IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v34y2023i6d10.1007_s10845-022-01958-5.html
   My bibliography  Save this article

Title: production planning and control in industry 4.0 environment: a morphological analysis of literature and research agenda

Author

Listed:
  • Anupama Prashar

    (Management Development Institute Gurgaon)

Abstract

The rapid industrial changes triggered by the fourth industrial revolution or I4.0 have ensued a dynamic and integrative perspective in production planning and control (PPC) decisions. Prior research on PPC transformation in I4.0 environment is in the form of computational experiments to solve sector-specific issues, with little emphasis on how PPC is influenced by the evolving digital capabilities, and how it operates in the new manufacturing paradigm? This study aims to develop an analytical framework to consolidate the prevailing research on PPC in I4.0 and identify future research possibilities. We used morphological analysis (MA) approach for reviewing 104 studies identified through a systematic review protocol. The MA framework is created with five dimensions (i.e., study setting, PPC functions, enabling technologies, digital capabilities, and core performance outcomes) defined based on input-process-outcome (IPO) approach of system analysis. This study is possibly the first to use MA for reviewing the PPC literature, presenting practitioner and theoretical contributions. The MA framework acts as a ready reckoner of the literature and its modular representation has the flexibility to be modified or augmented as the literature evolves.

Suggested Citation

  • Anupama Prashar, 2023. "Title: production planning and control in industry 4.0 environment: a morphological analysis of literature and research agenda," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2513-2528, August.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:6:d:10.1007_s10845-022-01958-5
    DOI: 10.1007/s10845-022-01958-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-022-01958-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-022-01958-5?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. Siavash Valizadeh & Omid Fatahi Valilai & Mahmoud Houshmand, 2020. "Flexible flow line scheduling considering machine eligibility in a digital dental laboratory," International Journal of Production Research, Taylor & Francis Journals, vol. 58(21), pages 6513-6531, November.
    2. Alexandre Moeuf & Robert Pellerin & Samir Lamouri & Simon Tamayo-Giraldo & Rodolphe Barbaray, 2018. "The industrial management of SMEs in the era of Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1118-1136, February.
    3. Olumide Emmanuel Oluyisola & Fabio Sgarbossa & Jan Ola Strandhagen, 2020. "Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications," Sustainability, MDPI, vol. 12(9), pages 1-29, May.
    4. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    5. Baliga, Ashwin J. & Chawla, Vaibhav & Sunder M, Vijaya & Ganesh, L.S. & Sivakumaran, Bharadhwaj, 2021. "Service Failure and Recovery in B2B Markets – A Morphological Analysis," Journal of Business Research, Elsevier, vol. 131(C), pages 763-781.
    6. Maroua Nouiri & Damien Trentesaux & Abdelghani Bekrar, 2019. "Towards Energy Efficient Scheduling of Manufacturing Systems through Collaboration between Cyber Physical Production and Energy Systems," Energies, MDPI, vol. 12(23), pages 1-30, November.
    7. Bogataj, David & Bogataj, Marija & Hudoklin, Domen, 2017. "Mitigating risks of perishable products in the cyber-physical systems based on the extended MRP model," International Journal of Production Economics, Elsevier, vol. 193(C), pages 51-62.
    8. Olumide Emmanuel Oluyisola & Swapnil Bhalla & Fabio Sgarbossa & Jan Ola Strandhagen, 2022. "Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 311-332, January.
    9. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    10. Sandeep Kumar & Bhushan S. Purohit & Vikas Manjrekar & Vivek Singh & Bhupesh Kumar Lad, 2018. "Investigating the value of integrated operations planning: A case-based approach from automotive industry," International Journal of Production Research, Taylor & Francis Journals, vol. 56(22), pages 6971-6992, November.
    11. Dongni Li & Xianwen Meng & Miao Li & Yunna Tian, 2016. "An ACO-based intercell scheduling approach for job shop cells with multiple single processing machines and one batch processing machine," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 283-296, April.
    12. Chunyang Yu & Wei Zhang & Xun Xu & Yangjian Ji & Shiqiang Yu, 2018. "Data mining based multi-level aggregate service planning for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1351-1361, August.
    13. Wen-Hsien Tsai & Yin-Hwa Lu, 2018. "A Framework of Production Planning and Control with Carbon Tax under Industry 4.0," Sustainability, MDPI, vol. 10(9), pages 1-24, September.
    Full references (including those not matched with items on IDEAS)

    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. Andreas Felsberger & Gerald Reiner, 2020. "Sustainable Industry 4.0 in Production and Operations Management: A Systematic Literature Review," Sustainability, MDPI, vol. 12(19), pages 1-39, September.
    2. Calabrese, Armando & Costa, Roberta & Tiburzi, Luigi & Brem, Alexander, 2023. "Merging two revolutions: A human-artificial intelligence method to study how sustainability and Industry 4.0 are intertwined," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    3. Mariani, Marcello & Borghi, Matteo, 2019. "Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    4. Bianco, Débora & Bueno, Adauto & Godinho Filho, Moacir & Latan, Hengky & Miller Devós Ganga, Gilberto & Frank, Alejandro G. & Chiappetta Jabbour, Charbel Jose, 2023. "The role of Industry 4.0 in developing resilience for manufacturing companies during COVID-19," International Journal of Production Economics, Elsevier, vol. 256(C).
    5. Hsing-Chun Hung & Yuh-Wen Chen, 2023. "Striving to Achieve United Nations Sustainable Development Goals of Taiwanese SMEs by Adopting Industry 4.0," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    6. Gillani, Fatima & Chatha, Kamran Ali & Sadiq Jajja, Muhammad Shakeel & Farooq, Sami, 2020. "Implementation of digital manufacturing technologies: Antecedents and consequences," International Journal of Production Economics, Elsevier, vol. 229(C).
    7. Kristoffersen, Eivind & Blomsma, Fenna & Mikalef, Patrick & Li, Jingyue, 2020. "The smart circular economy: A digital-enabled circular strategies framework for manufacturing companies," Journal of Business Research, Elsevier, vol. 120(C), pages 241-261.
    8. Bag, Surajit & Gupta, Shivam & Kumar, Sameer, 2021. "Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development," International Journal of Production Economics, Elsevier, vol. 231(C).
    9. Oliveira-Dias, Diéssica de & Maqueira-Marin, Juan Manuel & Moyano-Fuentes, José & Carvalho, Helena, 2023. "Implications of using Industry 4.0 base technologies for lean and agile supply chains and performance," International Journal of Production Economics, Elsevier, vol. 262(C).
    10. Somohano-Rodríguez, Francisco M. & Madrid-Guijarro, Antonia, 2022. "Do industry 4.0 technologies improve Cantabrian manufacturing smes performance? The role played by industry competition," Technology in Society, Elsevier, vol. 70(C).
    11. Vaibhav S. Narwane & Rakesh D. Raut & Sachin Kumar Mangla & Manoj Dora & Balkrishna E. Narkhede, 2023. "Risks to Big Data Analytics and Blockchain Technology Adoption in Supply Chains," Annals of Operations Research, Springer, vol. 327(1), pages 339-374, August.
    12. Verónica Sansabas-Villalpando & Iván Juan Carlos Pérez-Olguín & Luis Asunción Pérez-Domínguez & Luis Alberto Rodríguez-Picón & Luis Carlos Mendez-González, 2019. "CODAS HFLTS Method to Appraise Organizational Culture of Innovation and Complex Technological Changes Environments," Sustainability, MDPI, vol. 11(24), pages 1-28, December.
    13. Bokhorst, Jos A.C. & Knol, Wilfred & Slomp, Jannes & Bortolotti, Thomas, 2022. "Assessing to what extent smart manufacturing builds on lean principles," International Journal of Production Economics, Elsevier, vol. 253(C).
    14. Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro G., 2020. "Industry 4.0 innovation ecosystems: An evolutionary perspective on value cocreation," International Journal of Production Economics, Elsevier, vol. 228(C).
    15. Delgosha, Mohammad Soltani & Hajiheydari, Nastaran & Talafidaryani, Mojtaba, 2022. "Discovering IoT implications in business and management: A computational thematic analysis," Technovation, Elsevier, vol. 118(C).
    16. Padhi, Sidhartha S. & Mukherjee, Soumyatanu & Edwin Cheng, T.C., 2024. "Optimal investment decision for industry 4.0 under uncertainties of capability and competence building for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 267(C).
    17. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    18. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
    19. Battistoni, Elisa & Gitto, Simone & Murgia, Gianluca & Campisi, Domenico, 2023. "Adoption paths of digital transformation in manufacturing SME," International Journal of Production Economics, Elsevier, vol. 255(C).
    20. Riccardo Brozzi & David Forti & Erwin Rauch & Dominik T. Matt, 2020. "The Advantages of Industry 4.0 Applications for Sustainability: Results from a Sample of Manufacturing Companies," Sustainability, MDPI, vol. 12(9), pages 1-19, May.

    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:spr:joinma:v:34:y:2023:i:6:d:10.1007_s10845-022-01958-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.