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dc.contributor.authorTerziyan, Vagan
dc.contributor.authorGryshko, Svitlana
dc.contributor.authorGolovianko, Mariia
dc.date.accessioned2018-11-26T10:19:57Z
dc.date.available2020-07-01T21:35:13Z
dc.date.issued2018fi
dc.identifier.citationTerziyan, V., Gryshko, S., & Golovianko, M. (2018). Patented intelligence : cloning human decision models for Industry 4.0. <em>Journal of Manufacturing Systems</em>, 48 (Part C), 204-217. <a href="https://doi.org/10.1016/j.jmsy.2018.04.019">doi:10.1016/j.jmsy.2018.04.019</a>fi
dc.identifier.otherTUTKAID_77550
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/60331
dc.description.abstractIndustry 4.0 is a trend related to smart factories, which are cyber-physical spaces populated and controlled by the collective intelligence for the autonomous and highly flexible manufacturing purposes. Artificial Intelligence (AI) embedded into various planning, production, and management processes in Industry 4.0 must take the initiative and responsibility for making necessary real-time decisions in many cases. In this paper, we suggest the Pi-Mind technology as a compromise between completely human-expert-driven decision-making and AI-driven decision-making. Pi-Mind enables capturing, cloning and patenting essential parameters of the decision models from a particular human expert making these models transparent, proactive and capable of autonomic and fast decision-making simultaneously in many places. The technology facilitates the human impact (due to ubiquitous presence) in smart manufacturing processes and enables human-AI shared responsibility for the consequences of the decisions made. It also benefits from capturing and utilization of the traditionally human creative cognitive capabilities (sometimes intuitive and emotional), which in many cases outperform the rational decision-making. Pi-Mind technology is a set of models, techniques, and tools built on principles of value-based biased decision-making and creative cognitive computing to augment the axioms of decision rationality in industry.fi
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier Ltd
dc.relation.ispartofseriesJournal of Manufacturing Systems
dc.rightsCC BY-NC-ND 4.0
dc.subject.othervalmistustekniikkafi
dc.subject.otherteollisuusautomaatiofi
dc.subject.otherälytekniikkafi
dc.subject.othertietämysjärjestelmätfi
dc.subject.otherjoukkoälyfi
dc.subject.otherpäätöksentekofi
dc.subject.otherindustry 4.0fi
dc.subject.otherPi-Mindfi
dc.subject.otherdecision-makingfi
dc.subject.othercyber-physical systemfi
dc.subject.othercognitive modelsfi
dc.subject.othercollective intelligencefi
dc.subject.othervalue systemfi
dc.subject.otherpreferencefi
dc.subject.otherclonefi
dc.subject.otherpatented intelligencefi
dc.subject.othersmart decisionfi
dc.subject.otherontologyfi
dc.titlePatented intelligence : cloning human decision models for Industry 4.0fi
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201811264867
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikka
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2018-11-26T07:15:11Z
dc.description.reviewstatuspeerReviewed
dc.format.pagerange204-217
dc.relation.issn0278-6125
dc.relation.numberinseriesPart C
dc.relation.volume48
dc.type.versionacceptedVersion
dc.rights.copyright© 2018 The Society of Manufacturing Engineers. Published by Elsevier Ltd.
dc.rights.accesslevelopenAccessfi
dc.format.contentfulltext
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.jmsy.2018.04.019


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CC BY-NC-ND 4.0
Except where otherwise noted, this item's license is described as CC BY-NC-ND 4.0