Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61749
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBakhtari, Ahmad Reshaden
dc.contributor.authorWaris, Mohammad Maqboolen
dc.contributor.authorSanin, Cesaren
dc.contributor.authorSzczerbicki, Edwarden
dc.date.accessioned2024-07-22T11:05:37Z-
dc.date.available2024-07-22T11:05:37Z-
dc.date.issued2021-07-
dc.identifier.citationCybernetics and Systems, 52(5), p. 350-378en
dc.identifier.issn1087-6553en
dc.identifier.issn0196-9722en
dc.identifier.urihttps://hdl.handle.net/1959.11/61749-
dc.description.abstract<p>The fourth industrial revolution known as Industry 4.0 is reshaping and evolving the way industries produce products and individuals live and work therefore, gaining massive attraction from academia, business, and politics. The manufacturing industries are optimistic regarding the opportunities that Industry 4.0 may offer such as improved efficiency, productivity and customization. The present research contributes to the Industry 4.0 literature by identifying, modeling, analyzing, and prioritizing the challenges in implementing Industry 4.0 in manufacturing industries. In doing so, the article first introduces the interpretive structural modeling (ISM) to develop the hierarchical relationships among the challenges and analyzes their mutual interactions. Further, “Matrice d’Impacts Croises Multiplication Appliquee aun Classement” (MICMAC) analysis is used to categorize the challenges into four categories, namely autonomous, driver, dependent, and linkage based on their driving power and dependence power. Moreover, fuzzy analytic hierarchy process (F-AHP) methodology is used to prioritize the challenges based on three criteria: driving power, dependence power, and change management. The hierarchical model developed through ISM methodology shows that “lack of vision and leadership from top management (C12), lack of skills training program and education (C2), and uncertainty of return on investment (C9)” are the major challenges in implementing Industry 4.0 in manufacturing industries. The findings of F-AHP analysis suggest that “lack of vision and leadership from top management (C12), lack of skilled workforce (C3), lack of skills training program and education (C2), and uncertainty of return on investment (C9)” are some of the major challenges of implementing Industry 4.0. Finally, the obtained results show how challenges affect other so that to uncover the root cause triggering the other challenges. The industrial practitioners and managers can then take advantage of these analyses to know which challenge acts as the main barrier in implementing Industry 4.0 and to be focused first in order to reach a solution.</p>en
dc.languageenen
dc.publisherTaylor & Francis Incen
dc.relation.ispartofCybernetics and Systemsen
dc.titleEvaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Processen
dc.typeJournal Articleen
dc.identifier.doi10.1080/01969722.2020.1871226en
local.contributor.firstnameAhmad Reshaden
local.contributor.firstnameMohammad Maqboolen
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.startpage350en
local.format.endpage378en
local.peerreviewedYesen
local.identifier.volume52en
local.identifier.issue5en
local.contributor.lastnameBakhtarien
local.contributor.lastnameWarisen
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:1959.11/61749en
local.date.onlineversion2021-01-29-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleEvaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Processen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorBakhtari, Ahmad Reshaden
local.search.authorWaris, Mohammad Maqboolen
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/e45d8735-cbd2-4a90-94e7-a32a3baaa345en
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-07-25en
Appears in Collections:Journal Article
School of Science and Technology
Files in This Item:
1 files
File SizeFormat 
Show simple item record

SCOPUSTM   
Citations

39
checked on Nov 23, 2024

Page view(s)

266
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.