Kolon Benit Begins Building Manufacturing 'AX Leading Model'... Selects 3 Companies Including Isu Chemical

Kolon Benit said on the 19th that it will establish a manufacturing AX execution framework to apply AI to manufacturing sites in the automotive parts, textile materials, and petrochemical sectors. The framework includes on-site diagnosis, technology company selection, and project management.

Kolon Benit said it had selected 3 companies as adopters of the 'Win-Win AX Leading Model Construction Support Project' to move ahead with the business in earnest. The selected companies are Isu Chemical, Seowoo Industrial, and Seowoo Advanced Materials.

The 'Win-Win AX Leading Model Construction Support Project' is designed to support small and midsize companies, as well as mid-sized companies, in their enterprise-wide AX transformation based on the manufacturing innovation capabilities of large corporations. The project aims to create results and build a leading model that can be scaled and spread.

A distinguishing feature of the project is that it is not limited to introducing equipment at individual companies. Its purpose is to establish an execution model that peers in the same industry can reference, and the lead organization is Kolon Benit, with the Korea Productivity Center as a collaborating organization.

Kolon Benit will establish an AI quality prediction system, equipment predictive maintenance system, and process condition optimization system that link process and quality data for Seowoo Industrial and Seowoo Advanced Materials production lines. For Seowoo Industrial, it will apply an AI quality prediction model and digital-twin-based simulation to the nonwoven fabric production line to identify deviations in fabric thickness and density in advance, and establish a predictive maintenance system based on anomaly detection for major equipment. For Seowoo Advanced Materials, it will establish an automatic recommendation system for optimal conditions across key processes from raw material input to drying to spinning, as well as a real-time quality prediction system, anomaly detection system, predictive maintenance system, and integrated control system.

Kolon Benit will standardize on-site process and quality judgment criteria based on data. The goal is to improve quality stability and establish a production environment that can respond proactively to equipment abnormalities.

Isu Chemical is a mid-sized company, and Kolon Benit will establish an AI operation support system tailored to continuous chemical processes for Isu Chemical. To do so, it will integrate process control, equipment history, and production performance data, and push ahead with linking the integrated data to a single standard framework. It will then use time-series AI to detect signs of process abnormalities in advance and recommend optimal operating conditions in real time.

Kolon Benit said it plans to make the manufacturing AX execution model more concrete through this project. To that end, it chose a project structure that excludes predesignating and supplying specific solutions, defines tasks after on-site diagnosis, identifies companies with the relevant technologies and references to form a consortium, and takes overall responsibility for the project until completion of construction.

Kolon Benit judged that, given the rapid changes in AI technology and customer demand, quickly combining the best technology for the site would be more effective than prioritizing its own products. Accordingly, it decided to leverage a network of technology companies, including participants and partners in the Kolon Benit AI Alliance.

Kolon Benit plans to continue applying the diagnosis, sourcing, and project management systems and standards established through this project to future projects. Jang Jae-yong, head of Kolon Benit's DX division, said the company plans to continue participating in government demonstration projects and expand case studies by industry, while also expanding the execution model secured in manufacturing to other areas. He added that the company will push ahead with establishing an execution framework that leads from on-site diagnosis to technology partner formation and project management, and will expand its manufacturing AX business by combining data and AI capabilities through field experience accumulated across the group's manufacturing affiliates.

Source: IT DAILY · Yang Seung-gap
Original: https://www.itdaily.kr/news/articleView.html?idxno=242286

References

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