Drivers for CPS Adoption in the Manufacturing Industry: Implications for Productivity Improvement

Abstract

In recent years, digitalization has significantly progressed across various industries. The manufacturing industry, in particular, has been at the forefront of this digital revolution, embracing CPS, big data, and AI technologies since "Industry 4.0" in 2011. This transformative concept envisions integrating FA devices, factories, and the entire supply chain using standardized communication protocols to create more intelligent factories. The ultimate goal of Industry 4.0 is to revolutionize productivity by promoting automated production to the maximum extent possible.

At the heart of this technological revolution is CPS, a key technology that offers numerous benefits to the manufacturing industry, including improved productivity, cost reduction, and quality enhancement through predictive maintenance of production equipment. However, preliminary research in Japan and Germany has revealed that technical factors within networks between production facilities and the complexity of transaction subsystems pose significant challenges to realizing this vision, underscoring the urgency and importance of finding a solution.

As a result, many companies find themselves in a state of passive management, unable to fully exploit the potential of CPS technology. Therefore, this study is of utmost importance, aiming to identify the technical factors impeding the progress of CPS technology. This technology is not just critical, but it's a necessity for developing smart factories and maintaining and im-proving each manufacturer's international competitiveness. The proposed solution introduces a highly versatile middleware that can effectively overcome these technical challenges, enabling companies to gain a competitive advantage and instilling confidence in CPS adoption in the manufacturing industry.