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Artificial intelligence applied to the stone manufacturing industry: A systematic literature review

2025-12Journal article Open access
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datacite.subject.fosEngenharia e Tecnologia
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorSantos Silva, Alexandre
dc.contributor.authorAntunes, Carolina
dc.contributor.authorMiragaia, Rolando
dc.contributor.authorCosta, Rogério Luís C.
dc.contributor.authorSilva, Fernando
dc.contributor.authorRibeiro, José
dc.date.accessioned2025-11-05T10:42:59Z
dc.date.available2025-11-05T10:42:59Z
dc.date.issued2025-12
dc.descriptionArticle number - 110702
dc.description.abstractNatural stone has long been used in construction, as its properties provide functional and visual value, and the natural stone market currently holds significant importance in the global economy. It is important to consider integrating new technologies in the production chain to aid the industry in moving forward, increasing profit margins and reducing wasted material. This article reviews recent trends in using Artificial Intelligence and Machine Learning techniques in the industry between 2017 and 2024, following a methodology for Systematic Literature Reviews in computer science. It was found that extensive research has been conducted on the subject of tile classification, with solid solutions proposed, achieving results that can be considered robust enough for industrial application. Other subjects comprise tasks regarding stone cutting and defect detection, as well as variable prediction, and quarry activity monitoring. Some authors propose solutions to integrate new technologies into the complete production chain. While more research needs to be done on specific subjects, this review provides a solid first step to future research.eng
dc.description.sponsorshipThis work is partially funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., in the context of the project UIDB/04524/2020, and under the Scientific Employment Stimulus - CEECINS/00051/2018. The authors also gratefully acknowledge the European Union - Portuguese Recovery and Resilience Plan, Grant Contract number: Sustainable Stone by Portugal, Call: 2021-C05i0101-02—agendas/alianças mobilizadoras para a reindustrialização - PRR, Proposal: C632482988-00467016.
dc.identifier.citationSilva, Alexandre & Antunes, Carolina & Miragaia, Rolando & Costa, Rogério Luís & Silva, Fernando & Ribeiro, José. (2025). Artificial Intelligence Applied to the Stone Manufacturing Industry: A Systematic Literature Review. 10.2139/ssrn.5188439.
dc.identifier.doi10.1016/j.compeleceng.2025.110702
dc.identifier.issn0045-7906
dc.identifier.urihttp://hdl.handle.net/10400.8/14516
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationResearch Center in Informatics and Communications
dc.relation.ispartofComputers and Electrical Engineering
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence
dc.subjectMachine learning
dc.subjectStone industry
dc.subjectStone manufacturing
dc.subjectNatural stone
dc.subjectComputer vision
dc.titleArtificial intelligence applied to the stone manufacturing industry: A systematic literature revieweng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Center in Informatics and Communications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04524%2F2020/PT
oaire.citation.titleComputers and Electrical Engineering
oaire.citation.volume128
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameSantos Silva
person.familyNameMiragaia
person.familyNamede Carvalho Costa
person.familyNameSilva
person.familyNameRibeiro
person.givenNameAlexandre
person.givenNameRolando
person.givenNameRogério Luís
person.givenNameFernando
person.givenNameJosé
person.identifier662638
person.identifier.ciencia-idC712-E02E-0ED2
person.identifier.ciencia-id7717-9573-0C0F
person.identifier.ciencia-id9D19-84F9-F1CA
person.identifier.ciencia-id0C1B-5E3F-6830
person.identifier.orcid0009-0005-6975-9714
person.identifier.orcid0000-0003-4213-9302
person.identifier.orcid0000-0003-2306-7585
person.identifier.orcid0000-0001-9335-1851
person.identifier.orcid0000-0003-3019-1330
person.identifier.ridGLS-3615-2022
person.identifier.ridA-7940-2016
person.identifier.scopus-author-id26422369700
person.identifier.scopus-author-id7801604983
person.identifier.scopus-author-id24402946400
person.identifier.scopus-author-id55947747200
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
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