EcoPro (086520.KS) said Friday it is pursuing a companywide artificial intelligence transformation (AX) that applies AI across manufacturing operations and research and development (R&D). The company plans to introduce AI to all business divisions by 2028, its 30th anniversary.
EcoPro has decided to pursue a "three-stage roadmap" to transform into an AI autonomous-execution company. This year, it will build the foundation through companywide data standardization and pilot projects, and expand the scope of application next year. By 2028, the strategy calls for introducing AI to all affiliated companies at home and abroad, leaping toward an AI-driven company that operates its overall work on an AI basis.
First, the company plans to integrate AI into R&D to cut the time from product development to mass production by 50%. AI trained on experimental data will predict material properties and derive optimal experimental conditions, automating large-scale experimental work. Physical AI will be introduced at production sites to build autonomous manufacturing plants and autonomous laboratories. Robots will take over hazardous tasks, and the on-site management system will be converted into an AI autonomous-control environment based on a data platform and machine learning.
EcoPro plans to build an AI autonomous-control mother line on its precursor and cathode material sintering lines to raise manufacturing productivity by 30%. Through AI-based quality control with 95% accuracy, it will analyze and predict the causes of defects, while expecting to cut energy consumption by 15 to 20% through a predictive maintenance system. EcoPro BM's Hungary subsidiary, completed last year, plans to introduce AI-based robots to advance work automation and improve productivity.
"Beyond innovating traditional manufacturing methods, we are now in an era where collaboration with AI is essential," said Lee Soo-ho, vice president of EcoPro's AI Innovation Office. "By building an environment in which employees can use AI as naturally as a colleague, we plan to improve operational efficiency across the field."
