Writing the future of AI to drive digitalisation in the metals industry

In this article ABB’s Frederik Esterhuizen and Tarun Mathur share their insights on the development of Artificial Intelligence (AI) tools for the metals industry and how they are implemented, while also describing some of the decarbonisation challenges facing the sector and how they may be overcome by working together.

“Decarbonisation is a target across the whole metals industry, but also within ABB’s manufacturing sites and facilities. We have a responsibility to lead by example, focusing on our customers, our supply chain and ourselves.” - Frederik Esterhuizen

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The future of steelmaking is digital and sustainable

First published in the July/August 2023 issue of Aluminium International Today

What is the position of AI in the metals industry, what is the current uses, and how is it beneficial to the industry?

Tarun Mathur (TM): Industry 4.0 is making an impact across many industries, including metals, through aspects of operational excellence, process performance, asset performance, sustainability and connected worker, all underpinned by cyber security. Looking at a customer’s digitalisation journey, big data and AI have become more significant if you look at the maturity of the metals market today. Even five years ago, only 10-20% of the industry was connected. Most producers had some automated systems, but they were working in silos.

Since then, there has been a transition where these islands of automation have been broken down, pieced together or replaced to create either an edge or a cloud where all the data can be stored, accessed and shared, enabling gains in productivity, quality and yield. It means that an industry traditionally known as conservative has taken a big and important first step. We have now seen, in the last two years, more AI applications relevant to the industry.

It is still a new area, but the potential is immense. We have more and more unrestricted or available data from across customer sites and the wider industry. Large organisations like ABB can also help to leverage big data from across the many industries we serve, adopting from others and working together. For any organisation, greater certainty of future conditions is valuable and AI can improve that forecasting.

Do you think that AI and automation has a role in combatting industry specific workforce issues?

TM: It’s well known that workers are reaching retirement age and working beyond because companies cannot lose their experienced, knowledgeable people. This is unsustainable and the use of AI and automation can help retain information for the next generations. ABB is exploring the implementation of an app for connected workforces. AI as an assistant can go some way to addressing metals industry challenges.

What does ABB do regarding AI in the metals industry?

TM: ABB is investing in AI applications across many industries. For us, in the metals industry, workforce is one area with tremendous potential to grow. We have built AI packages starting from the upstream stock yards, through pellet plants, into the steel melt shop, and then the downstream rolling mills. The applications will improve the operations or improve the asset reliability or the overall performance of the plants.

At the recent ESTAD conference, which took place in conjunction with the METEC fair, ABB presented on the topic ‘The Role of Artificial Intelligence in Digital Transformation of the Steel Industry’. We outlined some of the tangible ways AI applications can optimise energy purchase and production including at site power plants and turbines. It can lead to more efficient energy use and improved electricity procurement forecasts, with difference of 10-15% compared to alternative solutions. Data and optimisation modelling and rule-based energy management algorithms can lead to optimised energy consumption and energy security in operations.

ABB Ability Data Analytics for cold rolling mills enables metals producers to reach new levels of performance optimization

Frederik Esterhuizen (FE): At ABB, across the process industries, we have examples of customers choosing to use our Collaborative Operations Center, based in India, where we serve our global network 24/7. This deploys AI to help predict any future failures or potential maintenance issues, as well as pinpointing where the initial fault occurred, which makes it easier for the operator to find it. It is about building up a bank of cases and learning from the data over time for process improvements. We can connect multiple locations of the same customer to one set up, enabling improved end-to-end production visibility and therefore better decision making.

In metals, we can learn and conduct simulations on different scenarios because we have the ABB Ability™ Data Analytics Platform for metals in place. It offers plant and enterprise-wide data integration, monitoring, data analytics and optimisation from one feature-rich and fully scalable, vendor neutral platform. It brings together the islands of automation we spoke about earlier and devices into one powerful resource with applications for performance optimisation.

Do you have any examples of the implementation of AI in the aluminium industry?

TM: Some of the best examples of AI applications relevant to aluminium are sustainable energy management. To optimise energy use, you need to forecast requirements better. Here, machine learning applications (ML) of AI are much more advanced. Progress is being made, but further work must be completed to gather enough data and measurements from cycles of batches to successfully forecast energy consumption. If you can forecast your energy requirement on the demand side as well as on the supply side, and if you are connected to the electricity market grid, you can have a good decision-making system to optimise your energy purchase and minimise energy consumption.

Before the digital solutions can be added into the process, there must be a solid automation layer. This is where we rely on the constantly evolving ABB Ability™ System 800xA distributed control system (DCS). We know that it has been independently verified as the world’s No. 1 DCS for more than 20 years for its capabilities of networking, controlling and collaborating across plants or enterprises. Now with AI and ML, the massive amounts of data generated by the DCS can be analysed better to help customers to increase production efficiency, predict problems and extend asset life.

Process automation and control are key to high-performance metals manufacturing and a prerequisite for digitalised, optimised and sustainable operations. With this in mind, ABB has developed a range of solutions specifically aimed at aluminium manufacturers. Notable examples include ABB’s control loops for eccentricity and hardness compensation at Alunorf’s two-stand aluminium cold rolling mill in Germany.

Two further examples of ABB’s commitment to pushing the boundaries of digitalisation and automation in the aluminium space include ABB Manufacturing Operations Management for metals which is being used to connect the mine, refinery, smelter and rolling mill at the world’s largest fully integrated aluminium plant; while the company’s flagship ABB Ability™ System 800xA distributed control system (DCS) is deployed at the record-breaking two-strand vertical continuous caster at Dillinger Hüttenwerke AG in Germany.

Performance optimization services use the latest digital technologies to make ABB’s deep rolling mill process know-how available operationally to customers around the clock

The implementation of AI requires a balance between skilled professionals and digital solutions. Do you think some knowledge will ultimately be lost in the industry?

FE: ABB is a technology partner to the metals industry, where you can genuinely make a difference and an impact in the world using the latest digital tools and solutions. To support the industry of tomorrow, covering the need for electrification, automation and digital solutions, we are working with the foremost industrial players to innovate new solutions, as well as in upskilling and talent sourcing. Diverse perspectives and ideas enable us to learn, grow, and reach greater goals. That is why our priority is to provide interesting career opportunities that helps to attract the right talent mix. We are seeking skilled professionals, including the younger generation, with competence in areas such as data science, analytics and sustainability.

Factory acceptance tests (FAT) have been carried our remotely using guidance systems from VR and AR, and with the backup of our experts around the world. Where applicable, this avoids flying workers long distances to isolated locations to reach customers. We have all the data available and access to the FAT on the site. There is an understanding on both sides that the technologies are here for people to work in their preferred location yet impact operations in the mill.

We continually devise solutions for remote operations, and these have the added benefit in sustainability. Experts are now typically available in central locations covering a number of customer mills. Taking ABB Ability™ Performance Optimization Service for cold rolling mills as an example, ABB offers customers an enabler to combine process-specific algorithms with real-time continuous monitoring and remote support from ABB experts. It’s one advanced digital service that shows the direction the industry needs to go to reach new levels of operations.

What is ABBs view on the future uses of AI?

TM: AI and ML are under a broad umbrella of physical and virtual technologies. They are only as good as the available data and, in my opinion, some parts of the metals industry are not currently ripe for reaping the benefits. For example, measuring the temperature of molten metal at such high temperatures cannot be done continuously with the equipment and technologies available today. We must work with a careful blend of digital tools and automated tools, backed by operators and experts in the field. ABB is focusing on assistive AI, helping the workforce to extract more productivity, quality, yield, and of course data. We can see a future with many more possibilities as we improve together.

Do you think there should be limitations/regulations on AI?

TM: People often speak about 100% autonomous factories, but the current reality is we need people, whether that’s on site or in a remote central location. There’s a mutual understanding in the metals industry that technologies can help make the impacts needed for people to reach company goals and global, wider societal targets around energy and emissions.

It’s a balance between accuracy, the product and safety. When you implement AI, you improve the accuracy, but humans have their intuition and deeper expertise on working practices, including safety, which cannot be replicated in AI, yet.

AI can, if not adopted well, view production as its only target and disregard safety, relationships in the workplace and social sustainability factors. AI must stay onside as an assistant to humans as every company must consider the purpose behind using these tools, which is often to improve the world for people to live and work in now and in future generations.

About the interviewees

Tarun Mathur

Tarun Mathur is Global Industry Consultant for ABB’s digital portfolio for the metals industry at ABB. He holds a Master’s degree in mathematical modeling and process control and has held several positions in R&D focusing on the development of advanced model-based solutions for process industries. Tarun is currently focused on projects applying new digital technologies to optimize steel plant performance, process and quality.

Frederik Esterhuizen

Frederik Esterhuizen is Global Business Line Manager for ABB’s metals industry portfolio, leading a global team of experts committed to helping metals manufacturers improve sustainability, quality and safety in their operations. Throughout his career, he has held a variety of roles in Engineering, Operations and Management across multiple industries. He holds a National Higher Diploma in Electrical and completed Project Management studies with distinction.