Here’s a look at how steel is produced in a steel mill or factory, and what the “smartization” of steel factories will look like.

So, how is steel made?

Iron Making

To make steel, manufacturers first need molten iron. Molten iron comes from two raw materials; iron ore and coal. Iron ore is converted into sinter ore in a sintering plant and coal is converted into raw coke using a coke oven. The processed materials are poured into a blast furnace where hot air reaching 1200℃ is blown in from the bottom through tuyeres, causing a chemical reaction. This process oxidizes the coke and reduces the sintered ore, creating molten iron.   

Steelmaking

In the steelmaking stage, the molten iron is transported to the steel making plant via a torpedo car, where the liquid is poured into a converter. Then, oxygen is blown into the converter to burn off all the impurities. All that is left is pure molten steel.

Continuous Casting

This is where steel finally becomes solidified into different shapes such as slab, bloom and billet. Liquid steel is poured into molds and cooled as it passes through a continuous casting machine until it solidifies into the desired shape.

Hot steel passes through rolling machines to be rolled into specific sizes and thicknesses. (Source: Global Sourcing Blog)

Rolling Process

During the rolling process, steel is heated once more to achieve various sizes and thicknesses. Steel slabs are heated to over 1100℃, then pass through rolling machines. This results in hot-rolled coils that can be shaped for different uses such as thick plates. They can also be processed into long, wire-shaped rods for billets. Often, the hot-rolled coils are rolled at room temperature for cold-rolled coils. Cold-rolled coils can be fabricated to produce galvanized and electrical steel products.

“Smartizating” these processes will involve converging IoT, Big Data, and AI to connect the different facilities, IT systems and workers in order to collect and analyze data for optimization.

POSCO is “smartizing” the steel-production process

POSCO is a steel company looking to lead the industry in adopting smart factories. CEO Kwon Ohjoon made “smartization” one of the 4 key priorities for POSCO starting back in 2014, and Kwon will continue to increase those investments.

POSCO smart factory incorporates artificial intelligence to enhance safety and efficiency.

SEE ALSO: How Smart Factories are Changing the Manufacturing Industry

In 2016, POSCO established its Smart Solution Council in order to research AI, big data and IoT applications. In the same year, POSCO ICT’s smart factory platform, PosFrame, was completed and installed in POSCO’s Gwangyang Steel Mill. PosFrame allows engineers to collect and monitor big data. So far, the company has saved over USD 14 million by incorporating the new technology in its production practices.

Here are some other features of POSCO’s Smart Factory.

POSCO’s Smart Blast Furnace

The Pohang Blast Furnace No.3 became a smart furnace in 2017, following a 102-day repair period. The furnace is now equipped with automated sensors that monitor and control its internal conditions using AI technology. Smart sensors monitor the blast furnace for factors like raw material quality and ventilator status, preventing breakdowns and ensuring a much longer lifecycle.

SEE ALSO: Will Artificial Intelligence Lead to Breakthroughs in the Steel Industry?

Worker Safety

Smart sensors can be used for more than just process monitoring. The company is working toward a full implementation of smart sensors for safety purposes, using IoT to create a better working environment.

Steel manufacturing involves high temperatures and high pressure levels, which is dangerous for workers who come in close contact with the equipment. With smart sensors monitoring all of the factory information, workers will instead be monitoring operation from a safe distance.

Workers in POSCO’s smart factory wear smart sensors for safety.

Wearable sensors, in conjunction with factory smart sensors, will be able to detect if and when workers are approaching potentially dangerous areas, and will alert them. These sensors will also detect and alert with regards to any impending accidents, or life-threatening situations like gas leaks, explosions, or fires.

Also, dust, sulfur, and nitrogen compounds will be removed via a high-plasma method, creating an eco-friendly steel plant and a healthier environment for workers.

POSCO will continue to add more smart features to its steel mills to increase efficiency, safety and sustainability. In efforts to learn and implement new technologies, POSCO CEO Kwon Ohjoon visited GE’s smart factories to learn about their technology earlier this year. POSCO also held the 2017 Smart POSCO Forum to share its insights with clients and affiliates, all as part of its expanding smartization efforts.

POSCO’s smart safety features

As a steelmaking company, POSCO has been working towards becoming a “Smart POSCO”, or incorporating the implementation of AI into their production practices. In 2016, POSCO established a Smart Solution Council to research AI, big data and IoT applications. To date, the company has achieved a cost reduction of USD 14 million with the new technology. Even as one of the first steel producers in the world to implement a smart factory for production, the road ahead is a long one. Members of the discussion panel at the 2017 Smart POSCO Forum offered their expert opinions on how companies should move forward with AI research and applications.

Problem Mining

“One of the biggest difficulties in applying AI to manufacturing companies is problem mining. The only way to solve a problem is to find it and define it.” Kim Byung-In, a professor at the POSTECH Department of Industrial and Management Engineering, started off discussions and added, “Along with problem mining, people can learn from the past with reinforcement learning. Reinforcement learning means learning through similar tasks from the past to apply to new assignments. Defining problems and solutions more precisely and systematically managing related keywords can be useful for future tasks.”

Professor Zhang Byoung Tak, an AI professor at Seoul National University and a distinguished professor for POSCO added, “Traditionally, people solve problems, but in the generation of AI, AI will be able to solve problems for us… People now have to focus on defining problems, implementing systems and getting the right kind of data.”

Cooperative Research and Investment

Along with defining the exact problems that AI can provide solutions for, the implementation of AI will also call for a new working culture for companies and industries.

Tech company VUNO CTO Jung Gyuhwan stated, “Each company has its own production or operation method, and different data formats and protocols, but product inspection and screen UI (User Interface) are common areas. If we can find such common areas that can be commercialized and continue to research ways to expand AI applications to different sectors, we can achieve meaningful results together.”

Researchers developing programming and coding technologies

Jung went on to highlight that most AI personnel are unfamiliar with manufacturing. In particular, steel production terms are so difficult that it takes a considerable amount of time to share and understand information. There are also numerous obstacles and obligations for startups entering an unfamiliar development environment full of regulations and restrictions on things like the use of codes.

“In other words, task efficiency is a trade off with information security. I believe that if there is such a process in POSCO where the risk of technology leakage is not high, it will speed up results through collaboration with start-ups. POSCO ICT in Pangyo is a good place for startup employees to work. If we can take advantage of the POSCO ICT databases, collaboration with start-up companies will be easier. As of now, there are not many AI companies in Korea that specialize in manufacturing. Most people don’t even know that there is a lot of data available in the manufacturing industry. That’s why fostering start-up companies specializing in manufacturing now, is a good idea.”

Google’s Fei-Fei Li announces Google’s acquisition of Kaggle. (Source: Venture Beat)

According to CB Insights, M&A (mergers and acquisitions) of AI startups have increased 700 percent since 2011, because they are more efficient and often more insightful when it comes to AI research. Besides investing in existing startups, members of the panel agreed that collaborative competitions such as Kaggle, a contest platform where data scientists from around the world participate in solving problems in industry and society, are a great place to find talent and foster them as start-up companies.

Tackling New Challenges

The flurry of activity around AI research shows just how new the sector really is. People are still finding ways to apply AI across different sectors and industries. In such a volatile environment, how do companies and researchers navigate their way forward?

According to Choi Heeyoul, a professor of computer science at Handong Global University, companies need to “start where the people, problem definition and data are ready. Whether it is in production, sales, distribution, etc., if there is the will to solve problems, then results will follow. Especially when collecting data, you need the help of data analysts. For example, classification data for different types of steel can only be analyzed if the history of the classification criteria is recorded. Speech recognition is not any better for AI application than other fields, yet the most active and productive research has been completed in this sector. This is attributable to the will to apply AI, the abundance of accurate data and close cooperation with data analysts.”

Obtaining accurate data is vital for AI research

Professor Zhang Byung-Tak had another approach to offer. “I hope people will boldly take on challenges. The dramatic increase in computing power can now enable attempts that were previously considered reckless…No matter how much data we gather, it will never be enough. We need to approach problems as experiments and just start. One way to go about it is to work in reverse instead of waiting for data to be accumulated. You can start the task to define the data that is needed and determine the coherence of the data to the task.”

Lee Jong-Seok, a Professor at Sungkyunkwan University added, “When we are defining problems, we need to separate them into ones that can be solved in the short term and ones that require long term solutions. Some problems can be solved with minor improvements, while other problems will persist. For the latter, it is important to have patience and invest in a solution over a long term.”

That’s exactly what manufacturing companies are doing. They are collecting data every stage of production all the way to sales and administration. Big data is now available to study and apply to boost companies’ efficiency, sustainability and performance. Those who come up with the optimal software and modeling systems for data analytics will win the competitive edge early on.

UNIST professor Choi Jaesik echoed the panel’s sentiment, in closing, saying, “It’s very uncommon for a manufacturing company to hold AI courses for all their employees. I think POSCO can take pride that…POSCO is a great place to apply AI and achieve results. There is already plenty of data on site and employees are continuously working to obtain more accurate data. I look forward to seeing what POSCO will bring to the advancement of AI.”

POSCO CEO Kwon Ohjoon plans on doing exactly that, by increasing investment in research and implementing AI technology where applicable. Read more on POSCO’s smartization efforts here.

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As many as 700 people attended the forum including POSCO Group affiliate employees, as well as those of POSCO’s major suppliers, outsourcing partners and AI-related professors. Notably, employees from Nastech and Korinox, where POSCO is carrying out smart factory support projects, participated as well.

POSCO CEO Ohjoon Kwon watching a presentation at the forum

“POSCO must continue to take up the challenge of implementing a smart POSCO in preparation for the dawning of the 4th Industrial Revolution. We will apply smart technologies to all processes of the steel mills, as well as to management areas such as finance, HR and purchasing to realize the concept of smart management,” stated POSCO CEO Ohjoon Kwon. “We will actively share the results of POSCO’s smartization process with our group affiliates and customers.”

Mi-hwa Park, head of the POSCO Information Planning Department added, “To realize a smart POSCO, we started the Smart Solution Council headed by our CEO last year, and identified 141 smart projects which applied Big Data and AI to solve practical problems. Approximately 600 employees participated in the projects and reduced costs by KRW 15.7 billion.” She added, “We will develop a POSCO-style SME smart factory model to support innovations for the manufacturing sites of our SME customers and suppliers. Furthermore, we will contribute to fostering SMEs and creating jobs by providing a lighter version of the PosFrame, developed by POSCO, as a customized smart platform for SMEs.”

POSCO CEO Ohjoon Kwon with the excellence award recipients

POSCO also recognized projects that applied Big Data and AI, for excellence in the steel production category. Out of the four, one improved the flatness of steel sheets and another provided improved technology for slab production. The “3D-based design/construction quality improvement” project that uses POSCO E&C’s Virtual Construction to predict risks, and the “power generation output through condenser performance diagnostics” project that can accurately detect errors in POSCO Energy’s power plants were also among those selected.

Forum participants were given an opportunity to experience POSCO’s smart solution platform PosFrame firsthand. PosFrame combines operational insights and IT technology to collect Big Data as well as process and monitor data in a way that allows participants to experience the reality of “Smart POSCO.” It was one of the most popular features of the forum among participants.

POSCO CEO Ohjoon Kwon looking at a PosFrame platform

POSCO also announced its plan to standardize the technologies and processes developed through smart projects, turn them into a technical package and actively incorporate them into its “Smart Solution” business to create added value.

Ki-won Na, CEO of Shinheung Automotive Co., Ltd., an automotive parts maker, said, “We received a lot of ideas applicable to our operations from the case studies presented today, and if we learn about POSCO’s Big Data analysis and utilization techniques in more detail and apply them, I expect it will greatly contribute to improving our productivity.”

POSCO joined hands with POSTECH to launch an advanced AI course earlier this year and is currently training 25 internal AI experts so that they can apply their AI knowledge in their field to solve problems and thus lead the way for a smart POSCO.

Also, POSCO has begun providing free AI education to young, underprivileged jobseekers in July and is now training 100 youths per year on both theoretical and practical knowledge. POSCO is also planning to support the customized SME smart talent development project, including practical education on AI and Big Data skills, for its customers and suppliers.

POSCO is actively planning to complete its smartization, meaning it will apply its “Smart Factory” to all processes of the steel mills, and carry out its “Smart Solution” business, which combines POSCO’s product technologies and services with smart technologies.

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