The Ministry of SMEs and Startups (MSS) said on the 26th that it will share the outcomes of the Smart Manufacturing Innovation Technology Development project, which it is pursuing with the Ministry of Science and ICT to support advanced smart manufacturing capabilities for small and medium-sized enterprises, and will hold an outcome-sharing event to spread the results on factory floors.
The event was held as part of the Smart Manufacturing Innovation Technology Development Project (R&D), a large inter-ministerial collaboration carried out by the Ministry of SMEs and Startups (MSS) and the Ministry of Science and ICT. The project will run for five years from 2022 to 2026 with a total budget of about 421.3 billion won, and supports three strategic areas—advanced manufacturing, flexible production, and on-site application—to advance smart manufacturing innovation and strengthen the competitiveness of smart factory solution providers.
In particular, as the advanced manufacturing and flexible production areas conclude at the end of this year, strong R&D outcomes are expected, and a session has been prepared to reward and encourage outstanding small and medium-sized enterprises and research-performing institutions.
At the presentation of best practices in the advanced manufacturing field, Cho Ki-chang, head of Dworld, will introduce outcomes that established the foundation for the digital transformation of inspection processes and developed a textile fabric defect vision inspection system using Deep Learning, securing international competitiveness. In addition, Son Ji-yeon, Deputy Minister at the Electronics and Telecommunications Research Institute, will introduce technology that integrates AI and digital twins into quality inspections that were previously based on visual checks and manual work to improve accuracy, and enables real-time analysis of process load rates and overall factory productivity through simulation.
As a presenter in the flexible production field, Kim Byeong-hee, head of VMS Solutions, will share know-how on succeeding in R&D projects, including the development and commercialization of SME-tailored APS SaaS through the development of cloud-based customized APS service technology.
R&D-performing corporations carrying out various smart manufacturing R&D projects will share their R&D experiences, and inter-project technology exchanges to accelerate commercialization, such as expert consulting, will also take place.
At the Smart Manufacturing Innovation Merit Awards ceremony, a total of 12 commendations will be presented to corporations and research-performing institutions that contributed to the "advanced manufacturing" and "flexible production" fields, including four Minister of Ministry of SMEs and Startups (MSS) commendations, two Minister of Ministry of Science and ICT commendations, four Smart Manufacturing Innovation Promotion Group head commendations, and two Information and Communication Technology Planning and Evaluation Institute head commendations.
Kwon Sun-jae, regional corporate policy director at the Ministry of SMEs and Startups (MSS), said, "We have continuously pursued projects to spread AI- and data-based approaches to domestic manufacturing sites, and we will prepare concrete support measures—such as follow-up R&D and non-R&D—that can serve as a primer to secure the competitiveness of small and medium-sized enterprises in the era of AI transformation."
Park Tae-wan, director general for information and communication industry policy at the Ministry of Science and ICT, said, "Korea, as a traditional manufacturing powerhouse, can advance its manufacturing capabilities by integrating technologies such as AI models and software, and smart manufacturing centered on small and medium-sized enterprises is important to support this." He added, "As a key solution that can revolutionize productivity on manufacturing sites, physical AI will be actively supported by the Ministry of Science and ICT through the establishment of data pipelines to internalize tacit knowledge on factory floors, along with securing world model-based technologies that understand physical laws and verify real-world applications."