Kolon Benit 为三家制造企业提供 AI 转型支持

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Kolon Benit announced on Oct. 19 that it has selected ISU Chemical, Seowoo Industrial and Seowoo Advanced Materials as participating companies in a government-backed project to establish collaborative artificial intelligence transformation (AX) models and will begin full-scale implementation.

The project is supported by the Ministry of SMEs and Startups, the Korea Technology and Information Promotion Agency for SMEs and the Korea Federation of SMEs. It aims to develop AI-based manufacturing models that can be adopted across industries by leveraging the manufacturing innovation capabilities and IT infrastructure of large and midsize companies to support enterprise-wide AX at small and midsize businesses. Kolon Benit was selected as the lead organization in July, with the Korea Productivity Center participating as a collaborating institution.

Seowoo Industrial manufactures automotive sound-absorbing and insulating components, including wheel guards and undercovers, while Seowoo Advanced Materials produces textile materials using recycled raw materials. ISU Chemical manufactures linear alkylbenzene (LAB) and normal paraffin (NP), key raw materials for detergents, and is expanding its high-value-added and environmentally friendly specialty chemicals business.

Kolon Benit said all three companies are working to combine accumulated factory data and workers’ experience with AI to improve process operations and root-cause analysis of abnormalities, while advancing data-driven decision-making and operational innovation.

Kolon Benit plans to establish AI-based quality prediction, predictive equipment maintenance and process condition optimization systems by integrating process and quality data across the production lines of Seowoo Industrial and Seowoo Advanced Materials.

At Seowoo Industrial, AI quality prediction models and digital twin simulations will be applied to nonwoven fabric production lines to identify variations in material thickness and density in advance. Major equipment will also be equipped with predictive maintenance systems based on anomaly detection.

At Seowoo Advanced Materials, the project will establish a system that automatically recommends optimal conditions for key processes, from raw material input through drying and spinning. It will also introduce real-time quality prediction, anomaly detection, predictive maintenance and integrated monitoring. The goal is to standardize process and quality assessment criteria using data, improve quality consistency and create a production environment capable of responding proactively to equipment abnormalities.

ISU Chemical, a midsize company, will introduce an AI-assisted operations system tailored to continuous chemical processes. The system will integrate process control, equipment history and production performance data into a standardized framework, use time-series AI to detect early signs of process abnormalities and recommend optimal operating conditions in real time.

AI-generated setpoints will be applied to control systems only after operators review and approve them within safe operating limits. The project will also establish predictive maintenance systems for factory equipment and real-time monitoring of energy consumption and carbon emissions.

Kolon Benit said it will take responsibility for each project from initial factory assessments and identification of requirements through consortium formation and final implementation. It will identify companies with the necessary technologies and project experience rather than prioritize its own solutions, reflecting the rapid evolution of AI technology and customer requirements.

To support this approach, Kolon Benit will draw on its network of technology companies, including members of its AI Alliance and other partners. It also plans to apply the assessment, technology sourcing and project management frameworks and standards developed through this initiative to future projects. Each project will run for one year.

Hyun-Seon, Park hspark@thelec.kr

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