Recently, demand for humanoid robots in China has surged, leading to a wave of large-scale supply contracts. In response, Morgan Stanley released its Humanoid Robots 100 report, projecting that the global humanoid robots market could reach as much as USD 60 trillion within the next decade. This article examines the potential of humanoid robots as an industrial mega trend, global technology development strategies, and Korea’s approach to this emerging sector.

Senior Researcher Jeoung-Heon Woo POSCO Research Institute

Humanoid Robots in History

Humanoid robots—machines designed to resemble humans—have appeared throughout history, sometimes as loyal assistants, other times as perceived threats. Examples include the bronze giant Talos from ancient Greek and Roman mythology, the water-clock-powered automaton of China’s Han Dynasty, and Leonardo da Vinci’s “robot knight” from the Renaissance. Across ancient civilizations, human-like machines have emerged in various forms.

Interest in humanoid robots has endured for centuries, accompanied by caution over potential risks. Notably, science fiction writer Isaac Asimov introduced the Three Laws of Robotics in his 1942 short story Runaround, raising philosophical questions about the relationship between humans and machines.

The rapid advancement of AI in recent years suggests that robotics may evolve toward a humanoid robots-centered future. While a “machine” is generally defined as a tool designed to perform production activities using power, a “robot” is an intelligent machine capable of making autonomous decisions under certain conditions.

Modern humanoid robots go further, combining advanced AI with a human-like form factor—a body structure modeled on human anatomy—allowing them to learn work methods, optimize performance, and actively assist in a wide range of human activities.

Physical AI: Extending Intelligence into the Real World

The concept of Physical AI is also gaining attention. Physical AI refers to AI embedded in physical devices—such as robots or autonomous vehicles—that interact directly with the real world. Traditional AI communicated with humans through digital interfaces like text or images, but Physical AI operates in real-world environments, collaborating with humans, perceiving surroundings, and responding accordingly. At CES 2025, NVIDIA CEO Jensen Huang identified Physical AI as a major future growth driver, emphasizing NVIDIA’s role at the center of this technological shift.

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Why the World is Paying Attention to Humanoid Robots

Humanoid robots are gaining social acceptance and technological attention for two main reasons: form factor suitability and socio-economic potential.

1. Form Factor Perspective

Robots designed for specific repetitive tasks benefit from specialized form factors. However, for Physical AI performing diverse, non-specialized actions in real-world environments, a human-like form factor is advantageous because our physical infrastructure is built for human proportions.

Door handles, stair dimensions, and control panel placements are all designed for human use. Humanoid robots can operate in these environments without costly infrastructure changes, offering high versatility. In contrast, having different standards for each form factor would be inefficient.

2. Socio-Economic Perspective

Humanoid robots’ human-like appearance enables a wide range of human-robot collaboration scenarios, extending beyond manufacturing into customer service, caregiving, education, and guidance. Recent advances in language processing, facial expression recognition, and gesture control have improved emotional engagement, signaling the evolution of robots into social entities.

However, psychological barriers remain. Masahiro Mori, Professor Emeritus at Tokyo Institute of Technology, proposed the Uncanny Valley theory, which suggests that robots that look too human can cause discomfort. This highlights the need to consider psychological acceptance and emotional distance alongside technical perfection.

Economically, humanoid robots are highly promising. Their development requires not only AI but also sensors, actuators, motion control systems, and energy supply technologies. These demands drive innovation across multiple industries, making humanoid robots development a potential growth engine for the future.

Humanoid Robots Industry Structure and Potential Players

Morgan Stanley’s February 2025 report divides the humanoid robots industry value chain into three core areas: Brain, Body, and Integrator, and identifies potential players in each.

• Brain: Combines software and hardware. Software includes AI models, data science, simulation technology, and vision software. Hardware includes memory and vision computing.
• Body: Includes actuators, components, motors, sensors, batteries, power semiconductors, analog semiconductors, aluminum casting, connectors, heat treatment, and automation systems.
• Integrator: Companies that assemble and integrate the brain and body into finished products. Potential players include Hyundai Motor, Boston Dynamics, Apple, Samsung Electronics, LG Electronics, Alibaba, Amazon, Naver, ABB, and KUKA.

The industry can also be categorized into core components and modules, finished product assembly, and service areas, with the service sector expected to see diverse business models emerge.

Global Technology Leaders: Tesla and NVIDIA and Hyundai Motor

▲ Tesla’s Optimus Gen 2 (Source:Tesla’s official YouTube channel)

The emerging humanoid robots industry is being led by Tesla and NVIDIA, each pursuing distinct strategies.

Tesla is leveraging its expertise in EV production and autonomous driving to develop Optimus, a humanoid robot intended to automate production lines. First unveiled at Tesla AI Day in 2021, Optimus has evolved to perform a variety of tasks. The 2024 Optimus 2 features 40 actuators—12 in the hands alone—allowing it to perform delicate actions such as cracking an egg. Tesla plans to enter the humanoid robots sales market in 2026.

NVIDIA, on the other hand, aims to dominate the humanoid robots “Brain” platform rather than build its own robot. Its Jetson Thor computer, based on the latest Blackwell GPU architecture, enables large-scale AI inference and vision-based decision-making directly on local devices—capabilities previously limited to server environments.

Tesla’s approach resembles Apple’s integrated hardware-software model, while NVIDIA’s strategy is akin to Android’s platform dominance.

▲ Hyundai Motor Company unveils humanoid robot “Atlas” at CES 2026(Source:Hyundai Motor Group official YouTube channel)

In addition to these global leaders, Hyundai Motor introduced its humanoid robot Atlas at CES 2026. Purpose-built for industrial and logistics operations, Atlas offers advanced mobility, precise manipulation capabilities, and seamless integration with Hyundai’s autonomous vehicle and smart factory ecosystems. The debut underscores Hyundai’s ambition to position itself as a key integrator in the humanoid robots value chain, capitalizing on its manufacturing expertise, robotics R&D, and global production footprint.

Securing Leadership in the Humanoid Robots Value Chain

Following smartphones and EVs, the world has lacked a clear driver of technological innovation—until humanoid robots emerged as the next catalyst. As a convergence of cutting-edge technologies, humanoid robots are recognized as a key area for future growth, though challenges remain in cost competitiveness and safety in human-machine collaboration.

Importantly, the humanoid robots industry’s impact will extend beyond AI and software into materials, components, and services. Development and standardization will require core components that meet both functionality and reliability, along with mass production capabilities. In the service sector, opportunities will arise in humanoid robots deployment, human-robot collaboration models, and humanoid robots training and operation.

In June 2025, the Korean government launched the K-Humanoid Robots Alliance, a national robotics and AI consortium involving over 40 domestic industry, academic, and research institutions. AI companies and experts are collaborating with universities to develop AI models for robot manufacturers, with field trials supported by demand-side companies such as POSCO Group.For example, Aei Robot has signed MOUs with POSCO E&C and HD Hyundai Mipo Shipyard to develop humanoid robots for construction sites and shipyards.

Humanoid robots have moved beyond simple robotics to become a central axis of next-generation industrial innovation. Understanding and responding strategically to the technological, industrial, and service trends surrounding their evolution is more important than ever.

Leading the spread of AX in the industrial field with applications such as coil unloading systems for tens of tons of steel products

POSCO DX (President Shim Min-suk) is accelerating its manufacturing AX (AI Transformation) by advancing its ‘Physical AI’ technology based on virtual environment simulation and applying it to the field one after another.

POSCO DX announced that it has developed an AI model that replicates a real-world factory in a virtual environment and established a ‘physical AI’ development system that efficiently supports AI learning and verification prior to field application. Facilities and sensors at industrial sites are greatly affected by the physical environment such as inertia, acceleration, and noise, and by implementing conditions that can be encountered in the real world in a virtual space and conducting various simulations, AI can learn the optimal movement of facilities.

At actual industrial sites, there were limitations in acquiring field data and testing AI models due to disruption of operations or safety and security reasons. POSCO DX utilized virtual environment simulation to solve these issues and is expected to significantly reduce the time and cost of AI model development and field application.

POSCO DX has implemented virtual environment simulation by adopting Isaac Sim of NVIDIA Omniverse platform. Isaac Sim is a SW that supports verification by simulating the physical environment precisely with actual sensors and systems in a virtual environment.

POSCO DX recently built a specialized optical laboratory in its Pangyo office building to further advance its ‘physical AI’. The optical laboratory is a space where the response of sensors and precision according to specifications, which are difficult to identify in AI simulations, are tested by artificially creating an environment similar to the actual site in terms of lighting, temperature, and movement. By reflecting the sensor data verified here in the AI ​​simulation, it is evaluated that the gap between the virtual and actual sites has been minimized, enabling more efficient simulations.

On the other hand, ‘Physical AI’, which was the topic of this year’s CES 2025, refers to AI that recognizes the surrounding environment and interacts with the real world by controlling physical systems. ‘Physical AI’By applying , AI can recognize and judge various operation situations and control and operate facilities directly with the on-site control system (PLC, Programmable Logic Controller), enabling unmanned operation. POSCO DX is leading the spread of ‘Physical AI’ in industrial sites by converging AI technology with existing IT (information technology) and OT(automation technology).

POSCO DX ‘physical AI’ to cranes that transport atypical products with different sizes and packaging forms.is prioritizing the application of In the first half of this year, POSCO DX developed an AI model to automate the unloading of coil products transported on trailers into cranes, and plans to spread it horizontally by conducting virtual test drives and applying it to the field.

Yoon Il-yong, head of POSCO DX AI Technology Development Center, emphasized, “POSCO DX is pursuing the implementation of ‘physical AI’ technology with the goal of ‘autonomous physical systemization of manufacturing facilities’ based on the convergence of AI, IT, and OT technologies,” and added, “We will strive to establish ourselves as a leading company in intelligent factories by advancing ‘physical AI’ utilizing physical development methodologies such as virtual environment simulation.”

▲POSCO DX AI researchers are testing the physical environment, such as light and distance, of the coil loading and unloading site in the optical laboratory of the Pangyo building.

Steel is strong. It’s solid and durable, which makes it an exquisite material in manufacturing automobiles and other vehicles. The sustainability of steel is another significant factor that shines a light on the future of transportation.

Worldsteel spotlights the maritime sector — among the many types of vehicles — and demonstrates how steel made a difference. See the details of how the combination of steel and latest technology is paving the future of the industry — POSCO Newsroom presents worldsteel, “Artificial Intelligence, Steel and the Future of Shipping.”

Technology is rapidly transforming operations across all industries — from retail to healthcare to real estate — and the implications of these changes are significant. Developments in road vehicle technologies for cars and trucks seem to hit the headlines constantly. But these aren’t the only type of vehicle with an eye on the future.

Welcome to the age of autonomous shipping — made possible by the powerful combination of artificial intelligence and steel. The maritime sector, like so many others, is experiencing unprecedented disruption. Experts are now in agreement that automation is a necessity if the industry is to stay relevant in the decades ahead.

While modernisation always presents challenges, the opportunities on the horizon for the shipping industry are enormous. If shipping companies can successfully implement fresh solutions based on technologies like artificial intelligence, they will be able to streamline and enhance their operations. The result will be valuable benefits such as cost-savings, better routing, and the ability to identify new business areas.

Tomorrow’s ships will be complex hubs filled with sensors and data-capturing devices with significantly enhanced connectivity capabilities thanks to improvements to satellite technologies. When it comes to the design, building and testing of vessels and their components, cloud technologies will also have a big impact.

Perhaps the most important potential outcomes, however, relate to the environmental impact of shipping. Shipping is already the world’s most energy-efficient means of transport, but there is still work to be done in terms of energy efficiency and carbon footprint. Automation technologies are set to have a notable positive impact on sustainability outcomes for the industry.

For example, more efficient shipping routes which use less fuel or alternative energy sources have the potential to minimise or eliminate carbon emissions entirely. At the same time, making improvements to shipping practices and routes can reduce the number of polluting road vehicles needed to transport cargo once it arrives at a destination — another sustainability win for the sector.

l The Future of Shipping

An example of the future of shipping in action is Yara Birkeland, an autonomous, electric and zero-emissions container vessel from Norway, which is expected to launch in 2020. Within its initial two years, Yara Birkeland will move from manned to autonomous operations, marking a world-first for the sector. The ship will directly replace around 40,000 truck journeys per year, reducing NO_x and CO₂ emissions significantly.

In the Yara Birkeland project and others like it, steel has an important part to play, acting as a key enabler for strides forward in shipping automation and other future-facing technologies. Vessels like the Yara Birkeland make use of steel throughout their designs, including the panelling of the hull, the engines, and on-board solar panel systems.

As autonomous shipping takes off, more and more companies are entering the race and hoping to get in on the action. For example, a “future-proof” ship concept called Electric Blue was revealed by leading brand Rolls-Royce in 2017. It includes steel-built modular components that can easily be replaced or upgraded as necessary in the future, as well as featuring a clean design focused on low building and maintenance costs.

The future of shipping is fast approaching, and it will only continue to gain pace throughout 2020 and beyond. As the technologies powering the world’s most important industries change, steel remains at the heart of helping to create greater business efficiencies, positive sustainability outcomes, and sophisticated, cutting-edge design.

Images: Yara; Rolls Royce Marine, Flickr

The original content published on the worldsteel’s ‘Our Stories’ section is available at: https://stories.worldsteel.org/innovation/artificial-intelligence-steel-and-the-future-of-shipping/

However, the Lighthouse Factory POSCO does not stop at simply leading the introduction of the Fourth Industrial Revolution technologies. What’s more? Here are the three factors that make POSCO stand out.

① Challenging the Impossible — POSCO’s Smart Blast Furnace

An unmanned storehouse or an automotive parts assembly factory run by robots could be the first thing that comes to mind when one hears the word ‘AI factory.’ Another might think that Artificial Intelligence could be applied only in specific areas, like the information technology industry. A blast furnace is a gigantic facility with a height equivalent to a 40-story building. On the inside, it is full of a mixture of solids and liquids, so turning it off or ‘looking’ inside seems impossible. Due to these many factors, applying AI to a blast furnace and making it ‘smart’ was considered nearly impossible.

POSCO stood up to this challenge. In 2016, the term ‘Fourth Industrial Revolution’ began to take its place in the industry. POSCO was one step ahead, but not in a hurry. It moved on to Step-by-step digitization and smartization with caution and care. At first, POSCO tried to do this with the technology of a global IT company but did not get satisfactory results. The new technology alone wasn’t enough. However, when POSCO’s unique expertise, intuition, and knowledge — along with its field experts — were combined with it, the advanced AI blast furnace could be born.

▲ The AI blast furnace is made with the combination of vast, sophisticated data, and the experience and intuition of POSCO experts. Deep learning enables optimal results and automates them to reduce human errors and increase productivity.

POSCO field experts — the technicians and engineers — standardized the main variables that determine the state of the blast furnace into Big Data. They enabled the blast furnace to conduct deep learning to extract optimal result value by imitating their know-hows accumulated for over 30 years. Facilities were also steadily improved so that the IoT could replace the manual work. As a result, POSCO boosted the daily production of molten iron by 240 tons. Additionally, workers could focus on advanced work for more creative performance. POSCO saved 250 billion KRW by carrying out 321 smart tasks — including the AI blast furnace — for the past four years.

Through the AI blast furnace, POSCO was able to break away from the old concepts of steel mills. POSCO’s “Technology for the automated control of blast furnace based on deep learning AI” is currently registered and protected as the National Core Technology of Korea (August 2019). POSCO is currently establishing smart factories not only in the blast furnace but also in the overall steelmaking, rolling, and surface treatment process and is creating high-quality smart steelworks.

② POSCO Smart Factory: A Collaboration Of Academia, SMEs, And Start-ups

There is another special feature behind the Lighthouse Factory POSCO — the collaboration of academia, SMEs, and startups in establishing the Smart Factory. As seen below, the World Economic Forum acknowledged POSCO’s effort in forming the collaboration model.

▲ A World Economic Forum article stating the reason POSCO was chosen as a Lighthouse Factory.

POSCO is actively cultivating AI experts in-house and is working with POSTECH for the cause. POSTECH has the best faculty of the artificial intelligence field in Korea. POSCO AI Expert Course, which began in 2017, is a program where selected outstanding POSCO personnel receive training from POSTECH professors. This course has resulted in more than 60 POSCO AI experts in three years. These AI experts are working to build smart factories in the work field.

The collaboration included SMEs and start-ups as well. POSCO developed the AI blast furnace with ‘ECMiner’ since 2016. ECMiner is an SME specializing in data mining*. It created a system that can automatically identify, analyze, and maintain the combustion condition of the blast furnace by combining its data mining technology with POSCO’s accumulated data. In the past, the combustion status was left to the manual labor of workers, checking through the wind hole, and judging by experience. However, with this system, the data can now be taken care of automatically. It also maintains the appropriate combustion level of the blast furnace, which reduces the amount of coal injected. This enables an overall cost reduction.
*Data mining: A technology that looks for hidden, valid, and potentially useful patterns in huge data sets, extracts feasible information, and makes decisions accordingly.

The collaboration resulted in a win-win for both POSCO and ECMiner. POSCO succeeded in creating an AI furnace with Korean technology, and ECMiner also benefited from the experience of processing huge amounts of data at POSCO. All academia, SMEs, and start-ups that participated in the building of POSCO Smart Factory, including ECMiner, can help construct a new one in another factory based on technology experienced at POSCO. This is expected to accelerate the proliferation of smart factories in Korea.

③ Sharing With The Industrial Ecosystem

The Lighthouse Factory POSCO shines brighter for the third factor. On January 9, Korean president Jae-in Moon visited POSCO Pohang works.  POSCO CEO Jeong-Woo Choi said:

“With the Smart Factory, POSCO has reduced production cost of 250 billion KRW for four years. And to relieve the wage gap with business partners, POSCO has extended an additional 270 billion KRW to outsourcing expenses for the last three years. Increased outsourcing expenses raises overall costs. However, POSCO is offsetting this through endless innovation. Through these measures, POSCO aims to foster the competitiveness of the whole industrial ecosystem, and then, in turn, enhance national competitiveness. POSCO’s management philosophy lies here.”

▲ Image source: KTV Youtube video

POSCO willingly shared the achievements of the smart factory project to solve the real problems many partner companies face. At first glance, this might simply seem like a ‘generous side’ of a large company, but in reality, this wasn’t an easy step. POSCO made this possible with its capacity earned through intense internal innovation. This is a good example showing how POSCO innovation isn’t just about POSCO.

POSCO went on to expand the benefits to SMEs who do not have direct business with POSCO. With the support service to build Smart Factory for shared growth, POSCO has provided the Smart Factory technology to 110 SMEs last year alone — 59 of which are companies with no direct business. The service will support 1,000 SMEs by 2023, with no limits to the subject. This is expected to increase the competitiveness of SMEs, which will, in turn, improve productivity and create new jobs.

▲ POSCO’s Smart Factory project not only increases POSCO’s competitiveness but also empowers the entire industrial ecosystem. It also helps in resolving current issues like narrowing the wage gap and creating new jobs.

This is what POSCO’s innovation is all about. The willingness to share with something that was earned hard. POSCO the lighthouse factory is indeed shining the light to a brighter future of the manufacturing powerhouse Korea.

POSCO Pohang Works was selected as the ‘Lighthouse Factory’ for spearheading innovation in manufacturing by the World Economic Forum (WEF) in July last year, opening a new horizon for smart blast furnaces. The WEF consultant, who visited Pohang Works for site review, showed great interest in the live monitor-controlling of the blast furnace. This complex and huge furnace is controlled by pairing the expertise of POSCO workers with AI technology. On January 9, South Korea’s President Jae-in Moon visited the site and watched the world’s smartest furnace at work.

POSCO is also striving to strengthen its industrial ecosystem by sharing its Smart Factory platform with business partners — including SMEs. Let’s take a closer look at how POSCO is working on its Smart Factory and pursuing Corporate Citizenship.

l POSCO’s Blast Furnace — At the Forefront of the Fourth Industrial Revolution.

Since the term ‘Fourth Industrial Revolution’ was first used at the 2016 Davos Forum, it has become the mainstream of all industries. Companies started working on to quickly acquire the core technologies of the Fourth Industrial Revolution — like Big Data, Artificial Intelligence, and the Internet of Things. Twice a year, Davos has been designating factories that are leading innovation in manufacturing as ‘Lighthouse Factories’. Last July, POSCO became the first South Korean company to be announced as a lighthouse factory.

The No.2 blast furnace at Pohang Works could be called the core of the Fourth Industrial Revolution Technology. POSCO embarked on the ‘digitization’ of the blast furnace in 2016 when the term ‘Fourth Industrial Revolution’ came about. Since the blast furnace was originally dependent on field workers’ heuristic knowledge, by ‘digitization’, POSCO worked on standardizing all accumulated data.

The blast furnace is a gigantic facility with a height of 110 meters — equivalent to a 40-story building. Inside the blast furnace flows a mixture of solids and liquids whose temperature rises as high as 2300℃. All these factors make it impossible to ‘look’ inside the blast furnace, hence, digitizing the variables of this huge blast furnace was more complicated and difficult than expected. The seemingly impossible task of ‘standardizing data’ of human knowledge marked the start of the smart furnace.

The accumulated data became the base of big data. Since 2017, POSCO has been working on deep learning with big data. Through deep learning, the blast furnace can self learn from the numerous cases given. This process called, “Smartization” enables the system to predict and control the potential variables, and to derive optimal results. The IoT has also accelerated the establishment of smart furnaces. In the past, multiple factors such as molten iron temperature, the amount of fuel and raw materials, and so on were left to the manual labor of workers. However, through IoT, high-definition cameras and sensors can take care of the data automatically.

▲ The internal temperature of the furnace can go up to 2,300℃. In the inside, several materials like iron ore and coke are mixed, causing various chemical reactions. It’s like a huge pressure vessel that’s 40 stories high. POSCO succeeded in data standardizing and automating the blast furnace.

As a result, Pohang No.2 Blast Furnace has become capable of self-control and prediction to an artificial intelligence level, giving it the name, ‘AI blast furnace’. With the experience of experts who have worked for more than 30 years at ironmaking, the smart furnace boosted the daily production of molten iron by 240 tons. Annually this amounts to 85,000 tons with which automakers can produce 85,000 more cars.

There is always a concern that follows these kinds of changes, “Won’t AI make people lose jobs?” But the answer is “No.” Instead of looking into the furnace all day, workers can focus on more advanced work with their Domain Knowledge. This enhances the possibility of more creative performance.

l What Makes POSCO’s Smart Factory Special?

Currently, leading global companies are adopting the smart factory platform. Then what makes POSCO’s Smart Factory more special? The answer lies in the platform established for the ‘Continuous Processing’ — a special term of steelwork. POSCO doesn’t stop at applying this platform to just furnaces. It has gone on to extend these smart factories to the overall steelmaking process. PosFrame, the engine of POSCO’s Smart Factory, is its unique factory platform specified for continuous manufacturing processes.

The steelmaking process is continuous, running smoothly from production planning to delivering the final product to the customer. Therefore, applying the smart factory platform to steel works is quite challenging — with a much bigger scale — than applying to a single factory that produces a single item. Pohang Works is massive in size, with hundreds of factories manufacturing hundreds of different steel products. In such an environment, data from each site should be gathered, organized, and standardized so that anyone can process it. This is one of the main functions of PosFrame.

Let’s say that the steelmaking process starts from A and ends at Z. When PosFrame is applied completely to the steelworks, it is possible to trace the cause of an issue that occurred in Z to A.

▲ A Smart Factory operation concept in an integrated steelwork. The cause of an issue occurring at the later part of the process can be automatically tracked to the earlier part of the process, diagnosed, and resolved.

l POSCO’s Technology For All Business Partners to Share

How is Corporate Citizen POSCO dealing with this unique technology? POSCO isn’t planning on making this technology exclusive. Instead, POSCO is working on expanding the smart factory technology to business partners including SMEs.

Dongkuk Industries, which has factories in Pohang and Siheung, is a company that processes POSCO’s hot rolled steel into high-quality cold rolled steel. This product is then supplied to companies that produce automotive parts. At Dongkuk Industries, steel goes under the pickling process, where hydrochloric acid (HCl) is used to remove scale on the product surface. This takes a great deal of time since each customer demands different quality requirements. Since it is nearly impossible to match each requirement, Dongkuk Industries pickled all materials even though each POSCO hot rolled steel had different scales. Naturally, productivity decreased, and this is where POSCO’s Smart Factory technology stepped in.

First, through PosFrame, POSCO sends predicted data showing where and how much scale is on the supplied hot rolled steel. This predicted data is received at the “AI for optimal pickling” in Dongkuk Industries. In the past, the pickling conditions were calculated manually by workers, but now this AI automatically extracts the optimum value based on the data obtained from PosFrame. After pickling, the resulting data is passed back to PosFrame. As POSCO hot rolled steel is processed into high-quality cold rolled steel here, its data are accumulated in PosFrame as big data and advanced through repeated learning. The data on both sides are exchanged repetitively, enabling the production of an optimized product — as if produced in a connected plant. The application of the Smart Factory in Dongguk Industries minimized the time required for the pickling process while securing product quality required by the customer. This increased productivity by 60%, and high-quality material sales by 1.5 times.

▲ Dongkuk Industries established a Smart Factory with POSCO. (From the top left clockwise) the front view of the Pohang factory; the pickling line; the hydrogen furnace; and the wide shear line. (Photo credit: Dongkuk Industries)

POSCO is also concentrating on Smart Factory consulting for SMEs. This service isn’t limited to direct customers but expanded to other business partners, including secondary customers. POSCO has engaged in support service to build Smart Factory for shared growth with the Ministry of SMEs and Startups — establishing Smart Factory in 110 companies until last year. At the same time, POSCO also provides ‘Smartification Consulting’ to enhance competence, thus, delivering advanced field expertise through POSCO’s unique innovation technique QSS(Quick Six Sigma). By 2023, POSCO is to contribute 20 billion KRW to empower 1,000 companies.

POSCO is operating seven major programs for shared growth, and some of them are as follows — ‘Open Purchase’ offering fair trading opportunities; ‘Proper Payment On Time’ abolishing the lowest price bidding system and giving payment in cash on time; ‘Corporate Citizenship Job Matching’ training job seekers and arranging employment at partner companies. Additionally, POSCO has aided 1 trillion KRW, leading the way in establishing a Venture Fund of 2 trillion KRW, and a Venture Valley to support start-up activities for the youth.

POSCO has become the “lighthouse” of the global manufacturing industry with its Smart Factory. And in Korea, POSCO is actively working as a guide of Smart Factory for business partners.

l POSCO’s ‘Deep Learning’ Blast Furnace

POSCO embarked on the journey of smart technology back in 2016, the year when a super AI AlphaGo beat Se-Dol Lee, human champion of the game Go.

As disheartening as it was, Lee’s defeat became an awakening moment for Korea and an opportunity for POSCO to start digging deep on the relatively new concept, artificial intelligence. From that moment on, POSCO accelerated its research into AI and deep learning collaborating with top university researchers across the country to develop smart blast furnace.

The core of smart blast furnace technology is, ‘Deep Learning.’ Deep learning discovers patterns amongst countless random data utilizing it to predict the possible outcome just as human intelligence categorizes random items.

Let’s say there are thousands of random pictures – pictures of cats and dogs. A computer reads, analyzes, and categorizes the data from each picture, so the next time it ‘sees’ similar photos, it will recognize, determine and predict the correct pattern, thus identifying the picture as either cat or dog. Lots of companies are already utilizing this technology to analyze massive volumes of audio-visual data.

l What Is a ‘Smart’ Blast Furnace?

A blast furnace is a gigantic structure of 110 meters in height, taller than an average 40-story building – it makes molten iron. Inside the blast furnace flows a mixture of solids and liquids whose temperature rises as high as 2300℃. Since blast furnaces operate 24/7 non-stop, it’s difficult to ‘look’ inside a furnace.

However, the No.2 blast furnace of Pohang Steelworks is changing the game of steelmaking business. The ‘smart’ Pohang No. 2 furnace utilizes deep learning with an automotive system that monitors and auto-controls the inside conditions of the furnace.

POSCO started by defining the five variables that affect the conditions of a furnace. Then, countless random data was digitized for standardization. All the major data which used to be controlled heuristically is now measured live and become digital data paving a new path so the furnace can start learning deeply.

After the digitization completed, POSCO took on smartization process to establish a system to predict and automate the condition of the blast furnace. The key distinction between digitization and smartization is that smartization allows prediction. Because the data is so massive – over 1,000 types – the smartization process assigns algorithm appropriate for each data and perform analysis-prediction-control. Based on the rendered result, the system determines whether the inside conditions are good or bad – or can cause problems.

To put it simply, a smart blast 1) learns countless live-collected cases and data; 2) self-assesses the conditions of inputs (i.e. raw materials and fuels) and the furnace condition; 3) predicts the result of furnace operation; 4) automatically pre-controls the operating conditions; 5) yields the best combination result with minimum error.

l AI Furnace, Smarter than Humans

Every day, the visual data generated from the smart blast furnace daily reach up to hundreds of gigabytes. The smart furnace learns this massive amount of data and is getting smarter every day. What are the potential implications of this vast learning?

Before the smartization, the field employees used to personally measure the blast temperature every two hours, but now the bottom sensor of the furnace live-records the molten iron temperature. Not only does it live-record the current temperature, it also predicts the temperatures inside the furnace an hour ahead auto-adjusting the temperature of hot metal accordingly.

Furthermore, highly consistent algorithm assesses the inside condition of the furnace utilizing the thousands of images collected from the cameras installed on the tuyere nozzles. Based on the assessment, the smart furnace auto-controls the charging actions of iron ores and coke.

What about the skull? It’s layers of adhesives that stick to the furnace wall. To a furnace, it’s a cancer-like lump. What the smart system does is to analyze the images collected through furnace thermometers, sketch the overall shape of the skull, subsequently auto-controlling the charging mode.

Image source: ‘Shipment standby’ – By Tae-Ha Woo (20th Korean National Steel Day photo contest)

Currently, the Pohang No.2 blast furnace is the testing ground for this cutting-edge technology – the smart furnace boosted the daily production of molten iron by 240 tons. Annually this amounts to 85,000 tons with which automakers can produce 85,000 more cars. It is also a huge energy saver reducing the energy per ton of molten iron production.

One of the biggest achievements of the smart blast furnace is having stabilized the furnace management process through AI auto-control.

For the last three years, POSCO completed developing the auto-control system for each component of the blast furnace. Now the company is focusing on comprehensive integration. Going forward, POSCO plans to expand the applications to the Pohang No.3 and No.4 furnaces – they both have bigger internal capacity (5,600 ㎥) than the current No.2 furnace (2,550 ㎥).

POSCO took a giant step by adopting the world’s first thinking blast furnace. With time, more data will be collected, which will improve the quality and efficiency of molten iron production. In the era of the Fourth Revolution, POSCO will continue leading the way towards the smartization of steelworks across the globe.

▲Karen Chupka, the Executive Vice President for the Consumer Technology Association (CTA), gives a keynote speech at CES 2019 (Source:CES)

On January 10th, the world’s largest trade show, Consumer Electronics Show (CES) wrapped up its four-day events in Las Vegas. CES was attended by over 4,500 companies leading the IT, electronics and mobility industries. Altogether over 180,000 individuals from more than 150 countries were present at this global stage for innovation.

Steve Koenig, Vice President of the CTA, started off the CES 2019 Trends to Watch session by discussing key industry trends marked by the term, ‘data age’ where new technologies like artificial intelligence (AI), 5G mobile communications, autonomous navigation, and 8K*, as well as Virtual Reality, will become crucial.
* 8K resolution refers to any screen with around 8000 pixels width. 8K UHD is the current highest ultra high definition television (UHDTV) resolution in digital with the 7680×4320 pixels resolution.

In recent years, so many automakers are attending CES that the convention earned the nickname, “Las Vegas Motor Show.” This year was no exception. Many leading automobile companies showcased their latest technology like autonomous mobility and intelligent connectivity.

At CES, POSTECH students’ autonomous navigating robots created a buzz. The solution was devised by Polaris3D, a company established by the graduate students of POSTECH’s Creative IT Engineering Department and led by CEO In-Bum Kwak.

┃Polaris3D’s Solution Creates 3D Maps with No Extra Infrastructure

In 2016, a group of POSTECH graduate students gathered to form Polaris3D, a venture company with one clear goal in mind: to create an affordable yet sophisticated autonomous navigating solution. Since its foundation, Polaris3D has been winning contests after contests, and since 2018, the company established an office space at Pohang Center for Creative Economy & Innovation.

At the CES conference this year, Polaris3D showcased technology that allows autonomous navigation from indoors through the simple installation of a program on the robot, just like installing an application on a computer. With this simple robot autonomous navigating solution, there is no need to build a separate infrastructure deemed crucial for autonomous navigation.

Until now, utilizing indoor autonomous-navigating robot required extra devices to be installed, to allow UWB (Ultra Wideband) wireless connection or Wi-Fi. With Polaris3D’s solution, however, no additional equipment is necessary.

Polaris3D’s program allows the robot to self-drive to create maps. Based on the map it has created, the robot estimates its own position and travels to the target point, a destination.

While the current SLAM (Simultaneous Localization and Mapping) technology requires a massive amount of computation, Polaris3D utilizes localization technology which can be used for small robots and drones. It can move within a relatively confined space.

This year, Polaris3D will market its solutions to robotics companies and laboratories who need indoor autonomous navigation. Furthermore, the company plans to cooperate with various robotics companies to utilize their solutions onto logistics robots or robot forklifts applying their autonomous-navigating robot solution that doesn’t necessitate additional infrastructure.

┃Industries Vie for Next-Generation Innovations

▲CES 2019 (Source: CES)

Besides Polaris3D’s technology for autonomous mobility, several Korean companies showcased a variety of new technologies at this year’s CES. On the first day of the convention, the products that gathered most attention were Samsung and LG Electronics new TV displays, which far exceeded the limits of current TV displays.

On the first day of CES 2019, Samsung Electronics unveiled the world’s smallest 75-inch micro-LED screen. As the screen size of micro LED becomes smaller, the size and spacing of the device become smaller too, which makes creating a 75-inch display all the more challenging, but Samsung pulled it off. LG Electronics, on the other hand, revealed the world’s first 65-inch rollable OLED TV. Depending on whether you want to watch the TV or not, the TV can be rolled up and down from a cabinet with built-in speakers and all the connectivity ports.

Samsung Electronics also introduced ‘New Bixby’ a smarter artificial intelligence platform as well as a series of robots like Samsung Bot Care, Samsung Bot Air, and Samsung Bot Retail. LG Electronics debuted LG HomeBrew, a capsule-based craft beer-making machine that allows in-home production of five distinctive, richly-flavored beers. LG also showcased intelligent service robot, LG Cloi SuitBot, that supports the lower body to reduce stress when lifting and bending.

The two core concepts of the Forth Industrial Revolution (4IR), a term first introduced at the World Economic Forum 2016, are hyper-connectivity and super-intelligence. The two keywords that best describe hyper-connectivity are the Internet of Things (IoT) and Big Data. For super-intelligence, it would be artificial intelligence – in consideration of which the global companies’ race for AI dominance is understandable, as they brace for the Fourth Industrial Revolution where the concepts of hyper-connectivity and super-intelligence are expected to play pivotal roles.

POSCO is not exempt from this global competition. What they are specifically focusing on is fostering AI experts from within, so they’re organizing related programs to educate prospective AI specialists. This September, they even organized ‘POSCO Industrial-AI Solution Challenge,’ a contest dedicated to various topics on artificial intelligence. The Challenge was open to the general public.

It seems there is no apparent linkage between a steel company like POSCO and AI technologies, but the three topics POSCO assigned for the AI Solution Challenge suggests otherwise. From predicting the cost fluctuations of steel raw materials, figuring out the timing of big swells in the ocean, to calculating how many lunches to prepare for POSCO employees, the scope of AI technology can be far-reaching.

POSCO Newsroom sat with the winners of each challenge category – Team Serio, Zero Coke, and Fast Learner – to hear what they have to say about the contest. All three winners acknowledged the immense potential of AI technology and its applicability to virtually all sectors: AI has no borders.

┃“Braving it out with the AI technology” – Team Serio

Jae-Ho Lee and Dong-Woo Kim, the two members of Team Serio, are from POSTECH (Pohang University of Science and Technology), working in the same research department. The moment when they saw the contest information on the school bulletin board, they knew. That this would be a great opportunity to implement their classroom knowledge to help solve the pressing issues in the field. So they applied with no hesitation.

When asked why Serio had specifically chosen to predict the cost fluctuation of steel raw materials, Lee replied: “This challenge topic has the most economic impact, and we also thought it was the most versatile model as it can apply to other time series forecast of similar nature.”

To come up with a solution, Team Serio utilized the model DA_RNN (Dual-stage Attention based RNN), based on the human cognitive process. When recognizing a particular object, a person first notices an area of interest around her or him. Then, he or she identifies an object within the area of interest, finally recognizing the specific features of the object. That is the typical process of human cognition.

For Lee personally, the most significant achievement from competing in the POSCO AI Challenge was becoming more assured about the prospects of AI research. “Because of the satisfactory result of our model, I think we can brave it out going forward, applying AI technologies more proactively and widely,” he added.

The POSCO AI Challenge has ended, with Team Serio as the final category winner. Even after the contest, however, both Lee and Kim are still testing various approaches that they couldn’t utilize because of the time constraint. For Team Serio, the clock is still ticking.

┃“A Solution As Refreshing As… Coke Zero” – Team Coke Zero

Yong-Woo Cho and Kyu-Soo Han of Team Coke Zero share many interests: they go to the same university. They both major in computer science. They also share the love of… Coke Zero. So it didn’t take long for them to choose their team name. Devising a solution for their challenge topic wasn’t as simple. How did they come up with a solution just as refreshing as their team name, Coke Zero?

For companies like POSCO, ocean cargo shipping is crucial, which is incredibly dependent on wave action. Hence the challenge topic of its AI contest, predicting the big swells. The members of Team Coke Zero who have been studying AI and deep learning since earlier this year found this topic especially intriguing.

To predict the result, they worked with meteorological data from a total of 33 observatories along the coast of the Eastern Sea, from Donghae, Ulsan, Ulleungdo and Dokdo island. The main predictors were water temperature, significant wave height, wave period, wave direction and wind direction. All data were observed at one-hour intervals.

For computer science students like Cho and Han, figuring out the exact causes of big swells was especially challenging. So they built an RSCNN model (Random Shuffle Convolutional Neural Network) to establish the relationships between a total of 248 spatial and temporal predictors. Each model they designed learned a different predictor bundle and the team generated dozens of such models. Through the application of ensemble technique, the team completed a solution predicting either the presence or the absence of big swells in the ocean.

Through the contest, Cho ‘felt more convinced’ about his chosen university major. Coming up with an AI model itself was challenging, but it was also rewarding. He has never had this much fun coming up with solutions for industry challenges. After the contest, Cho is feeling even more dedicated to AI research.

┃“I Taught Myself Artificial Intelligence” – Team Fast Learner

Unlike the other winners, Young-Bin Noh of Team Fast Learner doesn’t come from a science background – he is a Business Management student. He was also a solo contestant with no other teammates. What’s even more surprising was the fact that he studied artificial intelligence on his own. On reasons why he participated in the POSCO AI Challenge, he said that he wanted to receive professional feedback from field experts.

The challenge category Noh had chosen was to calculate how many lunches to prepare for POSCO employees. He chose this topic mainly for two reasons. Firstly, he wanted to practice dealing with text data. Text data mining, aka Natural Language Processing, is widely used and popular, so he always wanted to try his hand at it. Secondly, the challenge category didn’t require much background knowledge. So it was also a practical choice for a business student like Noh.

Noh utilized XGBoost algorithm, which creates hundreds of ‘decision-making trees’ to minimize prediction errors. Decision-making tree is one of the most basic algorithms in machine learning. Like the game of twenty questions, it narrows down the possible answers, ending up with one exact answer at the final stage. To further boost the predictability, Noh employed an ‘ensemble technique’ by creating one more XGBoost.

Noh admits he had to study harder after submitting his proposal, to prepare for the final presentation. The POSCO AI Challenge was an opportunity for Noh to connect with others who were studying data science more creatively. “I enjoyed teaching myself, but I also felt it would be great to learn with others, bouncing ideas off of each other,” he added.

Noh hopes one day the program he developed for the contest can be implemented to help reduce food waste in POSCO cafeteria.

The POSCO Industrial-AI Solution Challenge is now over, but the winners aren’t slowing down. Throughout the contest, they have been running toward the finish line. Now that they have extra time to improve their models, they’re trying to perfect them as best as they can.

The members of Team Serio, Coke Zero, and Fast Learner all said the POSCO AI Challenge was a great learning opportunity, strongly encouraging other AI researchers to participate in similar contests. Simply participating in an actual contest can teach something new, but the contestants can also receive valuable feedback from field experts.

Throughout the interviews, the enthusiastic energy of the young researchers was not only palpable, but also contagious, all of them treating each question with thoughtful consideration. With their dedication, Korea’s AI future seems promising.

Chatbot is one of the latest and popular technology not only adopted by chat-based services but through a multitude of competing industries such as Web portals, shopping malls, and manufacturers. As such, big changes are is in progress with its continued adoption. Among the services, a work support chatbot is especially notable for fostering convenient and smart working culture.

It is not a easy to improve the long-established working style in bigger corporations. Yet the adoption of chatbot technology encourages  improvements in efficiency that are unexpected. POSCO and its employees anticipate its role in the work culture. 

POSCO is rather open to adopting its work support chatbot services. The trial run of “People Search” chatbot service took place August last year. Since June this year, its function was upgraded along with the add-ons of document and email search services.

What is the reason for its adoption and what makes it so special? POSCO Newsroom met with developer (Min-ju Cha, Deputy Head of POSCO ICT) and planner (Min-ho Shin, Deputy Head of POSCO Information Planning Dept.) for an interview designed with POSCO’s actual chatbot chat window below.

POSCO is accepting applicants for the fourth round, offering free education courses on artificial intelligence, big data, and IoT for job seekers as well as the public.

Last year, POSCO along with Pohang University of Science and Technology (POSTEC) created education programs on AI, big data, and IoT in the form of basic online and advanced offline courses. The program comes as part of the company’s social contribution efforts offered free of charge to encourage these skills and broaden job opportunities.

Application for basic online courses are available for everyone until September 2 through POSTEC website. Upon completion of basic online courses, advanced offline courses are open to selected individuals for 10 weeks from September 3 through October 24 at POSTEC. To promote the offline program that provides intensive training in a short period of time, POSCO plans to actively promote these efforts in domestic universities and online communities for job seekers.

The four-month program is designed and carried out by POSTEC professors while equipment expenses are provided by POSCO. Basic online courses started out with six in the first round expanded to 13 this year. The first round of courses have ended on September 2. Over 6,000 students have completed basic knowledge on AI, machine learning, computational intelligence and more. POSTEC plans to take previous feedback into account to further enhance the quality of the courses.

The online programs on AI, big data and IoT were completed by 26,494 students thus far. The advanced offline courses completed by 49 students have successfully entered the domestic workforce  such as interns at POSTEC, regular employees at LG CNS, Kakao, and SK Innovation. POSCO plans to further advance the courses such as blockchain, cryptocurrency, and computer vision for students interested in even more specialized fields.

Meanwhile, Jeong-Woo Choi, who was elected as the 9th CEO of POSCO on July 27, presented ‘With POSCO(Building a better future together as corporate citizens)’ as a new vision at the inauguration ceremony, expressing his aspirations to create a better society through contribution. This program represents POSCO’s major social contribution activity, aimed at increasing job opportunities while enriching the country’s competency in the fourth industrial revolution.