Machina Rocks Joins KRW 11.8 Billion MOTIE R&D Project to Develop Autonomous Hot Forging Technology
TECHWORLD ·
✦ AI Summary
Machina Rocks was selected as a joint research and development institution for an R&D project of the Ministry of Trade, Industry and Energy.
The project is for developing a system that autonomously automates die design, production and quality management in the hot forging process for auto parts using AI.
The project period runs from June 2026 to December 2029, with a total budget of KRW 11.8 billion and KRW 2.4 billion in R&D funds allocated to Machina Rocks.
Machina Rocks will participate in an R&D project of the Ministry of Trade, Industry and Energy. Machina Rocks said on the 14th that it had been selected as a joint research and development institution for the Korea Institute for Advancement of Technology (KEIT)-led "2026 Machinery and Equipment Industry Technology Development Project (manufacturing-based production systems)."
The project aims to develop a system that autonomously automates die design, production and quality management in the hot forging process for auto parts using AI. Its goal is "development of an AI-based automatic correction system for hot forging die design for auto parts and an autonomous production system for forgings."
Saeil Forging will serve as the lead research and development institution. The participating organizations are six industry-academia-research institutions, including Machina Rocks, ING Global, the Korea Institute of Industrial Technology, Gyeongsang National University and the University of British Columbia (UBC).
The project will run from June 2026 to December 2029. The total project budget is KRW 11.8 billion, of which KRW 2.4 billion has been allocated to Machina Rocks for research and development.
The hot forging process involves heating metal to over 1,000 degrees Celsius and then applying pressure with a large press to produce parts. Under the conventional method of drafting die designs, work was carried out based on part drawings, and the person in charge had to extract design parameters manually. This conventional approach could result in variations depending on skill level and could also cause work delays.
Machina Rocks developed design automation technology using the AI operating system Runway and the drawing decision-making AI agent DrawX. The design automation method consists of AI recognition of forging drawings, AI extraction of design parameters and the proposal of die design corrections based on the extracted parameters. Machina Rocks also developed technology to diagnose process anomalies by using multi-sensor data such as temperature, load and vision in the production stage, and to predict forging quality based on vision AI.
Machina Rocks also plans to implement a digital-thread-based integrated control system. The integrated control system will have functions that connect design, process and quality data, and the implementation environment is Runway.
Machina Rocks plans to extend its existing AI application experience in manufacturing fields such as semiconductors and secondary batteries to forging, and use Saeil Forging's mass-production line as a demonstration site for the developed technology. Through this, it aims to reduce dependence on skilled workers in the forging sector and improve productivity and quality.
A distinctive feature of this project is that it connects data not only in the production process but also from the design stage, and it will proceed in a direction that promotes autonomy starting from the design stage. Machina Rocks plans to link product design, production and quality inspection data and, based on this, establish a structure that can continuously analyze process conditions and a structure that can continuously analyze quality histories.
Machina Rocks CEO Yoon Seong-ho said that the forging process is an area where reliance on worker experience is high because of its high-temperature environment, high-intensity work and many variables. He added that through this demonstration, the company will pursue the implementation of physical AI to solve on-site problems and also pursue the development of autonomous production technology that can be applied across the root industries.
Source: TECHWORLD · Kim Seung-gi
Original: https://www.epnc.co.kr/news/articleView.html?idxno=408182
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Source: TECHWORLD
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