The 'AI Convergence Regional Specialized Industry Support Project' of the Ministry of Science and ICT and the National IT Industry Promotion Agency (NIPA) will complete its two-year journey this year. Six regions were selected, including Daegu Transportation Equipment and Machinery Materials and Parts, Chungnam Eco-Mobility, Gyeongnam Auto Parts, Daejeon Digital Water Industry, Gwangju Medical and Healthcare, and Jeju Green Energy. It is an ambitious project aimed at strengthening the local economy, which is the root of the Korean economy, and laying the foundation for a great digital transformation by reorganizing it into a futuristic industry by integrating AI technology into regionally specialized industries. We will look at how regional specialized industries are changing through the convergence of AI, and introduce the achievements over six sessions. 〈Editor's Note〉

Daegu City and Daegu Techno Park Consortium secured KRW 3.73 billion (total project cost KRW 6.75 billion) in national funding in the field of transportation equipment and mechanical materials and components in the 'AI Convergence Regional Specialized Industry Support Project' of the Ministry of Science and ICT and NIPA, with a total investment of KRW 34.1 billion. .

Local transportation equipment and mechanical materials and parts companies that participated in the project as demand companies are showing anticipation, saying that it has been an opportunity to build a foundation for sustainable development based on new technology. Supplier companies that have developed AI technology have developed AI services using actual data from industrial sites that are difficult to access, opening up new possibilities and gaining early business opportunities that connect industry and AI. It is a win-win strategy for supply and demand companies.

Daegu Techno Park Director Do Geon-woo said, “We plan to support not only auto parts companies but also various local companies to use AI technology to increase the added value of existing businesses and to continue linked projects to improve productivity.”

◇ Computer Mate develops AI solution to minimize defects in actuator line at chassis factory

Computer Mate (CEOs Sang-in Seo and Sung-ho Kim) developed an AI solution that analyzes the correlation between data and defect rates and uses AI to learn optimal conditions to minimize defect rates. Gyeongchang Industrial (CEO Son Il-ho) used this to successfully minimize defects occurring in the actuator line of the chassis factory.

Computer Mate collects and monitors conditional information on the operation status of actuator equipment in preparation for sudden breakdowns or defects in actuator production/manufacturing equipment and inspection equipment. This allowed preventive inspection and preemptive measures to be taken. Not only can it reduce worker dependence, but it also reduces defects that occur in the manufacturing process. Gyeongchang Industrial expects to increase productivity by 7% per year through rapid response to abnormal situations and reduction of rework.

◇ InterX, AI-based CNC machining defect and tool life prediction system

Innotech (CEO Lee Hee-bang) produces electric vehicle reducers, automatic transmission shafts, drive unit hubs, and ball lamps. The biggest problem was the loss caused by malfunction or defect of the computer numerical controller (CNC), which is the core of product production. During the production process, processing parameter values were different depending on the skill level of the CNC operator, and in this case, defective product dimensions could not be avoided.

InterX (CEO Park Jeong-yoon) stepped forward as Innotech’s ‘AI solver’. By understanding the lifespan and replacement period of all tools, including CNC, in advance, we sought ways to significantly improve product defects and productivity. Innotech, which introduced the AI-based CNC machining defect prediction and tool life prediction solution developed by Interx, predicts that the defect rate of its main product, ball lamps, will decrease from 3.2% to 2.8%, increasing production efficiency from 80% to 90%. He said it would be possible.

◇ UDMTech, AI-based automatic control system for riveting process

PA (CEO Heo Seung-hyeon) is a company that develops and produces door latches, door modules, and door hinges. In the riveting process, which connects parts using metal rivets, when a change in setting value was required due to a change in vehicle type or process environment, the value was entered manually. This often delays the process or causes errors.

Through this project, PAHA joined hands with UDM Tech, which will develop AI technology. The two companies are
big data
  We collaborated on the development of AI-based quality prediction and servo axis position control systems for riveting processing processes.

By applying the AI-based automatic control system for the riveting process developed by UDM Tech, you can immediately respond to subtle process changes. Delays caused by changing setting values can be reduced. It also recommends optimal settings for high quality, reducing the occurrence of potential defects. AI-based riveting device reduces errors and delays by detecting abnormal load rate patterns and calculating statistical optimal settings. PAH announced that the overall efficiency of the facility increased by 7%, with the actual production volume of related products per hour increasing from 155 to 166.

◇Seongwon Information Technology, builds a data collection and analysis dashboard

Sangsin Brake (CEO Kim Hyo-il and Park Se-jong) is a company that produces brake pads. Brake pad friction materials vary in combination and ratio depending on performance, so research and analysis takes a considerable amount of time. Brake pads require analysis of numerous performance data and linkages between items in order to design new friction material products, but it is not easy to analyze all of this data with human resources alone. Sangsin Break's long-cherished goal was to analyze data to make the process and supply chain management necessary for product design intelligent, and to make the mixing recipe intelligent during the product development process.

To this end, two companies, Sungwon Information Technology (CEO Song Seong-ho) and Big Wave AI (CEO Hee-jun Lee), collaborated to develop two AI models: 'AI-based optimal manufacturing process system' and 'AI mixing recipe intelligent system'.

Seongwon Information Technology collected and processed existing data and established a separate database (DB) for data analysis. Based on this, we created a performance simulator and dashboard that enables analysis visualization during the formulation combination process. Seongwon Information Technology also provides system design and UI/Windows linked to existing systems so that production site workers can conveniently utilize them.
UX
also developed.

◇Big Wave i, establishes AI-based optimal manufacturing process

Big Wave AI learned the DB built by Sungwon Information Technology and accelerated the development of the 'AI-based optimal manufacturing process system' and the 'AI mixing recipe intelligent system' that minimizes the resources required for brake pad combination design. We developed an order and UPH (Unit Per Hour) forecasting model to increase the convenience of inventory management by knowing in advance the order lead time according to the expected production volume in the production process. Based on this, Sangsin Break established an automatic material requirements planning (MRP) system that allows for more accurate predictions. In addition, we also developed an AI mixing recipe intelligent model that predicts the physical properties of brake friction materials by learning the raw material mixing ratio and manufacturing process during the product development process. The company is focusing on development with the goal of achieving a 55% hit rate in the mix design and a 76% achievement rate in process capabilities for developed products.

Thanks to two AI solutions developed through collaboration between Seongwon Information Technology and Big Wave AI, Sangsin Break was able to further increase its technological competitiveness by shortening product design time and significantly improving quality.

[Regional specialized industry accelerates digital transformation with AI] Daegu transportation equipment and mechanical material parts industry prepares for emergency with AI engine

[Source] Electronic Newspaper, Reporter Park Ji-seong, jisung@etnews.com