Who are the largest steel producers in South Korea?
South Korea’s POSCO is the largest steel manufacturer in South Korea and one of the top ten steel groups in the world. Data show that in 2018, Pohang Steel’s crude steel output reached 42.86 million tons, ranking fifth in the world and fourth in Asia. POSCO has been rated as “the world’s most competitive steel manufacturer” by a famous investment bank in the United States.
Looking at the Digitalization in the steel industry of South Korea from the perspective of POSCO and Hyundai Steel
Currently, Korean industries are working on integrating digitalization into their production and organizational processes to be more competitive in globalization. Digitalization is a complete program that includes all departments and operations in order to assess a company’s value chain and leverage digital. It is important to emphasize that digitization is much more than converting “analogue” data and documents into digital form. Instead, what is important is the integration of data exchange and management, the creation of efficient interfaces, and the linking of business activities.
In today’s industrial revolution, digital transformation is crucial. Next-generation sensors, big data, machine learning, artificial intelligence, Internet of Things, Internet of Services, mechatronics and advanced robotics, cloud computing, cybersecurity, additive manufacturing, digital twins, and machine-to-machine (M2M) communication are some of the new key enabling technologies. Digital technologies can be applied to new plants or modified to work with existing facilities.
Information and Communication Technology (ICT) systems enable the main features of Industry 4.0 (real-time, interoperability, horizontal and vertical integration of production systems) to solve many problems. In addition, flexible production requires flexible ways of working, which can be achieved through self-organization and multi-tasking abilities fostered by education and lifelong learning programs. Therefore, flexible working methods are crucial.
South Korea’s steel industry is facing challenges amid mounting cost pressures, intensifying environmental regulatory restrictions, and increasingly stringent product and service standards. Therefore, the Korean steel industry has been actively involved in several legislative initiatives, R&D projects, and digitization-related patent filings over the past few decades.
1 POSCO Group
Initiatives related to Industry 4.0 mainly include the smart factory working group of the POSCO platform, which released the first version of the Korean steel manufacturing roadmap, which covers a wider range of stakeholders, including factory manufacturers and R & D institutions. POSCO’s use cases include the following enabling technologies.
1) The Internet of Things (IoT) is a network of interconnected devices
The term refers to an interconnected world in which electronic sensors, actuators, and other digital objects are networked and linked to collect and share data.
The online monitoring system built on the Internet of Things system architecture has four layers: perception layer, network layer, service resource layer, and application layer. Such systems have been built and validated on a continuous casting line connected to the Team Center platform.
2) Big data and cloud computing analysis
In industrial fields such as the steel industry, traditional database technologies may face challenges in capturing, storing, managing, and analyzing massive volumes of organized and unstructured data. Big data analytics refers to algorithms that analyze historical data to detect quality issues and minimize product failures. Big data technology is currently being utilized to monitor and improve the quality of steel products. This technology uses new processing techniques to extract meaningful information from different data types, and conduct data mining and analysis to make accurate decisions.
With data collected in real-time from the production line, precise predictions of billet surface defects are essential to modify processes in real-time and minimize their occurrence. The main problem is that the samples of normal instances and defect instances are often unbalanced. Some scholars proposed a one-class support vector machine classifier (SVM) to predict the occurrence rate of slab failure under normal conditions using process data and environmental variables collected online.
Machine learning-based methods help extract valuable information and knowledge from existing data to create data-driven models for a range of applications, including material property prediction and product failure detection and identification. Cloud computing provides on-demand computing services in a distributed environment with high reliability, scalability, and availability. With this technology, everything is handled as a service (i.e. XaaS), which mainly includes SaaS (Software as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service).
3) Robot-assisted manufacturing
The technology relies on humanoid robots to perform tasks such as assembly and packaging. Automation and robotics have grown in importance over the past few decades as industrial demands for higher quality, faster lead times and reduced costs have increased. The surface quality of steel products can be significantly improved if existing technologies in steelworks are upgraded with the help of robotics and automation.
4) Production line simulation
In the steel industry, methods for simulation optimization have been developed. The goal of developing a decision support system is to examine possible modifications to design and operation. In addition, new numerical methods are used, such as meshless methods in modelling systems for the steel industry.
5) Self-organized production
This technology requires the automatic coordination of machines to achieve optimal use and output of equipment. Self-organizing production is associated with decentralized solutions rather than centralized ones. New combinations of resources, equipment, and personnel, combined with increased automation, allow real-time management of production networks.
It is a system that integrates computing, networking, and physical processes. Embedded computers and networks monitor and regulate physical processes, creating feedback loops in which physical processes affect computation and vice versa.
7) Intelligent supply network
By monitoring the entire supply chain, smarter supply choices can be made. There are many variables and objectives that must be considered when developing a supply chain for the steel sector. By incorporating models into the integrated supply chain, the Smart Supply Network improves the steel mill’s manufacturing process from start to finish.
8) Vertical/horizontal integration
Horizontal integration is the process of integrating resource networks and information networks within the value chain. Vertical integration is relevant for networked production systems and customized customer manufacturing in the smart factory of the future.
9) Predictive maintenance
Through remote monitoring, the equipment can be repaired before failure occurs. The predictive maintenance approach is achieved through a combination of equipment monitoring and intelligent decision-making processes. In order to help steel companies make decisions and improve competitiveness, machine learning and data mining methods can be used to extract useful information from data and correctly predict results.
10) Network Security
For Internet-based services, this technology should be given priority. A use case for cloud-based production monitoring demonstrated based on the Industry 4.0 reference architecture model, and a procedural approach to cybersecurity analysis according to VDI/VDE guideline 2182.
11) Enhancement work, maintenance, and service
The fourth dimension is the application of augmented reality, which supports action suggestions, remote assistance, and document generation. For steel companies, the technology has certain advantages, especially when it comes to optimizing maintenance services. For example, remote maintenance can be performed by virtually linked service professionals. This will reduce travel expenses and save time, and resolve issues quickly.
12) Autonomous driving logistics vehicles
The technology relies entirely on an automated transport network. Using intelligent software to assist internal logistics operations enables companies to optimize and speed up process production. The supply and disposal of raw materials and intermediate products, as well as the removal of finished products and the management of by-products such as bulk material or slag, are critical. By using an intelligent shipping control system, internal shipping orders can be planned and managed, increasing productivity and service levels while reducing costs.
13) Digitization of knowledge management
Due to an increasingly competitive market, the steel industry has worked to overcome major digitalization difficulties. While this process has begun, more improvements are still needed. The expertise and experience of the technicians on this topic are the basis for these improvements. But major barriers to knowledge and expertise utilization include diverse distribution among workers, forgetting in the human brain, and loss of knowledge due to employee turnover.
2 Hyundai Steel Corporation
Since 2017, Hyundai Steel has started to upgrade its intelligent factories, using artificial intelligence (AI) and big data to improve the production process and technology of steel plants. Since 2019, the company has been accelerating innovation management, promoting the establishment of “smart enterprises” with more development potential, and advocating enterprise-wide intelligence.
The Smart Enterprise is a concept that not only covers manufacturing and production but builds intelligent management across all sectors of the process, including systems and infrastructure. In order to achieve this goal, the company established a dedicated department related to smart factory technology, which is responsible for the intelligent management of processes, systems, and infrastructure under the headquarters of research and development and quality.
1) Using big data for steel scrap management
A typical implementation case of Hyundai Steel’s smart factory is the use of big data for steel scrap management. Steel scrap is the raw material for electric arc furnace operation and is the first process of electric arc furnace steelmaking. Electric arc furnace operation is the process of making steel using high-temperature arc heat and electric current flowing through electrodes. In the past, mixing different grades of raw materials was unavoidable when managing and storing steel scrap. Therefore, it is difficult to accurately grasp the grade and quantity of steel scrap input during actual operation.
To this end, the company introduced a big data-based system in the electric arc furnace, and also set up lightweight equipment in the raw material warehouse to divide the scrap steel into grades and display them in detail on an electronic map, and on the crane carrying the scrap steel Laser sensors are installed to display the crane’s location in real-time on an electronic map. All steel scrap transferred, stored, and charged from the raw material warehouse, relevant grades, and information are automatically entered into the electronic map and accumulated as data. This big data system can also predict and analyze the quantity of scrap required based on quality. Thereby reducing unnecessary scrap steel input in the short term and effectively improving the overall operation process, and in the long run, future product quality can be predicted.
2) Human resources
Recognizing the importance of human resource development for digital transformation, Hyundai Steel plans to expand the training of professionals in the field of information and communication technology to all departments, focusing on developing experts in the fields of advanced statistics and machine learning, which are critical to artificial intelligence. As part of this initiative, a “Digital Transformation Academy” is already in operation.
3) Process digitization
Even when processes are partially automated, it is possible to better optimize the entire steel manufacturing chain. As a result, the Korean steel industry will be better prepared for Industry 4.0 transformation. Process digitalization through online adjustment and optimization help to improve process flexibility and reliability, increase production through the use of digital technology, improve product quality, and reduce maintenance workload. For greater impact, the move also helps to increase energy efficiency while improving the environmental performance of monitoring and controlling operations.
In the long run, the key challenge of digitization is to integrate all systems and production units along three dimensions: vertical (from sensors to ERP systems), horizontal (across the entire production chain), life cycle integration (across the entire plant life cycle, from construction to decommissioning) and total integration (based on decisions taken during the steel production chain, taking into account technical, economic and environmental aspects). In order to provide interdisciplinary capabilities, the digital process needs to be based on a working model of interdisciplinary teams, tasks, and thinking. New IT, automation, and optimization techniques may make these achievements even faster. Additionally, it is possible to implement predictive maintenance programs through equipment monitoring and intelligent decision-making methods. Also, ML-based data mining methods can be used in this case to predict maintenance work and schedule it. Finally, knowledge management is also a key component in the digitalization process.
The optimization of individual production units and the interaction of the entire production chain is part of the digital future vision of the Korean steel industry. As a result, the highest levels of quality, flexibility, and productivity can be achieved in the future. It is foreseeable that digital applications will continue to play an important role in the future. Through methods such as continuous improvement, optimization, data synchronization, zero-defect production, traceability, intelligent and integrated manufacturing, and adaptive online control is finally realized.
In the next few years, to successfully implement digitalization, the Korean steel industry will also face many challenges, such as standardizing systems and protocols, better-organising workplaces, and hiring more highly skilled workers, as well as making investments and necessary feasibility studies so that Find the right frame. As a result of digitization, industries, and economies are expected to truly benefit from increased productivity. When it comes to the impact of digitization on the industrial workforce, new technologies have the potential to create jobs while also giving workers better qualifications.
Nonetheless, there are changes in the medium term that will have an impact on the industrial workforce for a number of reasons. In addition, the steel industry must operate within statutory limits to maintain its long-term viability. The rising trend in energy consumption and the urgent need to adopt low-carbon energy systems present challenges for the steel industry to apply digital technologies that may help to cope with environmental regulatory constraints.
The metals and mining industry is expected to eliminate all waste and emissions within the next few years while consuming half as much resource. The use of digital technologies can help improve sustainability performance, and processes should be designed that take into account industrial sustainability needs and feasibility and allow the testing of new business models. Reducing emissions and improving energy efficiency can enable a circular economy paradigm, while the adoption of high-performance components, machines, and robots will help optimize the use of materials and energy.
Article Source: China Iron and Steel Industry Association – “Looking at the Digital Development of the Korean Iron and Steel Industry from Posco and Hyundai Steel”