nach oben

Erschienen in:

2024 | OriginalPaper | Buchkapitel

Examining the Role of Industry 4.0 in Supply Chain Optimization Through Additive Manufacturing

verfasst von : Shubhendu Singh, Subhas Chandra Misra, Gaurvendra Singh

Erschienen in: Advances in Intelligent Manufacturing and Service System Informatics

Verlag: Springer Nature Singapore

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The implementation of Industry 4.0 enabling technologies to optimize supply chain processes has become an essential aspect of modern manufacturing. Supply chain optimization (SCO) through additive manufacturing technology (AMT) is one area where Industry 4.0 is having a considerable impact. This study, therefore, explores the aspects of Industry 4.0 enabled by the incorporation of AMT into the production system that contribute to supply chain optimization. Ten such features have been identified and analyzed in this study using the novel Grey Influence analysis (GINA) technique. GINA methodology in this research helps to circumvent the restrictions of contemporary causal modeling methods such as the Decision-making trial and evaluation laboratory (DEMATEL) and Interpretative structural modeling (ISM) with the cumulative integration of responses, thus mitigating data loss. The results of the investigation demonstrate that cloud manufacturing, sustainable manufacturing, on-demand manufacturing, and distributed manufacturing are the predominant features of Industry 4.0 enabled by AMT. The findings of this study can be utilized by businesses to take informed decisions concerning incorporation, investment, and optimal application of AMT as well as to determine the significance of AMT to optimize their supply chains.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel A Stochastic Bilevel Programming Model for an Industrial Symbiosis Network

Nächstes Kapitel Mathematical Models for the Reviewer Assignment Problem in Project Management and a Case Study

Horst, D.J., Duvoisin, C.A., de Almeida Vieira, R.: Additive manufacturing at industry 4.0: a review. Int. J. Eng. Tech. Res. 0869(8), 3 (2018). www.erpublication.org

Stentoft, J., Rajkumar, C.: The relevance of Industry 4.0 and its relationship with moving manufacturing out, back and staying at home. Int. J. Prod. Res. 58(10), 2953–2973 (2020). https://doi.org/10.1080/00207543.2019.1660823CrossRef

Garrido-hidalgo, C., Olivares, T., Ramirez, F.J., Roda-sanchez, L.: An end-to-end Internet of Things solution for reverse supply chain management in industry 4.0. Comput. Ind. 112, 103127 (2019). https://doi.org/10.1016/j.compind.2019.103127CrossRef

Garcia, D.J., You, F.: Supply chain design and optimization: challenges and opportunities. Comput. Chem. Eng. 81, 153–170 (2015). https://doi.org/10.1016/j.compchemeng.2015.03.015CrossRef

Beheshtinia, M.A., Feizollahy, P., Fathi, M.: Supply chain optimization considering sustainability aspects. Sustain. 13(21), 11873 (2021). https://doi.org/10.3390/su132111873

Sonar, H., Ghosh, S., Singh, R.K., Khanzode, V., Akarte, M., Ghag, N.: Implementing additive manufacturing for sustainability in operations: analysis of enabling factors. IEEE Trans. Eng. Manag., pp. 1–15 (2022). https://doi.org/10.1109/TEM.2022.3206234

Niaki, M.K., Nonino, F., Palombi, G., Torabi, S.A.: Economic sustainability of additive manufacturing: contextual factors driving its performance in rapid prototyping. J. Manuf. Technol. Manag. 30(2), 353–365 (2019). https://doi.org/10.1108/JMTM-05-2018-0131

Song, J.S., Zhang, Y.: Stock or print? Impact of 3-D printing on spare parts logistics. Manage. Sci. 66(9), 3860–3878 (2020). https://doi.org/10.1287/mnsc.2019.3409CrossRef

Liu, P., Huang, S.H., Mokasdar, A., Zhou, H., Hou, L.: The impact of additive manufacturing in the aircraft spare parts supply chain: Supply chain operation reference (scor) model based analysis. Prod. Plan. Control 25, 1169–1181 (2014). https://doi.org/10.1080/09537287.2013.808835CrossRef

10.

Mehrpouya, M., Vosooghnia, A., Dehghanghadikolaei, A., Fotovvati, B.: The benefits of additive manufacturing for sustainable design and production (2021). https://doi.org/10.1016/B978-0-12-818115-7.00009-2

11.

Ntinas, C., Gkortzis, D., Papadopoulos, A., Ioannidis, D.: Industry 4.0 sustainable supply chains: an application of an IoT enabled scrap metal management solution. J. Clean. Prod. 269, 122377 (2020). https://doi.org/10.1016/j.jclepro.2020.122377

12.

Kumar, V., Vrat, P., Shankar, R.: Prioritization of strategies to overcome the barriers in industry 4.0: a hybrid MCDM approach, 58(3), 711–750. Springer India (2021). https://doi.org/10.1007/s12597-020-00505-1

13.

Moeuf, A., Lamouri, S., Pellerin, R., Tamayo-Giraldo, S., Tobon-Valencia, E., Eburdy, R.: Identification of critical success factors, risks and opportunities of Industry 4.0 in SMEs. Int. J. Prod. Res. 58(5), 1384–1400 (2020). https://doi.org/10.1080/00207543.2019.1636323CrossRef

14.

Sonar, H., Khanzode, V., Akarte, M.: Investigating additive manufacturing implementation factors using integrated ISM-MICMAC approach. Rapid Prototyp. J. 26(10), 1837–1851 (2020). https://doi.org/10.1108/RPJ-02-2020-0038CrossRef

15.

Thomas, D.: Costs , benefits , and adoption of additive manufacturing : a supply chain perspective. Int. J. Adv. Manuf. Technol. 85, 1857–1876 (2016). https://doi.org/10.1007/s00170-015-7973-6

16.

Stavropoulos, P., Foteinopoulos, P., Papapacharalampopoulos, A.: On the impact of additive manufacturing processes complexity on modelling. Appl. Sci. 11(16), 7743 (2021). https://doi.org/10.3390/app11167743

17.

Eyers, D.R., Potter, A.T., Gosling, J., Naim, M.M.: The flexibility of industrial additive manufacturing systems. Int. J. Oper. Prod. Manag. 38(12), 2313–2343 (2018). https://doi.org/10.1108/IJOPM-04-2016-0200CrossRef

18.

Basu, J.R., Abdulrahman, M.D., Yuvaraj, M.: Improving agility and resilience of automotive spares supply chain: the additive manufacturing enabled truck model. Socioecon. Plann. Sci., 85, 101401 (2022). https://doi.org/10.1016/j.seps.2022.101401

19.

Belhadi, A., Kamble, S.S., Venkatesh, M., Jabbour, C.J.C., Benkhati, I.: Building supply chain resilience and efficiency through additive manufacturing: an ambidextrous perspective on the dynamic capability view. Int. J. Prod. Econ., 249, 108516 (2022). https://doi.org/10.1016/j.ijpe.2022.108516

20.

Berman, B.: 3-D printing: the new industrial revolution. Bus. Horiz. 55(2), 155–162 (2012). https://doi.org/10.1016/j.bushor.2011.11.003CrossRef

21.

Huang, S.H., Liu, P., Mokasdar, A., Hou, L.: Additive manufacturing and its societal impact: a literature review. Int. J. Adv. Manuf. Technol. 67(5–8), 1191–1203 (2013). https://doi.org/10.1007/s00170-012-4558-5CrossRef

22.

Moreno-Cabezali, B.M., Fernandez-Crehuet, J.M.: Application of a fuzzy-logic based model for risk assessment in additive manufacturing R&D projects. Comput. Ind. Eng., 145, 106529 (2020). https://doi.org/10.1016/j.cie.2020.106529

23.

Meyer, M.M., Glas, A.H., Eßig, M.: A Delphi study on the supply risk-mitigating effect of additive manufacturing during SARS-COV-2. J. Purch. Supply Manag. 28(4), 100791. (2022). https://doi.org/10.1016/j.pursup.2022.100791

24.

Javaid, M., Haleem, A., Singh, R.P., Suman, R., Rab, S.: Role of additive manufacturing applications towards environmental sustainability. Adv. Ind. Eng. Polym. Res. 4, 312–322 (2021). https://doi.org/10.1016/j.aiepr.2021.07.005

25.

Eyers, D., Managing 3D printing: Operations Management for Additive Manufacturing. Springer International Publishing, Berlin (2020).https://doi.org/10.1007/978-3-030-23323-5

26.

Rauch, E., Unterhofer, M., Dallasega, P.: Industry sector analysis for the application of additive manufacturing in smart and distributed manufacturing systems. Manuf. Lett. 15, 126–131 (2018). https://doi.org/10.1016/j.mfglet.2017.12.011CrossRef

27.

De Giovanni, P., Belvedere, V., Grando, A.: The selection of industry 4.0 technologies through Bayesian networks: an operational perspective. IEEE Trans. Eng. Manag., 1–16 (2022). https://doi.org/10.1109/TEM.2022.3200868

28.

Khajavi, S.H., Holmström, J., Partanen, J.: Additive manufacturing in the spare parts supply chain: hub configuration and technology maturity. Rapid Prototyp. J. 24(7), 1178–1192 (2018). https://doi.org/10.1108/RPJ-03-2017-0052CrossRef

29.

Akmal, J.S., Salmi, M., Björkstrand, R., Partanen, J., Holmström, J.: Switchover to industrial additive manufacturing: dynamic decision-making for problematic spare parts. Int. J. Oper. Prod. Manag. 42(13), 358–384 (2022). https://doi.org/10.1108/IJOPM-01-2022-0054CrossRef

30.

Ju-Long, D.: Control problems of grey systems. Syst. Control Lett. 1(5), 288–294 (1982). https://doi.org/10.1016/S0167-6911(82)80025-XMathSciNetCrossRefMATH

31.

Liu, S., Forrest, J.Y.L.: Grey Systems: Theory and Applications. Springer, Berlin Heidelberg (2010). https://books.google.co.in/books?id=hJsRBwAAQBAJ

32.

Vishwakarma, A., Dangayach, G.S., Meena, M.L., Gupta, S.: Analysing barriers of sustainable supply chain in apparel & textile sector: a hybrid ISM-MICMAC and DEMATEL approach. Clean. Logist. Supply Chain 5, 100073 (2022). https://doi.org/10.1016/j.clscn.2022.100073

33.

Rajesh, R.: An introduction to grey influence analysis (GINA): applications to causal modelling in marketing and supply chain research. Expert Syst. Appl. 212, 0–2 (2023). https://doi.org/10.1016/j.eswa.2022.118816

Titel: Examining the Role of Industry 4.0 in Supply Chain Optimization Through Additive Manufacturing
verfasst von: Shubhendu Singh
Subhas Chandra Misra
Gaurvendra Singh
Verlag: Springer Nature Singapore
Buch: Advances in Intelligent Manufacturing and Service System Informatics
Print ISBN: 978-981-9960-61-3

Electronic ISBN: 978-981-9960-62-0

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-99-6062-0_62

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner

Marktübersichten