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Industry 4.0 triggered by Lean Thinking: insights from a systematic literature review

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  • V. L. Bittencourt
  • A.C. Alves
  • C. P. Leão

Abstract

Lean Thinking has successfully challenged mass production practices, by providing ‘leaner’ processes and supply chains, i.e. with less waste. Industry 4.0 has become an important strategic approach in the technological change of manufacturing and others. It aims to connect the physical and virtual worlds in industrial production. With such automation associated with Industry 4.0, questions arise about the synergy between this approach and the role of Lean in this ongoing industrial revolution. Therefore, a systematic literature review was carried out in order to identify the role of Lean in this scenario. The review was conducted from 2011 to 2019 timeframe and resulted in a total of 33 papers. This review demonstrated this as an emerging research area with most of the studies published in recent years (2017–2019). A deep analysis was undertaken to understand the Lean effect as a trigger for Industry 4.0. Main findings from a 15 out of the 33 papers revealed elements and facts found in sentences of such papers that act as this trigger. Additionally, a words count indicated that management, processes and people were the most cited words by the 15 papers, reinforcing the role of these key players in the companies’ transformation.

Suggested Citation

  • V. L. Bittencourt & A.C. Alves & C. P. Leão, 2021. "Industry 4.0 triggered by Lean Thinking: insights from a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1496-1510, March.
    • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:5:p:1496-1510
    DOI: 10.1080/00207543.2020.1832274
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    Cited by:

    1. 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).
    2. Zeba, Gordana & Dabić, Marina & Čičak, Mirjana & Daim, Tugrul & Yalcin, Haydar, 2021. "Technology mining: Artificial intelligence in manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 171(C).

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