Kolon Benit: “Combining On-Site Data and Worker Experience at Isu Chemical, Sewoo Industry, and Sewoo Advanced Materials With AI”

Kolon Benit announced that it has selected Isu Chemical, Sewoo Industry, and Sewoo Advanced Materials as participating companies in the “Support Project for Building a Win-Win AI Transformation (AX) Leading Model” and will fully move ahead with the project. The initiative will focus on combining on-site data and worker experience at Isu Chemical, Sewoo Industry, and Sewoo Advanced Materials with AI.

The win-win AX leading model support project is based on the manufacturing innovation capabilities of large companies. The project aims to support the enterprise-wide AX transformation of small and mid-sized companies and to build leading models that can generate and spread results.

The purpose of the project is not simply to help individual companies introduce equipment, but to prepare an execution model that peers in the same industry can reference. As the lead organization, Kolon Benit will oversee the overall project, while the Korea Productivity Center will participate as a partner organization.

Sewoo Industry produces sound-absorbing and noise-reducing components such as automotive wheel guards and undercovers. Sewoo Advanced Materials produces fiber materials using recycled raw materials. Isu Chemical produces LAB (linear alkylbenzene) and NP (normal paraffin), key raw materials for detergents, and is expanding its high value-added, eco-friendly specialty chemicals business based on LAB and NP.

Kolon Benit, Sewoo Industry, and Sewoo Advanced Materials will jointly pursue a direction that combines accumulated on-site data and worker experience with AI. Through this, the three companies will advance process operations and the analysis of abnormal causes, while also pursuing data-driven decision-making and business innovation.

Against this backdrop, Kolon Benit will establish a system for the production lines of Sewoo Industry and Sewoo Advanced Materials. The system will include AI quality prediction linked to process and quality data, equipment predictive maintenance, and process-condition optimization.

For Sewoo Industry, AI quality prediction models and digital twin-based simulations will be introduced for the nonwoven fabric production line. This will allow the company to identify deviations in fabric thickness and density in advance and establish a predictive maintenance system based on anomaly detection for key equipment.

For Sewoo Advanced Materials, Kolon Benit will establish an automated recommendation system for optimal conditions, real-time quality prediction, anomaly detection, equipment predictive maintenance, and an integrated monitoring and control system for the core processes of raw material feeding, drying, and spinning.

Ultimately, the goal is to standardize on-site process and quality judgment criteria based on data. In addition, the project will also push ahead with improving quality stability and building a production environment that can respond proactively to equipment abnormalities.

Isu Chemical will build an AI operations support system tailored to continuous chemical processes. To do so, it will integrate process control, equipment history, and production performance data, and link the integrated data into a single standard system. Time-series AI will then be applied to detect signs of process abnormalities in advance and recommend optimal operating conditions in real time.

Through this project, Kolon Benit plans to flesh out a manufacturing AX execution model. Kolon Benit's approach is not to preselect and supply a specific solution, but to define tasks after diagnosing the site. It then identifies companies with the relevant technologies and references, forms a consortium with those companies, and carries out the project in a structure in which it takes responsibility through completion of the deployment.

In this project, Kolon Benit will establish standards for diagnosis, sourcing, and project management. In this process, it will leverage a network of technology companies, including AI Alliance participants and partner companies. The system and standards established in this way are planned to be applied continuously to future projects.

Kolon Benit will also provide win-win support for Sewoo Industry and Sewoo Advanced Materials. The support includes establishing an AX transition roadmap, guidance on data standardization, providing AI and data infrastructure, and offering training for current employees. It will also expand the period of free maintenance support after deployment.

Jang Jae-yong, head of Kolon Benit's DX Division, said the company plans to continue participating in government demonstration projects, expand application cases by industry, and extend the execution model secured in manufacturing to other areas. He said the company plans to establish an execution framework spanning on-site diagnostics, technology partner composition, and project management, and explained that it has accumulated on-site experience, data, and AI capabilities through the group's manufacturing affiliates. He added that, based on that accumulated experience and capabilities, the company plans to expand its manufacturing AX business.

Source: TECHWORLD · Lee Gwang-jae
Original: https://www.epnc.co.kr/news/articleView.html?idxno=408363

References

• https://www.epnc.co.kr/news/articleView.html?idxno=408363