– The 2nd year workshop of the AI ​​Autonomous Manufacturing Pilot Project hosted by the Ministry of Trade, Industry and Energy

AI-based process improvement for cathode material quality prediction and productivity innovation.

EcoPro aims to increase productivity by 30% by 2027 through quality prediction and real-time data collection based on artificial intelligence (AI).

CHEONGJU, South Korea — October 10, 2025 —  EcoPro recently announced that it held a workshop for the second year of the AI ​​Autonomous Manufacturing National Project, which was attended by the Electronics and Telecommunications Research Institute (ETRI), Korea Textile Machinery Convergence Research Institute (KOTMI), DL Information Technology, Smile Information Technology, and Chungbuk Technopark. This event was organized to share the achievements of the ‘AI Autonomous Manufacturing Leading Project ‘ that the Ministry of Trade, Industry and Energy and the Korea Institute of Industrial Technology Evaluation and Planning have been carrying out since last year and to discuss the second year’s promotion plan.

EcoPro plans to use this second-year workshop, building on the research findings from the first year, to fully apply AI to the group’s manufacturing processes and productivity improvements. Through this first-year research, EcoPro secured the data necessary for kiln quality prediction and developed an AI quality prediction model with a prediction accuracy of approximately 87%.  

In the second year, the goal is to apply core technologies such as autonomous control of equipment and robots, AI-based quality prediction, and real-time data collection and analysis platforms to the field, converting the company’s major work systems to AI and improving work productivity by 30% by 2027. The plan is to increase the accuracy of quality prediction AI modeling to 90%.  

EcoPro BM, which is responsible for the production of cathode materials, plans to apply smart facilities to the field, such as near-infrared (NIR) sensors that can autonomously control raw material input in real time, autonomous mobile robots (AMRs) that can perform tasks in place of workers in high-temperature, dusty environments, and a crucible ( kiln vessel ) tracking system. The strategy is to automate the process and secure quality data in real time through these.

EcoPro builds a data lake ( raw data storage ) that integrates production management systems and facility data, laying the foundation for utilizing all data from manufacturing sites for AI analysis.

ETRI will advance data preprocessing technologies, including AI quality prediction modeling and key factor correlation analysis based on actual manufacturing data. MISO Information Technology and DL Information Technology will develop a data platform and data linkage and visualization system to support the integrated management and analysis of diverse process data within the group.

Lee Su-ho, head of EcoPro’s AI Innovation Lab, said, “Through this workshop, we will review the master plan for AI autonomous manufacturing and the progress of detailed tasks, and secure practical execution capabilities for AI-based process innovation and productivity improvement within the group.” He added,“ We will further strengthen our global competitiveness through AI and data-based manufacturing innovation.”

Source: EcoPro