing, Big Data, Cloud Manufacturing, Digital Twin, and Blockchain. A case study for the implementation of MPaaS in personalised face masks is presented. The workforce with constant exposure to contaminants requires personal protective equipment (PPE), such as facemasks, for longer hours resulting in pressure-related ulcers. This prolonged use of PPE highlights the importance of personalisation to avoid ulcers and other related health concerns. Most studies have used Additive Manufacturing for individualisation and cloud capabilities for large-scale manufacturing. This study develops a framework and mathematical model to demonstrate the capability of the proposed solution to address one of the most critical challenges by making personalised face masks as an essential PPE in the critical industrial environment.
Persistent Identifierhttp://hdl.handle.net/10722/308202
ISSN
2023 Impact Factor: 8.0
2023 SCImago Journal Rankings: 1.731
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorAheleroff, S-
dc.contributor.authorMostashiri, N-
dc.contributor.authorXu, X-
dc.contributor.authorZhong, RY-
dc.date.accessioned2021-11-12T13:43:55Z-
dc.date.available2021-11-12T13:43:55Z-
dc.date.issued2021-
dc.identifier.citationAdvanced Engineering Informatics, 2021, v. 50, p. article no. 101438-
dc.identifier.issn1474-0346-
dc.identifier.urihttp://hdl.handle.net/10722/308202-
dc.description.abstractThe Fourth Industrial Revolution (Industry 4.0) leads to mass personalisation as an emerging manufacturing paradigm. Mass personalisation focuses on uniquely made products to individuals at scale. Global challenges encourage mass personalisation manufacturing with efficiency competitive to mass production. Driven by individualisation as a trend and enabled by increasing digitalisation, mass personalisation can go beyond today’s mass customisation. This paper aims to introduce Mass Personalisation as a Service (MPaaS) to address unique and complex requirements at scale by harnessing Industry 4.0 technologies, including Internet of Things, Additive Manufacturing, Big Data, Cloud Manufacturing, Digital Twin, and Blockchain. A case study for the implementation of MPaaS in personalised face masks is presented. The workforce with constant exposure to contaminants requires personal protective equipment (PPE), such as facemasks, for longer hours resulting in pressure-related ulcers. This prolonged use of PPE highlights the importance of personalisation to avoid ulcers and other related health concerns. Most studies have used Additive Manufacturing for individualisation and cloud capabilities for large-scale manufacturing. This study develops a framework and mathematical model to demonstrate the capability of the proposed solution to address one of the most critical challenges by making personalised face masks as an essential PPE in the critical industrial environment.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/aei-
dc.relation.ispartofAdvanced Engineering Informatics-
dc.subjectIndustry 4.0-
dc.subjectInternet of Things-
dc.subjectCloud Manufacturing-
dc.subjectAdditive Manufacturing-
dc.subjectPersonalisation-
dc.titleMass Personalisation as a Service in Industry 4.0: A Resilient Response Case Study-
dc.typeArticle-
dc.identifier.emailZhong, RY: zhongzry@hku.hk-
dc.identifier.authorityZhong, RY=rp02116-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.aei.2021.101438-
dc.identifier.scopuseid_2-s2.0-85117715271-
dc.identifier.hkuros329676-
dc.identifier.volume50-
dc.identifier.spagearticle no. 101438-
dc.identifier.epagearticle no. 101438-
dc.identifier.isiWOS:000711640000001-
dc.publisher.placeUnited Kingdom-

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