Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61800
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dc.contributor.authorShafiq, Syed Imranen
dc.contributor.authorSanin, Cesaren
dc.contributor.authorSzczerbicki, Edwarden
local.source.editorEditor(s): Edward Szczerbicki and Cesar Saninen
dc.date.accessioned2024-07-25T03:06:59Z-
dc.date.available2024-07-25T03:06:59Z-
dc.date.issued2020-
dc.identifier.citationKnowledge Management and Engineering with Decisional DNA, p. 83-126en
dc.identifier.issn1868-4408en
dc.identifier.issn1868-4394en
dc.identifier.urihttps://hdl.handle.net/1959.11/61800-
dc.description.abstract<p>Knowledge-based support has become an indispensable part not only to the traditional manufacturing set-ups but also to the new fast-emerging Industry 4.0 scenario. In this regard, successful research has been performed and extensively reported to develop Decisional DNA based knowledge representation models of engineering object and engineering process called Virtual engineering object (VEO), Virtual engineering process (VEP) and Virtual engineering factory (VEF). These models are the virtual representation of manufacturing resources, and with the help of IoT, are capable of capturing the past experience and formal decisions. In this chapter, a complete virtual manufacturing environment is summarized. Furthermore, the scope of this work is explained in the Cyber-Physical Systems (CPS) based Industry 4.0 framework. Four case studies are presented to validate the practical implementation of the proposed concept. In the first case the idea of VEO-VEP-VEF is applied to design an intelligent factory framework to achieve contextual information through real-time visualization. In the second study, the smart tool performance analysis is presented in which data of key tool parameters like tool life, surface integrity, tool forces, and chip formation can be sensed in real-time; also predictions can be made according to the specific requirements. In the third case study, the technique of Decisional DNA (DDNA) is applied to FMS to develop a generic model to achieve effective scheduling and manufacturing flexibility. In the last study, the framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical CIM is presented. The benefits of this approach are manifold as it creates manufacturing DNA of a factory, felicitates in effective decision making, increases the rate of production, reduces errors and production waste, and streamlines manufacturing sub-systems. Moreover, and can be instrumental in designing Industry 4.0.</p>en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofKnowledge Management and Engineering with Decisional DNAen
dc.relation.ispartofseriesIntelligent Systems Reference Libraryen
dc.titleSmart Decisional DNA Technology to Enhance Industry 4.0 Environment in Conjunction with Conventional Manufacturingen
dc.typeBook Chapteren
dc.identifier.doi10.1007/978-3-030-39601-5_3en
local.contributor.firstnameSyed Imranen
local.contributor.firstnameCesaren
local.contributor.firstnameEdwarden
local.profile.schoolSchool of Science and Technologyen
local.profile.emailcmaldon3@une.edu.auen
local.output.categoryB1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeCham, Switzerlanden
local.identifier.totalchapters7en
local.format.startpage83en
local.format.endpage126en
local.series.number183en
local.peerreviewedYesen
local.contributor.lastnameShafiqen
local.contributor.lastnameSaninen
local.contributor.lastnameSzczerbickien
local.seriespublisherSpringeren
local.seriespublisher.placeSwitzerlanden
dc.identifier.staffune-id:cmaldon3en
local.profile.orcid0000-0001-8515-417Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61800en
local.date.onlineversion2020-02-05-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleSmart Decisional DNA Technology to Enhance Industry 4.0 Environment in Conjunction with Conventional Manufacturingen
local.output.categorydescriptionB1 Chapter in a Scholarly Booken
local.search.authorShafiq, Syed Imranen
local.search.authorSanin, Cesaren
local.search.authorSzczerbicki, Edwarden
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.available2020en
local.year.published2020en
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-08-21en
Appears in Collections:Book Chapter
School of Science and Technology
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