Digital technologies as lean augmentation: Preliminary study of Japanese Automotive manufacturers

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Abstract:

Purpose
There are growing interests in a new wave of digital technologies (known as Industry 4.0, smart manufacturing, etc.) in the Japanese automotive industry, where lean is the dominant production paradigm. According to Buer et al. (2018), there is more literature studying how digital technologies support lean practices, but fewer works examining if lean production supports the successful implementation of digitalisation. How do Japanese automotive manufacturers interpret digitalisation potentials? Which digital technologies do they attempt to employ in what way? This study aims to explore how automotive-related manufacturers in Japan do (or do not) embrace digital technologies and to build working hypotheses for further research about the interplays between digitalisation and lean production.

Design
Since the intensive use of digital technologies in the production system is a relatively new phenomenon, we employed a multiple-case research design. The cases were selected based on theoretical sampling. The cases include two car manufacturers and five part suppliers, three of whom are keiretsu suppliers and the remaining are independent ones. The extent of digital technology introduction varied among cases. We loosely defined the ‘digital technologies’ as the usage of sensors, radio-frequency identification, cyber-physical system (CPS), artificial intelligence (AI), and so forth. The semi-structured interviews with company executives, plant managers, production engineers, and shop-floor managers, as well as guided plant tours (when available), were conducted from 14 to 21 November 2019. We also used secondary data sources, including company websites, brochures, and business publications (e.g., newspapers, business magazines, and books).

Findings
We classified the usage of digital technologies by the case firms into three domains: operations, continuous improvements (kaizen), and human resource development (HRD). The operations were further categorised into 1) processing, 2) assembly, 3) inspection, 4) inventory and logistics, 5) maintenance, and 6) production planning and control. Kaizen activities were distinguished into 1) data collection, 2) analysis, 3) solution generation, and 4) implementation. We sub-categorised the HRD as 1) HRD by the digital technologies and 2) HRD for the digital technologies.
Major findings of the case research are summarised as follows.
First, in the operations domain, the most commonly observed use cases of the digital technologies were 1) part processing, 3) inspection, and 5) maintenance. However, the digitalisation often took place at a specific machine or process on a stand-alone basis. Digitalisation in 2) assembly 4) inventory and logistics, and 6) production planning and control tasks were relatively low. To address the increasing complexity of production processes, investigated firms preferred conventional practices and techniques (e.g., heijunka, kanbans, pre-set parts supply, commonisation of the production process, etc.) rather than using digital technologies.
Second, regarding kaizen activities, 1) automated data collection and 2) data analysis (visualisation) were most commonly implemented usages (six out of the seven cases). Digital technologies were regarded as a means to make the data collection and analysis easier and faster to let employees focus on 3) solution generation and 4) implementation tasks.
Third, there was only two case that uses digital technologies (e.g., motion capture technology, CPS, and AI) for HRD. Regarding HRD for digitalisation, many of the case firms opted to have the existing plant and shop-floor engineers learn about the new technologies. IoT/AI specialists, if any, collaborated with plant managers and engineers by providing technical supports, but did not take a leading position in the digitalization initiatives.
Finally, digitalisation projects were implemented by plant-level managers and engineers. The planning-doing-checking-actions cycles were conducted bottom-up. It is noteworthy, however, that the digitalisation was initiated top-down. In the case of suppliers, close interactions with particular carmakers (keiretsu) seemed to provide motivation (or pressure) to undertake digitalisation.

Implications
The case firms selectively introduced digital technologies to support their existing production systems. For example, various types of sensors were used to monitor and keep track of production activities as a time-compressing tool for operations and kaizen. LCD andons, tablets, and smartphones were employed to achieve paper-less shop floors. Unmanned parts delivering systems were invented to enhance pull logistics. Some of these technologies were novel to the case firms, but their usage was in line with the lean principle. The case firms seem to regard the digitalisation as a means to augment lean production capabilities.
This can be explained by the facts that in many case firms, the implementation of digitalisation was championed by upper-level management but conducted by plant managers, production engineers, and shop-floor engineers. Because their interests in new technologies are rooted in factory- or shop floor-level production problems, their search for the usage of digital technologies will likely be anchored to the existing production paradigm. Provided that a firm’s resources and cognitive capability are limited, the firm’s established organizational structure and processes will affect the allocation of resources and provision of attentions toward the digitalisation. Since our study is based on limited cases, we need further investigation to discover more robust logic and evidence that repeatedly appear across cases.
The pros and cons of the incremental approach toward digitalisation should also be examined. In many case firms, they did not seem to have a grand vision on digitalisation; but they conduct an experimental digitalisation in a specific machine or process to establish a small successful use case, and then roll out in other machines, processes, or plants. This may be an efficient way to enhance the existing production system, but may not lead to a breakthrough in production.

References
Buer, S. V., Strandhagen, J. O., and Chan, F. T. S. (2018) “The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda,” International Journal of Production Research, 56(8), 2924-2940.