Beyond Industry 4.0 – Integrating Lean, Digital Technologies and People

Closes:

Guest editors

Prof. Alejandro G. Frank ([email protected]) - Federal University of Rio Grande do Sul, Brazil.

Prof. Giuliano A. Marodin ([email protected]) – University of South Carolina, USA.

Prof. Moacir Godinho Filho ([email protected]) – EM Normandie Business School, Metis Lab, France & Federal University of São Carlos, Brazil

Prof. Matthias Thürer ([email protected]) – Jinan University, China
 

Background

The growing proliferation of digital technologies worldwide has been acknowledged as a new age called the Fourth Industrial Revolution (Meindl et al., 2021). Given the need to increase gross domestic products and thus productivity, governments have created technology programs such as Industry 4.0 and Smart Manufacturing to enhance the digital transformation of operations and production activities in this context (Koh et al., 2019). This transformation is driven by digital base technologies such as the Industrial Internet of Things (IIoT), Cloud Computing, Big Data Analytics, and Artificial Intelligence (AI) (Frank et al., 2019), and new digital capabilities necessary to cope with technology adoption (Sousa-Zomer et al., 2020).

Although this digital transformation can increase productivity and flexibility, it can also create tensions with human-centered production systems, such as lean production, which is one of the dominant management paradigms in the industry nowadays (Dornelles et al., 2021; Cagliano et al., 2019). Unlike technology-driven management pardigms, lean emphasizes continuous improvement driven by workers, learning and leadership (Tortorella et al., 2018; Åhlström et al., 2021). Even the efficiency based view of lean (e.g. Hopp and Spearman, 2021) emphazises management principles that can, and often must, be operationalized without information technologies. In this lean context, technology should help organize and improve work processes and support workers in solving problems to reduce waste in value creation (Cifone et al., 2021). But how can this be done?

Lean has been described as a socio-technical system, and recent studies suggest that Industry 4.0 should be analyzed from a socio-technical perspective and include workers and organizational issues (Marcon et al., 2021). New perspectives have also enhanced the role of digital technologies for workers and the organizational system. This includes Industry 5.0 from the European Commission, which enhances the social aspects of the manufacturing technology models, and the Smart Working view of Industry 4.0, which considers the valorization of digital technologies for workers, becoming the worker a target of digital technology application (Cagliano et al., 2019; Dornelles et al., 2021; Meindl et al., 2021; Frank et al., 2019).  Consequently, there is an urgent need for more research on how digital technologies will be incorporated into workers' daily routines (Meindl et al., 2021; Senoner et al., 2021). Work routines are the essence of management concepts, such as lean, but do they remain applicable within Industry 4.0? (Åhlström et al., 2021). There is also an issue of legitimization and reputation (Holweg et al, 2022): Will workers accept a loss in autonomy and non-human decisions? Answering these questions is essential since it is well-known that Industry 4.0 models are oriented to create autonomous production systems based on AI tools that may not necessarily focus on workers (Kagermann et al., 2013; Dalenogare et al., 2018).

The literature on Industry 4.0 and lean has been predominantly optimistic about their integration (Cifone et al., 2021; Rosin et al., 2020; Tortorella et al., 2019). It assessed Industry 4.0 technologies that support lean, and considered Industry 4.0 maturity models that acknowledge some of lean’s organizational aspects. It appears that lean and the implementation of new technologies go hand in hand, but is there true integration? The literature clearly lacks evidence. Both concepts represent an interconnected arrangement of techniques and practices (Åhlström et al., 2021; Frank et al., 2019), and there is an intrinsic complexity in both that deserves more research on implementations. We look for more robust theoretical developments that explain how Industry 4.0 technologies and lean practices can be effectively combined to enhance operational performance.

We are interested in contributions that take a micro-perspective focusing on actual implementations in practice. For example, Huang et al. (2021) recently showed how lean can enable additive manufacturing to compete with mold-injection on costs, something previously considered impossible. At the same time, we look for contributions that adopt theories to explain evidence from practice. As for most lean research, there is a lack of theory in the literature on lean and Industry 4.0. We are specifically interested in papers that create middle-range theories, i.e. theories that lie between the working hypotheses that evolve in abundance during day-to-day research and the all-inclusive systematic efforts to develop a unified theory that will explain all the observed uniformities (Merton, 1949). Furthermore, we also aim for Impact Pathway Papers that can provide new avenues for research in the Industry 4.0 domain, considering the intersection between Lean, Digital Technologies, and People.
 

Objectives

Organizations in practice cannot neglect that a digital transformation is taking place. However, they also need management concepts such as lean, since new technology itself is just an enabler. Despite the apparent need to integrate lean and new technology programs such as Industry 4.0 and Smart Manufacturing, there is a lack of research on how this can be done. Existing research gathered ample evidence that lean and Industry 4.0  are implemented and used simultaneously. Nevertheless, there is little evidence that there is true integration, how this integration is achieved, and what is the outcome.

This Special Issue has two general objectives:

  • To provide empirical evidence on effective integration between lean and Industry 4.0;
  • To provide the theoretical underpinning explaining this evidence, for example, why integration is sometimes achieved and sometimes not.

Specific objectives include:

  • Testing competing empirical models to better explain the relationship between Industry 4.0 and lean production.
  • Using OM theories to interpret convergencies, divergencies, and paradoxes in integrating Industry 4.0 and lean.
  • Proposing implementation strategies for Industry 4.0 and lean.
  • Understanding the implications for workers and the way work is done, when AI and other advanced digital tools gain control
  • Expanding the frontiers of Lean and Digital Transformation into other fields like healthcare and supply chain management. 
  • Proposing Impact Pathways for new frontiers in the intersection between Lean, Digital Technologies, and People.
     

Potential Topics

This special issue sets out to prepare the grounds for integrating lean and Industry 4.0. We call specifically for in-depth qualitative studies that focus on implementations. This includes case studies, action research, intervention-based research, field studies and design science. We are interested in existing solutions and new solutions. We are also interested in empirical papers that develop new theories or test theories. But these studies should be thoroughly grounded in real implementations, and there should be clear support for causal links, for example using directed acyclical graphs or advanced econometric techniques for a causal interpretation. Potential research questions include:

  • How does new technology impact workers’ work routines?
  • Will lean workers accept non-human decisions?
  • How can lean contribute to unlock the potential of new digital technologies?
  • How can new digital technologies enhance lean?
  • What strategies can managers adopt when encountering paradoxes when jointly implementing lean and Industry 4.0?
  • How can lean and Industry 4.0 be integrated in complex and dynamic environments, such as healthcare and supply chains under uncertainties?
  • How should Industry 4.0 and lean programs be implemented in practice?
  • What problems do companies that implement Industry 4.0 and lean face, and how can they be addressed?
  • What solutions exist, and what solutions can be designed to integrate lean and Industry 4.0?
     

Key Dates: 

Submissions Open: 1st January 2023

Submissions Deadline: 30 April 2023

Expected Publication: October 2023
 

Connected conferences and workshops

To be confirmed - This special issue will be linked to special tracks and paper development workshops that will be communicated in due time. Tentative meeting points for all authors interested to submit to the special issue are the following:

  • Webinar “Meet the Guest Editors”, September 2022
  • EurOMA’S and POMS College of Operational Excellence workshops
     

Review process

The review process will consider the following steps:

The review process will follow a continuous flow up to the deadline of the call for papers to accelerate the review process.

  1. The guest editors will conduct a first screening of the submitted papers to ensure the quality of the articles sent for review.
  2. Those articles that pass the first screening will be sent to the reviewers. The guest editors will select reviewers from their network (co-authors, colleagues from the EurOMA and IJPE board in which Prof. Frank participates, and colleagues from the guest editors' research network) and from the IJOPM's list of reviewers.
  3. After receiving the feedback from the reviewers, the team of guest editors will evaluate the submitted papers and decide if they are electable for improvement aiming for potential publication or not. We aim to send the reviewers again only those papers that present high chances of being part of the special issue.
  4. The guest editors will ensure the last stage of final improvements with editorial requests to ensure the quality of the final articles that will be published.
     

About the guest editors

Alejandro G. Frank, Ph.D. is an Associate Professor at the Department of Industrial Engineering of the Federal University of Rio Grande do Sul (UFRGS), the Director of the UFRGS Organizational Engineering Group, and a Research Affiliate at the MIT Industrial Performance Center, Massachusetts Institute of Technology. He is also member of the board of the European Operations Management Association (EurOMA), member of the editorial board of the International Journal of Production Economics (Elsevier) and of the European Journal of Innovation Management (Emerald), and Regional Editor of the Journal of Knowledge Management (Emerald).  He received Ph.D. and M.Eng. degrees in Industrial Engineering from UFRGS, Brazil, and a B.Eng. degree in Industrial Engineering from the National University of Misiones (UNaM), Argentina. He has been a visiting scholar at the Massachusetts Institute of Technology (USA), and at Politecnico di Milano (Italy). His research is devoted to the interface between operations and technology management, with emphasis on digital transformation, Industry 4.0, and new business model innovation in manufacturing firms. His research has been published in academic journals including the International Journal of Operations and Production Management, Research Policy, International Journal of Production Economics, Supply Chain Management, International Journal of Production Research, R&D Management, and others. 

Giuliano Marodin is the Continental Chair Professor in Operations & Supply Chain at the Moore School of Business at the University of South Carolina. He received his PhD, his Master’s degree in industrial engineering and a BBA degree from the Federal University of Rio Grande do Sul in Brazil, where he also worked as an adjunct professor for the Department of Industrial Engineering and the Business School. He was a visiting professor at the Department of Management Sciences, The Ohio State University for the academic year of 2014/2015. Since 2002, he has worked as a consultant implementing lean production systems in firms from several sectors, also as a partner of Lean Enterprise Institute in Brazil. His research interests are in lean production and service implementation journeys, and operational and supply chain excellence, and has appeared in the International Journal of Operations and Production ManagementInternational Journal of Production Economics, Supply Chain Management, International Journal of Production Research, and others. 

Moacir Godinho Filho is a Full Professor in the Department of Supply Chain Management, Operations Management and Decisions Sciences at EM Normandie Business School (France) and an affiliated professor in the graduate program in Industrial Engineering at Federal University of São Carlos (Brazil). He received his BS from the Federal University of São Carlos, his MBA from Fundacão Getulio Vargas (Brazil), MS, and his PhD from the Federal University of São Carlos. Professor Godinho Filho was a visiting professor in the Department of Industrial and Systems Engineering, University of Wisconsin at Madison (USA), in the Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University (USA), and also at Kellogg Business School - Northwestern University (USA). Professor Godinho Filho has published more than 120 papers in journals with a selective review process in several high quality journals such as: International Journal of Operations & Production Management, Production and Operations Management, International Journal of Production Economics, International Journal of Production Research, Annals of Operations Research, and many others. His areas of interest are production planning and control, Lean Production, lead time reduction, logistics, industry 4.0, sustainable operations and supply chain management.

Matthias Thürer is Distinguished Professor in Management Science and Engineering at the School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai, PR China). Simple control for complex shops is one of Matthias’ main research interests. He contributed to the improvement, simplification and integration of material flow control systems, and their integration with Industry 4.0. He is a board member of the POMS Operational Excellence college since 2021. His research has appeared in the International Journal of Operations & Production Management, Production and Operations Management, Journal of Operations Management, European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, and others.

 

References

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Cagliano, R., Canterino, F., Longoni, A., & Bartezzaghi, E. (2019). The interplay between smart manufacturing technologies and work organization: the role of technological complexity. International Journal of Operations & Production Management.

Cifone, F. D., Hoberg, K., Holweg, M., & Staudacher, A. P. (2021). ‘Lean 4.0’: How can digital technologies support lean practices?. International Journal of Production Economics241, 108258.

Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of production economics204, 383-394.

Dornelles, J., Ayala, N. F., & Frank, A. G. (2022). Smart Working in Industry 4.0: How digital technologies enhance manufacturing workers' activities. Computers & Industrial Engineering163, 107804.

Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics210, 15-26.

Holweg, M., Younger, R., & Wen., Y. (2022). The Reputational Risks of AI. California Management Review

Hopp, W. J., & Spearman, M. S. (2021). The lenses of lean: Visioning the science and practice of efficiency. Journal of Operations Management67(5), 610-626.

Huang, Y., Eyers, D. R., Stevenson, M., & Thürer, M. (2021). Breaking the mould: achieving high-volume production output with additive manufacturing. International Journal of Operations & Production Management.

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Merton, R.K., (1949), “On sociological theories of the middle rangefrom Robert K. Merton, Social Theory and Social Structure, New York: Simon& Schuster, pp. 39-53 

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Tortorella, G. L., de Castro Fettermann, D., Frank, A., & Marodin, G. (2018). Lean manufacturing implementation: leadership styles and contextual variables. International Journal of Operations & Production Management.