Lean production models in the era of digitization of supply chains: recapturing basic principles

Type de publication:

Conference Paper


Gerpisa colloquium. Who drives the change? New and traditional players in the global automotive sector. (2018)


Lean production models in the era of digitization of supply chains: recapturing basic principles


Zuhara Chavez
Ph.D. Student
Graduate of Integrated Frontier Sciences. Department of Automotive Science.
Kyushu University
Address: 744 Motooka, Nishi-Ku, Fukuoka, Japan 819-0395

Title: Lean production models in the era of digitization of supply chains: recapturing basic principles
Theme n°: 3
Keywords: lean production, digital supply chains, best practices, industry 4.0
Digitalization will be the most powerful driver of innovation over the next few decades and will act as the trigger of the next wave innovation. As a result, today’s value chains and business models will come under increasing pressure. Digitalization is having a highly disruptive impact on markets, the world of work and our social structures (Kagermann, 2015).
The importance of the value given to a business by investors suggests that more emphasis may need to be placed in assessing business excellence on the way in which management is increasing the value of the business and its constituent parts. This will mean examining the business models that management uses – how and why these may change over time, and how the strategy is extracted from these models (Williams et al., 2006).
From a technological point of view, lean production can be regarded as a complement to automation. Both industry 4.0 and lean production favor decentralized structures over large, complex systems and both aim for small, easy to integrate modules with the low level of complexity (Sule et al., 2018)
Current market tendencies can bring uncertainty to organizations, diverse authors highlight examples of ways to overcome the uncertainty in environments that are coping with industry 4.0, such as: explicit acknowledgment that the individual human being will continue to play an active, engaging role in manufacturing, the full integration of machinery and equipment with production management systems, the creation of organizations clusters that deal with the development of standards, i.e. communication used in a production system. The composition of these clusters should include the following: projecting and producing control systems, robots, machines and machine tools and software to support them (Magruk, 2016).
This paper aims to illustrate the tendencies of organizations and their actions towards an integrated production model that complies with the requirements of a digital supply chain and lean manufacturing. Understanding the impact and changes that organizations are experiencing will allow us to define how we can better outline the production models triggered by digitalization and new initiatives such us industry 4.0.
Research question
The aim of this paper is twofold, first to investigate to what extent are lean production models being impacted by the digitalization of supply chains, and second, how are lean practices in production models in automotive manufacturing environments being influenced by digital technologies.
The methodology is centered on exploratory research with a multi-method approach; firstly we performed a qualitative analysis on literature related to research and practitioner cases targeting production models, assessing the academic position in the topic, cases are not exclusive to Germany or Europe, as we aim for a global and objective perspective on the topic. Secondly, we present the perspective of an automotive supplier in a case study; we performed field observations that lead to understanding their current situation and degree of integration of digitalization with lean manufacturing best practices. The intention of employing a multi-method is to have a triangulation between conceptual work and real practices found in the industry.
Products may become more modern and incorporate technological changes, but manufacturing still relies on basic production techniques and industrial engineering principles, i.e., line balancing, standard work, pacemaker, the economy of movements, to develop trustworthy manufacturing systems.
Successful organizations understand that in pursuing a lean system, is not the tools but the core knowledge what brings outstanding results. In this environment, the concept of respect for people is gaining importance, when before the efforts would be targeted to adopting practices, replicating systems, implementing tools and techniques for higher results, nowadays their focus is on the creation of value with the dissemination of knowledge.
Knowledge and experience in complex manufacturing are a key asset. On the contrary to what we may think, in a world where data is available at all times through technology, their value is still acknowledged by organizations. The essence on well-established practices are a must and may not be replaced for a long period of time, for instance when challenges appear, effective and solid practices such as finding root causes and problem-solving techniques haven’t lost their value.
Practical implications
In this paper, we aimed to characterize the inclinations of organizations on the way to an integrated production model in the era of industry 4.0. Illustrating the current state may allow better targeting future research. Industry 4.0 is a relatively new topic, yet unclear for most practitioners; the tendency tells us that there is a need for further understanding of the term. Therefore it’s meaningful to study organizational needs that could arise along with its development.
Being the case study from an automotive supplier can reduce the degree of maturity in adopting contemporary practices or digital technologies. However, it can give a more realistic scenario of the average organization in terms of efforts and resources dedicated to digital technologies and how this affects or not, their operations.

Kagermann, H., 2015. Change Through Digitization—Value Creation in the Age of Industry 4.0., in: Albach H., Meffert H., Pinkwart A., R.R. (Ed.), Management of Permanent Change. Springer Gabler, Wiesbaden, London, United Kingdom., pp. 23–48.
Magruk, A., 2016. Uncertainty in the Sphere of the Industry 4.0 – Potential Areas to Research. Business, Manag. Educ. 14, 275–291. https://doi.org/10.3846/bme.2016.332
Sule, S., Alp, U., Cevikcan, E., Durmusoglu Bulent, M., 2018. Lean Production Systems for Industry 4.0, in: Industry 4.0: Managing The Digital Transformation. springer cham. https://doi.org/https://doi.org/10.1007/978-3-319-57870-5_3
Williams, R., Bertsch, B., Van Der Wiele, A., Van Iwaarden, J., Dale, B., 2006. Self-assessment against business excellence models: A critique and perspective. Total Qual. Manag. Bus. Excell. 17, 1287–1300. https://doi.org/10.1080/14783360600753737

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