Since the 2008 global financial crisis, traditional manufacturing powerhouses have been striving to revive the manufacturing industry. As one of these efforts, governments in many countries are adopting the introduction and spread of smart factories ...
Since the 2008 global financial crisis, traditional manufacturing powerhouses have been striving to revive the manufacturing industry. As one of these efforts, governments in many countries are adopting the introduction and spread of smart factories as one of the important industrial policies. They are creating smart factory reference models, presenting them to their manufacturers and making them to follow. The Korean government also proposed smart factory reference models by industrial sector in 2014 to encouraging Korean firms to adopt them.
The purpose of this study is to supplement the theoretical basis of the Korean smart factory model and to suggest its development direction. To achieve this objective, this study was conducted in two directions. The first analysis was to find differences between models through international comparison of smart factory reference models and to determine components applicable to Korean companies. Second, the effect of the previously derived components on the business performance of Korean companies was empirically analyzed. The purpose of this analysis was to find implications for the Korean model to supplement.
For the international comparison, Germany's RAMI4.0, US IIRA were chosen as the targets for comparison. This study was mainly conducted with literature studies about domestic and foreign academic papers and policy data of each government.
The empirical analysis was carried out on 96 smart factory companies located in the manufacturing cluster (Gyeongsangnam-do) in Korea. In the empirical analysis, the moderating effect of smart factory factors was verified in the correlation between the company's internal capability factors, external environment factors and corporate management performance. As the dependent variables of this model, BSC performance indicators such as financial, customers, process and learning indicator were set.
The results of this study can be summarized in the following four. First, the Korean reference model, unlike other foreign models, has limited interoperability due to unclear standards. Second, the Korean model does not include a business perspective, so it remains just in the expansion stage of factory automation. In other words, in the Korean model, the concepts of value stream, life cycle, and data integration are not evident. Third, it was concluded that the Korean smart factory reference model is more complementary to Germany's Rami4.0 than the US IIRA. Therefore with reference to the RAMI 4.0 model, three smart factory elements, which will be the basis of analysis, were defined: horizontal integration, vertical integration, and IT axis integration. Fourth, among above mentioned factors, the moderating effect was statistically most evident in vertical integration, which is the integration between devices. On the other hand, the effect of horizontal integration and IT axis connection elements was not clear.
The implications of this study are as follows. First of all, it seems that the Korean smart factory reference model should be redesigned based on the standard. This will serve as a basis for securing interoperability with other foreign models, Second, from the perspective of technology management, logical completeness should be improved. In other words, considering that the smart factory is not just an extension of factory automation, the concept of product life cycle and value stream should be sufficiently described. Lastly, since the integration of IT axis or data integration in the Korean model is also the most essential part of the smart factory element, it should be fully explained and the technical implementation method should be proposed.
As for the limitations of this study, it was not easy to accurately measure the moderating effect because smart factories in Gyeongsangnam-do were introduced not long ago and therefore the level of understanding about the smart factory was low. In addition, there was a limit to the normal correlation analysis due to the overall decline in corporate performance caused by the impact of COVID-19. Accordingly, there should be follow-up studies in a normal corporate environment.