The metals industry thinks big and gets practical about digitalization

Working alongside visionary leaders on their most critical challenges often results in new industry perspectives.  In this article you will get practical examples on how to envision, create and manage digitalization initiatives and capture real value.

Originally published in the December 2021 issue of MPT International

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The metals industry is under great pressure to transform from an environmental, political, and cultural perspective - and this pressure will continue until major action is taken. Our customers are setting ambitious goals for energy management and emission control, increased productivity, uptime, better operational cost control, and optimized capacity. A complete paradigm shift and new ways of achieving these goals become possible through digitalization. Eager to attract the next generation of digitally literate talent to whom issues such as climate change are a genuine concern, companies want to demonstrate that they are serious about sustainability and innovation.


So, how can we bring the metals industry’s digital plants to life? It all starts by envisioning the future. Powerful integrated solutions speeding up decarbonization. New business models that ensure value outcomes and competitiveness. Autonomous operations across transparent value chains. No company can do it alone. We believe that this can only be achieved by collaboration with the best ecosystem partners. When embarking on a digital transformation journey, it is also important to balance both short and long-term targets, driving rapid change while keeping sight of the larger vision.
ABB is enabling process industries customers to achieve their vision for digital operations
Data gathered by metals companies is essential to reaching digital potential

Sanjit Shewale and Tarun Mathur from ABB share their insights about metals producers successfully converting from conventional to more modern operations that are safe, smart and sustainable.

 

Making an impact, layer by layer

Today’s business leaders require organization-wide visibility and control, so that they can quickly evaluate how production is impacted by rising material costs, adapt pricing strategies, and better manage supply chains and assets. Therefore, data integration at all levels – from equipment, and processes, to engineering and business systems – becomes one of the core business imperatives. Metals producers are already generating a lot of data, but are struggling to make it valuable for digital applications, ready to communicate towards the cloud and the shop floor in real time – and affordable. Digital apps simply do not make sense without such trusted data.

In real-world scenarios, converging operational technology (OT), IT and engineering data can be challenging, especially when enterprise information infrastructure includes heterogeneous information systems. Most metals plants also live with incompatible legacy OT systems which can become a massive hurdle to integration.  The integration process therefore requires expertise on both the domain and system levels, and specific connectivity solutions.


ABB has the right combination of domain-specific expertise and knowledge of both OT and IT infrastructure to ensure that your data management approach is closely aligned to your business strategy. We know how to properly label, model and structure industry-specific data, how to store, compute and stream high volumes of data securely and cost-effectively. Traffic between layers can be secured and controlled down to the smallest detail.

When basic data requirements are fulfilled, there are plenty of potential use cases opening new possibilities. 
ABB recommends user-friendly dashboards via web page or mobile

From our experience, the pain points that often come first are

How to improve my disparate equipment availability and ensure my processes are running at the most optimal and profitable level?
And we agree with this, because when assets or processes do not run reliably and optimally, you reduce, restrict or stop fulfilling your higher-level business goals.

When focusing on running assets and processes optimally, it’s important not to treat them separately. The real value comes when you start uncovering previously hidden relationships and correlations. We are helping customers improve interactions with other parts of the value chain, and get people engaged on all levels in real time, so that everybody is working towards common goals with a sense of belonging to one family. Questions from the operations people that we often help to address:

How to manage all resources in real time and provide contracted product quantities and qualities faster?

Companies focused on continuous improvement are eager to explore how powerful enterprise-grade industrial analytics and artificial intelligence (AI) can provide them with still deeper insights about their activities, asset or process behavior and reap the benefits of higher productivity, lower energy/emissions, better industry reputation. Leaders with the need for deeper actionable insights are asking:

How to get real-time visibility to my business, mill, process or equipment - no matter location or time?

When lacking in-house experts in certain areas, metals producers are also turning to ABB in order to get fast access to the best experts for cyber security services, predictive maintenance, critical equipment or process performance optimization and shared risks.

We have recently supported a steelmaker to establish a data platform delivering exhaustive plant data collection and smooth data flow upwards, enabling meta-data – structure and information within data itself and a site data lake – with cloud connectivity.  Further options could be: cloud data lake, data integration for specific customer’s digital use cases, edge computation service environment – KPIs, calculations, applications, visualization services, training and support. The data platform will be used by this steelmaker for better production knowledge and continuous improvement (like speed, quantity and price), equipment condition monitoring (for availability) and more. We also ensured the reliability of sensors (avoiding temperature drift) and opened production data to customers (for direct sales).

What digital solutions are out there?

Technology leaders obviously wish to see plants adopt new solutions to benefit operations, but sometimes the digital landscape can seem quite intimidating, with a plethora of vendors and software solutions. Decision makers in metals companies’ c-suite, managers and operators alike have to be convinced and with technology applications they can see and feel it working.

What solutions are out there and how can they be applied to create value? We have selected real-life examples providing evidence that digital transformation strategies are working and demonstrating value in the metals industry.  There are five digital solution areas in our portfolio, representing the following value pillars.

The shop-floor and top-floor can be more connected, with greater visibility than ever before

Operational excellence

Operational excellence is about flexible manufacturing execution, improving insights from operations by integrating different areas – from production to upper-level systems – and optimizing costs across distributed plants. This includes key performance indicator (KPI) monitoring, analytics and remote operations capability.

One of the largest manufacturers of metal and flat steel products in the Middle East and North Africa region Al Ezz Dekheila Steel Company Alexandria S.A.E. (EZDK), implemented ABB’s Manufacturing Operations Management (MOM) system tailored to metals processes — including complete tracking from furnace charging area to C hook conveyor. It provides EZDK with 24/7 and year-round access to production management system dashboards from any mobile device, making it even easier for them to visualize their processes and utilize the information provided to further optimize operations.

Working alongside Sunflag Iron and Steel Company Ltd. in Bhandara, India, ABB has tied together all manufacturing and operational data from steel melt shop and rolling mills to improve production planning and plant performance optimization. The plant, which has a capacity to produce 500,000 metric tons of high-quality special steel per annum, now has the platform to integrate data sources across 17 operational areas, including non-ABB systems. ABB integrated with the existing automation systems for process and quality monitoring in real time, aligning with user-friendly operator dashboards available via a web page or mobile. The platform enables identification and diagnosis of issues or use of extra resources. This is allowing for better decision making and will ultimately show long-term returns in productivity, quality and resource efficiency.

Meanwhile, JSW Steel Ltd, India’s leading steel company, adopted a complete smart factory solution for energy-efficient, safe and productive melt shop operation - which is unique in the industry. This digital solution connects steel melt shop operations with ladle and crane tracking and thermal loss prediction for higher casting speeds and additional output. It addresses one of the major challenges facing steelmakers today, which is to maintain the optimal temperatures required to make molten steel while balancing high electrical energy costs. Ensuring the right temperature at the right time, together with other parameters in the molten steel, directly determines steel quality and productivity. JSW Steel expects to increase the company’s EBITDA profit by around 2 million USD per annum through four percent higher casting speeds, time savings of one working day per month and additional output equating to 24,000 tons a year. In wider benefits, the lower energy consumption means fewer consumables used per batch and therefore a lower carbon footprint with less CO₂ per ton of steel produced. Automatic tracking and scheduling enable better maintenance planning and increases personnel safety as they are removed from the production area during crane and ladle movements. The scheduling solution also results in reducing tapping delays by ensuring these movements are synchronized with process requirements.

Based on advanced digital algorithms and mathematical modeling, ABB Ability™ Smart Melt Shop is a true example of technology convergence as it utilizes cameras and image-processing, weighing systems, radar, laser and wireless-based technologies to ensure steel melt shops operate at optimum levels where crane and ladle tracking and their availability are critical to the entire steelmaking process.


Another premier steel manufacturer in India suffering from poor visibility across 35 systems from different vendors with multi-level, hierarchical structure wanted to get a better understanding of complex interrelations of energy flows, operational modes, and other aspects. It turned to ABB to establish a Central Command Center for better plant operation planning and coordination between multiple processing units. Now the production data, downtime, movement of heats, raw material - trends, statistical process control (SPC), alarms and events – are continuously monitored. ABB’s data analytics for production solution analyzes complex, large data across time frames and facilities, leading to significant savings from solving production bottlenecks and quality issues.

Process performance

The process performance area includes solutions around advanced process control (APC), optimization and related services. This lets the industry achieve sintering and pelletizing process stability, improve quality and output, reduce costs by employing Model Predictive Control that acts as an 'autopilot' and sustains benefits over time.

At an Indian steel plant, the task was to maintain the outlet temperature at a desired setpoint. APC was implemented with dryer outlet temperature as the controlled variable and fuel flow as the manipulated variable. A model of dryer outlet temperature was developed based on plant data to include the fuel flow control valve and disturbance variables, such as feed rate. The model was used to predict the upcoming control performance, calculating setpoint corrections, which were then downloaded to Level-1 proportional–integral–derivative (PID) controllers.

APC maintained the dryer temperature even with changes in feed rate and process delays, achieving a 10 percent reduction in the standard deviation of the temperature. The implementation of APC stabilized temperature conditions within the dryer, improving overall performance and productivity.

Across any of the digital solution areas, there is always the opportunity to make enhancements with industrial analytics, AI and machine learning (ML).

Cold rolling mills have opportunities to optimize their performance and profitability through continuous performance monitoring and real-time expert insights. ABB’s data analytics solution for cold rolling mills helps carry out benchmark analysis comparing productivity, quality and yield for golden coil and actual coil. It lets you find out which process steps (threading, reversing, unthreading, acceleration, deceleration, minimal speed, operation speed and slowdown) are having a negative impact on your productivity. You can investigate your thickness deviations including related sensors, actuators and control loops or find the root causes of your exit flatness quality issues. If you want to know the state of your mechanics, motors, drives, and automation platform or if you are simply unsure about which issues to prioritize in terms of potential performance improvement, our analytics engine specific to cold rolling will help you focus on the right goal, attain optimum rolling setpoints and achieve world class strip quality and uniformity at the highest rolling speeds.


For bar mill or wire rod mills with large amounts of plant and process data it is also not realistic to manually monitor all the important KPIs - due to a large number of data sources and process variables. Operators need more advanced tools to help them better understand the trends and inter-relations between the process parameters that cause faults and failures. ABB’s data analytics solution for long product mills is increasingly used for this purpose, but success in digital depends on the availability of process expertise in both implementation, operation and maintenance of such tools. Combining data analytics, process-specific algorithms, real-time continuous monitoring and remote support from ABB experts allows our customers to access a much higher level of process insight, preventing cobbles and continuously improving yield, quality, productivity and margin.

Asset performance

Asset performance is about increasing the uptime of the plant through asset monitoring and failure prediction, prolonging the life of an asset and achieving the best performance from it. Asset-intensive industries, including metals, have a focus on reducing maintenance costs.

One of Europe’s largest steel producers CELSA Barcelona deployed ABB’s asset condition monitoring solution. The application monitors the health of a variety of production assets, including automation, instrumentation, electrical, mechanical and process equipment. For CELSA, it has meant a complete overview of its production assets’ health, avoiding unnecessary maintenance and unplanned shutdowns, reducing exposure to hazardous areas and speeding up repairs. According to ARC Advisory Group, 18 percent of assets have age-related failure patterns, and 82 percent of asset failures happen at random intervals. Switching from time-based equipment inspections, without any sensors on assets, to checking equipment health status online, with real-time predictive notifications means faster decisions, easy root-cause analysis for quick failure detection, faster corrective actions thanks to the recommendations and continuous improvement culture.

Like the other pillar, the next generation of Asset Performance Management (APM) solutions is getting enhanced by AI and ML. At ABB, this is underway with ABB Ability™ Genix APM suite. Asset performance management means different things to different people, who have varying degrees of difficulty to locate and analyze data across an organization. Some assets do not last their originally predicted design and service life. It is also common for assets to operate past their design life, and that might result in performance problems and safety risks. Genix APM, based on the industrial analytics and AI platform, helps you get the most from disparate data sources. It automates data integration, lets you identify previously hidden relationships, correlations with processes, analyze performance trends, make timely predictions and accurate asset life assessments.  The business value from the holistic view and tighter control over assets is tailored to specific roles in your organization and enables cross-enterprise actions.

This can only be achieved if you trust the people who are building the optimization models: their deep process expertise, the know-how of your operations, processes and asset behavior. Now, their expertise and ingenuity can be captured and shared on a common platform - augmented with edge, cloud and ML technologies for maximum impact. We are particularly excited about this new APM solution, which will be a step change for the industry.

Sustainability and connected worker

In addition to the recurring challenges of optimizing efficiency, maintaining throughput and quality control during high-volume production, metals producers must now comply with increasingly strict environmental legislation aimed at reducing emissions, or face penalties. Iron ore reduction is where the vast majority of carbon emissions come from in steelmaking. Transforming the ways to make steel depends on the energy sources available. But the world will continue to rely on iron ore until around 2100. The carbon challenge for the industry in the coming decades must therefore be to transition to alternative sources of energy and to optimize their use for iron ore reduction.

The sustainability solution area reflects the need for managing environmental compliance and reporting for energy, water, emissions and waste. For example, in a European steel plant with an annual capacity of up to five million tons of steel, complex distribution networks for electricity, steam, by-product gases and imported fuels make up to 20 percent of production costs.

Digital energy management in steel industry has a proven track record of short payback times and long-term benefits. It not only optimizes costs, throughput and quality, but also energy-related costs, raw material usage, carbon, greenhouse gases and waste emissions. It relies on decades of experience in the process industries, and steelmaking in particular, captured in predictive energy management algorithms. 

ABB’s energy management software is successfully used by the above steelmaker for site-wide optimization: managing energy purchase and production. It assists gas dispatching, calculates optimal power production based on real-time data and is adapted to power market. It also optimizes energy consumption and secures energy availability considering steam yield, consumption of by-product gases, energy purchase and production including site power plants and turbines. We helped this customer achieve 10 percent less flaring of gases thanks to data and optimization model and 15 percent accuracy improvement of electricity procurement forecasts. 15k€ per month are saved on average every year.


Waste gas utilization in metals production can be greatly improved by monitoring generation and consumption across plant facilities in real time. Data is collected from multiple systems to compare allocation with actual consumption, provide real-time demand and supply calculations, balancing, benchmark and optimal distribution as well as forecasts based on production plans and historical data modeling. Root cause analysis is also applied to the data whenever a gap occurs between supply and demand.

Complementing digital energy management systems with data contextualization and digital twins can   further optimize energy consumption through load profiling and balancing, process parameters (such as air temperature at compressor intake etc). The latest possibilities from an enterprise-grade platform and suite of AI and ML tools will let you deploy and monitor advanced controllers, data analytics and optimization solutions at the edge, to and from an industrial cloud/multi-cloud or on-premise.


Safety, productivity, compliance and training of your workforce in these areas can also be more effective through software solutions, where knowledge retention is an issue for companies. The industry rarely has key experts in the same role for 25-30 years as was the case in the past, so there is an opportunity to retain and speed up knowledge transfer through simulators and technology advances from the augmented reality (AR) and virtual reality (VR) space. We are working on helping companies move towards an immersive workspace with mixed reality (XR) helping people master necessary skills more effectively and faster, establishing a foundation of consistency no matter the personnel.

Supply chain optimization

Supply chain optimization goes along with planning and scheduling, with steelmakers looking for decision-making and end-to-end material tracking. A compelling example is ABB’s Stockyard Management System, which enables real-time supervision, planning, automated reporting and simulation of bulk stockyards, and in doing so opens the door to fully automated and autonomous operation of material handling chain and stockyards. It gives users a high level of situational awareness showing utilization of material, available quantities and qualities. It is also a formidable job scheduling, optimization, reporting and forecasting tool, and can include full-site automation for major handling machinery, increasing stockyard productivity by 5-10 percent.


ABB recently concluded a successful project for a German steelmaker seeking a quick digital solution for material batch planning and quarterly yard inventory validation. Thanks to the ABB solution including 3D stockpile visualization, quality allocation and automated inventory estimation modules, the customer gained a much higher degree of transparency, resulting in better blend quality, optimization of material sourcing and trading, and overall production planning. Capacity utilization got improved by stacking multiple ores in a single pile. Barge and train waiting time was reduced as yard planning and optimization became faster and more efficient.

Bringing it together

Digital transformation discussions will continue between the many process industries leaders and technology implementors and innovators.

The increased complexity requires the ability to master very different technologies, industry-specific processes, cyber security and provide the needed consultancy and assistance to the end users from the early design stages up to system commissioning and maintenance. The reward for metals plant owners adopting digital solutions will be better performances at a reduced capital cost, overall standardization of operational, process, maintenance, environmental and supply chain management practices, which will help in reducing and managing the inherent complexity.

Today we are able to establish a single source of truth system for all information related to all the five solution areas. By combining perspectives between the shop-floor and top-floor, it directly contributes to strengthening your continuous improvement cycle. With energy cost, efficiency and environmental implications gaining top priority globally - particularly for heavy energy consumers - new digital tools are being developed at a much faster pace than ever before, in collaboration with customers, universities, and other ecosystem players. Let's join forces, co-develop and collaborate to set new standards for the metals industry!

Energy management and monitoring is possible to realize cost savings

Biographies

Global Product Manager, Metals Digital at ABB

Tarun Mathur joined ABB in 2006 and has held several positions in research and development, specializing in the development of advanced model-based solutions for process industries. In his current role, Tarun focuses on projects applying new digital technologies to optimize steel plant performance, process and quality. Tarun graduated from the Indian Institute of Technology, Mumbai, and holds a Master’s degree in mathematical modeling and process control.

Head of Digital, Process Industries, ABB

Sanjit Shewale joined ABB in 2020 as the Head of Digital for Process Industries. He has 20+ years of experience in the advanced industrial software space across many different verticals, including discrete. Most recently, he was with Honeywell’s Connected Plant & Advanced Solutions and Danaher’s Product Identification business. Sanjit holds a Chemical Engineering degree from McMaster University and a Management Sciences degree from University of Waterloo. At ABB his focus is on digital strategy and sustainability. He writes about ways to accelerate the shift to carbon-free and energy-efficient operation, autonomous systems, remote management, asset performance and more.

Learn more

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Digital transformation in metals and steel industries
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