IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i21p8757-d432742.html
   My bibliography  Save this article

Real-Time Data Utilization Barriers to Improving Production Performance: An In-depth Case Study Linking Lean Management and Industry 4.0 from a Learning Organization Perspective

Author

Listed:
  • Henrik Saabye

    (Department of Materials and Production, Aalborg University, 9000 Aalborg, Denmark)

  • Thomas Borup Kristensen

    (Aalborg University Business School, Aalborg University, 9000 Aalborg, Denmark)

  • Brian Vejrum Wæhrens

    (Department of Materials and Production, Aalborg University, 9000 Aalborg, Denmark)

Abstract

This study presents empirical evidence for the ongoing discussion about the link between Lean Management (LM) and industry 4.0 (I4.0) by exploring a non-technical perspective on how manufacturers can capitalize on their technological investments. The paper, therefore, studies the link between LM and I4.0 from a learning organization (LO) perspective by examining the implementation, commissioning, and utilization of a real-time operational data gathering system at a Danish building material manufacturer. This six months in-depth case study finds that for the manufacturer to utilize real-time operational data from a LO perspective, several barriers must be addressed: problem solving that is not initiated by operators, operators who do not have second-order problem-solving abilities, operators who perceive the new real-time data technology as coercive, poor learning environments and processes, and a lack of leadership that supports learning. This study can help practitioners understand the importance of balance, the prevalent technocentric focus when implementing new I4.0 technologies with a LO focus. Furthermore, the study provides practitioners with a list of specific barriers from a LO perspective to be mindful of when aiming to combine LM and I4.0 to improve production performance.

Suggested Citation

  • Henrik Saabye & Thomas Borup Kristensen & Brian Vejrum Wæhrens, 2020. "Real-Time Data Utilization Barriers to Improving Production Performance: An In-depth Case Study Linking Lean Management and Industry 4.0 from a Learning Organization Perspective," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:8757-:d:432742
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/21/8757/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/21/8757/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William Giordani da Silveira & Edson Pinheiro de Lima & Fernando Deschamps & Sergio E. Gouvea da Costa, 2018. "Identification of guidelines for Hoshin Kanri initiatives," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 67(1), pages 85-110, January.
    2. John Paul MacDuffie, 1997. "The Road to "Root Cause": Shop-Floor Problem-Solving at Three Auto Assembly Plants," Management Science, INFORMS, vol. 43(4), pages 479-502, April.
    3. Culot, Giovanna & Nassimbeni, Guido & Orzes, Guido & Sartor, Marco, 2020. "Behind the definition of Industry 4.0: Analysis and open questions," International Journal of Production Economics, Elsevier, vol. 226(C).
    4. 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.
    5. Bortolotti, Thomas & Boscari, Stefania & Danese, Pamela, 2015. "Successful lean implementation: Organizational culture and soft lean practices," International Journal of Production Economics, Elsevier, vol. 160(C), pages 182-201.
    6. Sven-Vegard Buer & Jan Ola Strandhagen & Felix T. S. Chan, 2018. "The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2924-2940, April.
    7. Cho, Young Sik & Linderman, Kevin, 2019. "Metacognition-based process improvement practices," International Journal of Production Economics, Elsevier, vol. 211(C), pages 132-144.
    8. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    9. Eelke Wiersma, 2007. "Conditions That Shape the Learning Curve: Factors That Increase the Ability and Opportunity to Learn," Management Science, INFORMS, vol. 53(12), pages 1903-1915, December.
    10. Tortorella, Guilherme Luz & Cawley Vergara, Alejandro Mac & Garza-Reyes, Jose Arturo & Sawhney, Rapinder, 2020. "Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers," International Journal of Production Economics, Elsevier, vol. 219(C), pages 284-294.
    11. Guilherme Luz Tortorella & Diego Fettermann, 2018. "Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2975-2987, April.
    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. Varun Tripathi & Somnath Chattopadhyaya & Alok Bhadauria & Shubham Sharma & Changhe Li & Danil Yurievich Pimenov & Khaled Giasin & Sunpreet Singh & Girish Dutt Gautam, 2021. "An Agile System to Enhance Productivity through a Modified Value Stream Mapping Approach in Industry 4.0: A Novel Approach," Sustainability, MDPI, vol. 13(21), pages 1-31, October.

    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. Tortorella, Guilherme Luz & Saurin, Tarcísio Abreu & Filho, Moacir Godinho & Samson, Daniel & Kumar, Maneesh, 2021. "Bundles of Lean Automation practices and principles and their impact on operational performance," International Journal of Production Economics, Elsevier, vol. 235(C).
    2. Tortorella, Guilherme Luz & Narayanamurthy, Gopalakrishnan & Thurer, Matthias, 2021. "Identifying pathways to a high-performing lean automation implementation: An empirical study in the manufacturing industry," International Journal of Production Economics, Elsevier, vol. 231(C).
    3. 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).
    4. 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).
    5. 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).
    6. Eslami, Mohammad H. & Achtenhagen, Leona & Bertsch, Cedric Tobias & Lehmann, Annika, 2023. "Knowledge-sharing across supply chain actors in adopting Industry 4.0 technologies: An exploratory case study within the automotive industry," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    7. Cifone, Fabiana Dafne & Hoberg, Kai & Holweg, Matthias & Staudacher, Alberto Portioli, 2021. "‘Lean 4.0’: How can digital technologies support lean practices?," International Journal of Production Economics, Elsevier, vol. 241(C).
    8. Ricci, Riccardo & Battaglia, Daniele & Neirotti, Paolo, 2021. "External knowledge search, opportunity recognition and industry 4.0 adoption in SMEs," International Journal of Production Economics, Elsevier, vol. 240(C).
    9. Battaglia, Daniele & Galati, Francesco & Molinaro, Margherita & Pessot, Elena, 2023. "Full, hybrid and platform complementarity: Exploring the industry 4.0 technology-performance link," International Journal of Production Economics, Elsevier, vol. 263(C).
    10. 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.
    11. Sony, Michael & Naik, Subhash, 2020. "Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical model," Technology in Society, Elsevier, vol. 61(C).
    12. Bueno, Adauto & Goyannes Gusmão Caiado, Rodrigo & Guedes de Oliveira, Thaís Lopes & Scavarda, Luiz Felipe & Filho, Moacir Godinho & Tortorella, Guilherme Luz, 2023. "Lean 4.0 implementation framework: Proposition using a multi-method research approach," International Journal of Production Economics, Elsevier, vol. 264(C).
    13. 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).
    14. Valeria Cirillo & Matteo Rinaldini & Jacopo Staccioli & Maria Enrica Virgillito, 2023. "Trade unions' responses to Industry 4.0 amid corporatism and resistance," PSL Quarterly Review, Economia civile, vol. 76(305), pages 91-120.
    15. 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.
    16. Assadej Vanichchinchai, 2023. "The relationships between soft and hard factors of the Toyota way: a socio-technical perspective," Operations Management Research, Springer, vol. 16(2), pages 768-779, June.
    17. Juliana Salvadorinho & Leonor Teixeira, 2021. "Stories Told by Publications about the Relationship between Industry 4.0 and Lean: Systematic Literature Review and Future Research Agenda," Publications, MDPI, vol. 9(3), pages 1-20, July.
    18. Gábor Szabó-Szentgróti & Bence Végvári & József Varga, 2021. "Impact of Industry 4.0 and Digitization on Labor Market for 2030-Verification of Keynes’ Prediction," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    19. Soni, Gunjan & Kumar, Satish & Mahto, Raj V. & Mangla, Sachin K. & Mittal, M.L. & Lim, Weng Marc, 2022. "A decision-making framework for Industry 4.0 technology implementation: The case of FinTech and sustainable supply chain finance for SMEs," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    20. Fawaz M. Abdullah & Abdulrahman M. Al-Ahmari & Saqib Anwar, 2023. "Analyzing Interdependencies among Influencing Factors in Smart Manufacturing," Sustainability, MDPI, vol. 15(4), pages 1-19, February.

    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:gam:jsusta:v:12:y:2020:i:21:p:8757-:d:432742. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.