AI Welding and Robotic Dogs Enhance Manufacturing in South Korea

Collaborative robot for flat block assembly at HD Hyundai Heavy Industries. [Photo=Joint Coverage Group]

"When manufacturing 'lugs,' which are essential for moving ship blocks, six workers could produce about 100 units a day manually. Recognizing that this is the only product that can be mass-produced in shipyards, we established an autonomous manufacturing system where robots create lugs without human intervention, significantly enhancing productivity. The need for artificial intelligence (AI) is growing to maintain competitiveness and increase productivity," said Yoon Dae-kyu, an executive at HD Hyundai Heavy Industries.
As domestic manufacturing faces challenges from intensified price competition from China, a shortage of labor due to an aging workforce, and a global supply chain restructuring, AI is paving the way for solutions. The transition to manufacturing AI (M.AX) is becoming a necessity rather than an option.
During a visit to the medium-sized ship division of HD Hyundai Heavy Industries in Ulsan on June 12, Yoon noted that industrial robots were continuously welding and producing or recycling lugs, which are essential components in ship manufacturing.
Lugs connect the blocks of a ship to lifting equipment when they are hoisted or moved. They are produced in various specifications but are used in large quantities throughout the shipbuilding process, making a timely supply system for diverse lugs essential. Additionally, since lugs can be reused two to three times, a recycling and management system is also necessary.
HD Hyundai Heavy Industries has established a lug autonomous manufacturing system based on eight industrial robots and two autonomous mobile robots (AMRs). This system has transitioned from a manual welding-centered production method to an unmanned production system. According to Yoon, this change has improved the continuity and stability of the production flow.
Production efficiency has also increased. Since implementing the lug autonomous manufacturing system, production has improved by 87.5%. The automation equipment performs repetitive tasks reliably, enhancing production efficiency and allowing for flexible supply of various lugs. Variations in worker skill levels have decreased, reducing the physical strain on workers and lowering the risk of industrial accidents.
The use of collaborative robots is also on the rise. In the second shipbuilding plant, welding collaborative robots are utilized during the assembly of flat blocks. Previously, the repetitive welding tasks in confined spaces posed significant risks and discomfort for workers, increasing the likelihood of musculoskeletal disorders.
The collaborative robots, which incorporate the expertise of skilled workers, are now performing the tasks of two workers with 5 to 10 years of experience each, resulting in a productivity increase of about 70%, according to HD Hyundai Heavy Industries.
Looking ahead, the challenge lies in developing unstructured AI technology. Yoon stated, "Currently, we can manage structured components to some extent, but unstructured ones vary by design and product. We are developing humanoids that can be utilized in the dock for building ships, not just for components inside the ship."

Boston Dynamics' Spot robot inspecting a tuyere at POSCO's Pohang Steelworks. [Photo=POSCO]

M.AX is being applied not only in shipbuilding but also in the steel industry. POSCO is introducing autonomous robot technology for predictive maintenance and high-risk tasks in steel production. Predictive maintenance involves collecting data and using AI to monitor the condition of machinery in real-time to predict failure points.
A prime example is the use of Boston Dynamics' Spot robot to inspect tuyeres in the second blast furnace at the Pohang Steelworks. Inspecting the external temperature and gas leaks of the 30 tuyeres that blow air into the furnace is crucial. However, with a limited number of workers managing the entire furnace, regular inspections have been challenging. The extreme heat exceeding 1,100 degrees poses risks of burns and gas exposure for workers.
To address this, robots are being deployed for tuyere inspections based on accumulated data. The robots are equipped with anomaly detection capabilities through data analysis, enabling real-time monitoring. This ongoing data collection has also led to the implementation of monitoring functions based on digital twin technology.
AI is expected to be utilized for inspecting rollers on belt conveyors that transport steel and for manual steelwork. By detecting anomalies based on voice data from the belt conveyor, robots can facilitate replacements. The plan is to have humanoid robots perform tasks previously done by humans near molten metal, minimizing the need for workers in high-risk environments.
The technologies developed through these initiatives are expected to be applicable in similar industries in the future. Choi Yong-jun, a researcher at POSCO, stated, "After enhancing the diagnostic performance for key equipment anomalies, we will expand robot demonstrations and plan to create an integrated platform for predictive maintenance packages to facilitate technology transfer."

* This article has been translated by AI.