AIBIZ (CEO Ha Seung-jae), a specialist in AI (artificial intelligence)-based manufacturing process diagnostics, and Seoul Finetech, a fine chemical manufacturer, formed a consortium and were finally selected for the Ministry of SMEs and Startups' '2025 Government General-Type Smart Factory Implementation Support Program.' The program is part of a policy to strengthen the manufacturing innovation competitiveness of small and mid-sized manufacturers. Its core goal is to use ICT (information and communication technology) to integrate the entire manufacturing chain, including △design △production △quality △sales, and make processes more efficient. The 'AIBIZ-Seoul Finetech Consortium' presented a strategy centered on an AI solution capable of △real-time process anomaly detection △quality prediction △automated equipment integration. Going forward, it plans to build an integrated sensor- and controller-based system linked to the intelligent AI solution, making product design and production processes more efficient. Seoul Finetech is a fine chemical manufacturer that produces rubber compound materials (CMB/FMB) for automotive parts. It has been pursuing smart factory adoption to resolve recurring process deviations and quality defect problems. AIBIZ plans to provide a system based on its AI platform 'DutchBoy'. Accordingly, time-series data from the rubber compounding process will be collected and deep learning analysis applied, making it possible to detect anomalies in real time and analyze their causes. Unlike conventional after-the-fact inspection, the system is characterized by immediately detecting anomalies during the process, analyzing their causes, and enabling quick responses. AIBIZ said it will develop the system with a focus on quality stability and production efficiency. AIBIZ CEO Ha Seung-jae said, "Drawing on our technology accumulated in semiconductors, secondary batteries, and more, we plan to build a precision diagnostic system suited to the rubber compounding process, which involves high repeatability and variability," adding, "Through this project, we will prove the effectiveness of AI process diagnostics in the automotive parts manufacturing industry." He added, "We will advance AI solutions specialized for diverse manufacturing environments to lead digital transformation across industry."