IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v186y2023ipbs0040162522007259.html
   My bibliography  Save this article

Industry 4.0: a tertiary literature review

Author

Listed:
  • Lemstra, Mary Anny Moraes Silva
  • de Mesquita, Marco Aurélio

Abstract

Industry 4.0 has become one of the most discussed subjects in academic and professional fields. The number of articles published is large and continues to increase, introducing new issues, concepts, methods, and technologies. Many review articles deal with specific issues and not always with the necessary rigor, making a more general understanding of the subject difficult. Motivated by the large volume of literature, this study makes a tertiary review of Industry 4.0 (i4.0), identifying the main concepts, methods, and technologies. The study is guided by three research questions: What are the literature reviews on i4.0? What are the research questions of these reviews? What are the main results of i4.0 reviews? The reviewed articles are systematic review articles indexed in the Scopus and Web of Science databases. This study presents a descriptive analysis of the review articles (46 articles) and a second descriptive analysis of the references cited in them (1542 articles). In content analysis, we grouped the articles into three classes: conceptual articles, articles on enabling technologies, and articles that address operations management in i4.0. The reviewed articles show the multidisciplinary nature of the topic and the still relative scarcity of studies on its application in companies.

Suggested Citation

  • Lemstra, Mary Anny Moraes Silva & de Mesquita, Marco Aurélio, 2023. "Industry 4.0: a tertiary literature review," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
  • Handle: RePEc:eee:tefoso:v:186:y:2023:i:pb:s0040162522007259
    DOI: 10.1016/j.techfore.2022.122204
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522007259
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2022.122204?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fernanda Strozzi & Claudia Colicchia & Alessandro Creazza & Carlo Noè, 2017. "Literature review on the ‘Smart Factory’ concept using bibliometric tools," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6572-6591, November.
    2. Osterrieder, Philipp & Budde, Lukas & Friedli, Thomas, 2020. "The smart factory as a key construct of industry 4.0: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 221(C).
    3. Juan Pablo Usuga Cadavid & Samir Lamouri & Bernard Grabot & Robert Pellerin & Arnaud Fortin, 2020. "Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1531-1558, August.
    4. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    5. Manuel Parente & Gonçalo Figueira & Pedro Amorim & Alexandra Marques, 2020. "Production scheduling in the context of Industry 4.0: review and trends," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5401-5431, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kumar, Devinder & Singh, Rajesh Kr & Mishra, Ruchi & Daim, Tugrul U., 2023. "Roadmap for integrating blockchain with Internet of Things (IoT) for sustainable and secured operations in logistics and supply chains: Decision making framework with case illustration," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    2. Huang, Kerry & Wang, Kedi & Lee, Peter K.C. & Yeung, Andy C.L., 2023. "The impact of industry 4.0 on supply chain capability and supply chain resilience: A dynamic resource-based view," International Journal of Production Economics, Elsevier, vol. 262(C).
    3. Betz, Ulrich A.K. & Arora, Loukik & Assal, Reem A. & Azevedo, Hatylas & Baldwin, Jeremy & Becker, Michael S. & Bostock, Stefan & Cheng, Vinton & Egle, Tobias & Ferrari, Nicola & Schneider-Futschik, El, 2023. "Game changers in science and technology - now and beyond," Technological Forecasting and Social Change, Elsevier, vol. 193(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mitsuhiro Fukuzawa & Ryosuke Sugie & Youngwon Park & Jin Shi, 2022. "An Exploratory Case Study on the Metrics and Performance of IoT Investment in Japanese Manufacturing Firms," Sustainability, MDPI, vol. 14(5), pages 1-21, February.
    2. Eleonora Di Maria & Valentina De Marchi & Ambra Galeazzo, 2022. "Industry 4.0 technologies and circular economy: The mediating role of supply chain integration," Business Strategy and the Environment, Wiley Blackwell, vol. 31(2), pages 619-632, February.
    3. Shih-Chia Chang & Hsu-Hwa Chang & Ming-Tsang Lu, 2021. "Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    4. Li, Mingxing & Huang, George Q., 2021. "Production-intralogistics synchronization of industry 4.0 flexible assembly lines under graduation intelligent manufacturing system," International Journal of Production Economics, Elsevier, vol. 241(C).
    5. Behice Meltem Kayhan & Gokalp Yildiz, 2023. "Reinforcement learning applications to machine scheduling problems: a comprehensive literature review," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 905-929, March.
    6. Dieste, Marcos & Sauer, Philipp C. & Orzes, Guido, 2022. "Organizational tensions in industry 4.0 implementation: A paradox theory approach," International Journal of Production Economics, Elsevier, vol. 251(C).
    7. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    8. Agnieszka A. Tubis & Katarzyna Grzybowska, 2022. "In Search of Industry 4.0 and Logistics 4.0 in Small-Medium Enterprises—A State of the Art Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    9. Satish Kumar & Filomena Maggino & Raj V. Mahto & Riya Sureka & Leonardo Salvatore Alaimo & Weng Marc Lim, 2022. "Social Indicators Research: A Retrospective Using Bibliometric Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(1), pages 413-448, July.
    10. Sebastian Mayer & Tobias Classen & Christian Endisch, 2021. "Modular production control using deep reinforcement learning: proximal policy optimization," Journal of Intelligent Manufacturing, Springer, vol. 32(8), pages 2335-2351, December.
    11. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    12. Özden Tozanlı & Elif Kongar & Surendra M. Gupta, 2020. "Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain," Sustainability, MDPI, vol. 12(13), pages 1-33, July.
    13. Mansoureh Maadi & Hadi Akbarzadeh Khorshidi & Uwe Aickelin, 2021. "A Review on Human–AI Interaction in Machine Learning and Insights for Medical Applications," IJERPH, MDPI, vol. 18(4), pages 1-27, February.
    14. Björn Häckel & Florian Hänsch & Michael Hertel & Jochen Übelhör, 2019. "Assessing IT availability risks in smart factory networks," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 523-558, December.
    15. Livio Cricelli & Serena Strazzullo, 2021. "The Economic Aspect of Digital Sustainability: A Systematic Review," Sustainability, MDPI, vol. 13(15), pages 1-15, July.
    16. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
    17. Gohari, Adel & Ahmad, Anuar Bin & Balasbaneh, Ali Tighnavard & Gohari, Ali & Hasan, Razi & Sholagberu, Abdulkadir Taofeeq, 2022. "Significance of intermodal freight modal choice criteria: MCDM-based decision support models and SP-based modal shift policies," Transport Policy, Elsevier, vol. 121(C), pages 46-60.
    18. Estefania Tobon-Valencia & Samir Lamouri & Robert Pellerin & Alexandre Moeuf, 2022. "Modeling of the Master Production Schedule for the Digital Transition of Manufacturing SMEs in the Context of Industry 4.0," Sustainability, MDPI, vol. 14(19), pages 1-28, October.
    19. Sudhanshu Joshi & Manu Sharma, 2022. "A Literature Survey on Vaccine Supply Chain Management Amidst COVID-19: Literature Developments, Future Directions and Open Challenges for Public Health," World, MDPI, vol. 3(4), pages 1-28, October.
    20. Eryarsoy, Enes & Kilic, Huseyin Selcuk & Zaim, Selim & Doszhanova, Marzhan, 2022. "Assessing IoT challenges in supply chain: A comparative study before and during- COVID-19 using interval valued neutrosophic analytical hierarchy process," Journal of Business Research, Elsevier, vol. 147(C), pages 108-123.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:186:y:2023:i:pb:s0040162522007259. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.