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dc.contributor.authorKonur, Savas
dc.contributor.authorLan, Yang
dc.contributor.authorThakker, Dhaval
dc.contributor.authorMokryani, Geev
dc.contributor.authorPolovina, N.
dc.contributor.authorSharp, J.
dc.date.accessioned2021-01-28T15:12:40Z
dc.date.available2021-01-28T15:12:40Z
dc.date.issued2023-11
dc.identifier.citationKonur S, Lan Y, Thakker D et al (2023) Towards design and implementation of Industry 4.0 for food manufacturing. Neural Computing and Applications. 35: 23753-23765.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18328
dc.descriptionYesen_US
dc.description.abstractToday’s factories are considered as smart ecosystems with humans, machines and devices interacting with each other for efficient manufacturing of products. Industry 4.0 is a suite of enabler technologies for such smart ecosystems that allow transformation of industrial processes. When implemented, Industry 4.0 technologies have a huge impact on efficiency, productivity and profitability of businesses. The adoption and implementation of Industry 4.0, however, require to overcome a number of practical challenges, in most cases, due to the lack of modernisation and automation in place with traditional manufacturers. This paper presents a first of its kind case study for moving a traditional food manufacturer, still using the machinery more than one hundred years old, a common occurrence for small- and medium-sized businesses, to adopt the Industry 4.0 technologies. The paper reports the challenges we have encountered during the transformation process and in the development stage. The paper also presents a smart production control system that we have developed by utilising AI, machine learning, Internet of things, big data analytics, cyber-physical systems and cloud computing technologies. The system provides novel data collection, information extraction and intelligent monitoring services, enabling improved efficiency and consistency as well as reduced operational cost. The platform has been developed in real-world settings offered by an Innovate UK-funded project and has been integrated into the company’s existing production facilities. In this way, the company has not been required to replace old machinery outright, but rather adapted the existing machinery to an entirely new way of operating. The proposed approach and the lessons outlined can benefit similar food manufacturing industries and other SME industries.en_US
dc.description.sponsorshipInnovate UK—Knowledge Transfer Partnerships (KTP010551)en_US
dc.language.isoenen_US
dc.rights© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.subjectIndustry 4.0en_US
dc.subjectSmart manufacturingen_US
dc.subjectFood manufacturingen_US
dc.subjectInternet of thingsen_US
dc.subjectArtificial intelligenceen_US
dc.subjectMachine learningen_US
dc.subjectBig dataen_US
dc.titleTowards design and implementation of Industry 4.0 for food manufacturingen_US
dc.status.refereedYesen_US
dc.date.application2021-01-25
dc.typeArticleen_US
dc.type.versionPublished versionen_US
dc.identifier.doihttps://doi.org/10.1007/s00521-021-05726-z
refterms.dateFOA2021-01-28T15:13:59Z
dc.openaccess.statusGolden_US
dc.date.accepted2021-01-08


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