Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61750
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAhmed, Muhammad Bilalen
dc.contributor.authorMajeed, Farhaten
dc.contributor.authorSanin, Cesaren
dc.contributor.authorSzczerbicki, Edwarden
dc.date.accessioned2024-07-22T11:29:29Z-
dc.date.available2024-07-22T11:29:29Z-
dc.date.issued2021-
dc.identifier.citationCybernetics and Systems, 52(5), p. 296-312en
dc.identifier.issn1087-6553en
dc.identifier.issn0196-9722en
dc.identifier.urihttps://hdl.handle.net/1959.11/61750-
dc.description.abstract<p>In this paper we describe how our Smart Virtual Product Development (SVPD) system can be used to enhance product inspection planning. The SVPD system is comprised of three main modules, these being the design knowledge management (DKM) module, the manufacturing capability and process planning (MCAPP) module, and the product inspection planning (PIP) module. Experiential knowledge relating to formal decisional events is collected, stored and used by the system in the form of set of experiences (SOEs). Here we discuss the working mechanism of the PIP module and show how experiential knowledge relating to the inspection of products that have features and functions in common can be used to enhance product inspection planning during early stages of product development. Our discussion commences with an introduction to fundamental concepts and a general system overview. We then describe the development of our SVPD system’s PIP module, and a case study we undertook for validation purposes. Results of the case study show that our system is capable of supporting product inspection planning in smart manufacturing, and thus has a vital role to play in Industry 4.0.</p>en
dc.languageenen
dc.publisherTaylor & Francis Incen
dc.relation.ispartofCybernetics and Systemsen
dc.titleExperience-Based Product Inspection Planning for Industry 4.0en
dc.typeJournal Articleen
dc.identifier.doi10.1080/01969722.2020.1871222en
local.contributor.firstnameMuhammad Bilalen
local.contributor.firstnameFarhaten
local.contributor.firstnameCesaren
local.contributor.firstnameEdwarden
local.profile.schoolSchool of Science and Technologyen
local.profile.emailcmaldon3@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeUnited States of Americaen
local.format.startpage296en
local.format.endpage312en
local.peerreviewedYesen
local.identifier.volume52en
local.identifier.issue5en
local.contributor.lastnameAhmeden
local.contributor.lastnameMajeeden
local.contributor.lastnameSaninen
local.contributor.lastnameSzczerbickien
dc.identifier.staffune-id:cmaldon3en
local.profile.orcid0000-0001-8515-417Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61750en
local.date.onlineversion2021-01-28-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleExperience-Based Product Inspection Planning for Industry 4.0en
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorAhmed, Muhammad Bilalen
local.search.authorMajeed, Farhaten
local.search.authorSanin, Cesaren
local.search.authorSzczerbicki, Edwarden
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.available2021en
local.year.published2021en
local.fileurl.closedpublishedhttps://rune.une.edu.au/web/retrieve/7ddc269e-3b1f-4742-8d4a-f2df3f98f021en
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-07-30en
Appears in Collections:Journal Article
School of Science and Technology
Files in This Item:
1 files
File SizeFormat 
Show simple item record

SCOPUSTM   
Citations

9
checked on Nov 23, 2024

Page view(s)

188
checked on Aug 3, 2024
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.