ABB ABILITY™ SMART MELT SHOP
By synchronizing the movement of ladles using digital and automation solutions, melt shops can detect and eliminate equipment or process bottlenecks to maximize throughput, while at the same time minimizing energy use per tonne of production.
Ladle tracking by itself is not enough to optimise melt shop operations, yet many vendors only offer ladle tracking solutions. ABB Ability™ Smart Melt Shop additionally offers how to pace the heats and ladles optimally while eliminating delays caused by either processes or cranes. This ensures the correct superheat at the caster and that there are no tapping delays at the arc furnace or converter; this additional functionality is a key differentiator for the company and customers.
Thermal loss prediction based on ladle conditions and forecasted delays in operations provides ladle furnace operators with the right lifting temperature prediction to ensure heats reach the right superheat at the caster, hence the opportunity for the steelmakers to increase caster speeds and higher production from melt shops.
ABB Ability™ Smart Melt Shop displays many attributes of an internet of things (IoT) solution in that it connects all the processes, cranes, ladles, and tracks all these different objects uniquely in the melt shop and applies algorithms to improve the production ecosystem.
What do we mean by a 'smart' melt shop? Take Uber cabs as an example. Customers are demanding a taxi to a certain location, with multiple users making the same request to a central server via an app. Uber looks at the availability in that area and then allocates a specific cab for a specific user.
Transfer this model to the steel melt shop, where you have multiple people requesting a crane to pick up the material at the right time. ABB Ability™ Smart Melt Shop makes the entire ladle and heat movement automated by tracking the cranes using radar technology, ladle transfer cars by laser and augmenting this data with an image-based system to track the real time position of ladles/heats. This data is then fed into the scheduling engine, which automatically generates and schedules crane jobs based on real time visibility, with pick up and drop location information made available to the operator on a screen.
Instead of only ladle tracking, ABB's solution extends to derive real values by scheduling crane operations, heat pacing and thermal model predictions to optimise melt shop operations with the preferred heats and speeds, and less arcing in ladle furnaces.
The ABB tracking engine has no sensors on the ladle itself, and instead radar- based technology for crane positioning and laser-based technology for transfer car positioning allow to logically and uniquely track the ladles in the steel melt shop. This alternative approach reduces the hardware footprint and saves melt shop clients having to spend time and money on additional hardware maintenance.
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.
Currently, the crane operations are manually coordinated. Typically, each process station speaks to the operator via walkie-talkie, with a manager overseeing the process to ensure each station gets the material it needs on time. Manual coordination may result in inefficient operations leading to delays in tapping ladle for EAF or delays in ladle transfer to the caster.
ABB automated crane scheduling, part of its smart melt shop model, encompasses job forecasting, route planning, automatic crane scheduling and automatic acknowledgement of jobs for optimal work allocation. For example, when arcing is complete, the system identifies that a crane is needed, creates a job list and dispatches the crane on time based on legacy and current production data.
By centrally visualising what is happening in the melt shop in this way, the tracking engine replaces inefficient manual crane management with synchronised operations that streamline production. A major reduction in tapping delays is observed after the implementation of the smart melt shop system. In addition, the crane operator's job is made easier, more predictable and less stressful via the automated generation of job lists, rather than coordinating operations via walkie talkie. Safety is also improved by minimizing exposure to hazards via full visibility of ladle and crane movements.
Effective superheat control for the heats at the caster is critical to running it at maximum speed. In addition to this, effective superheat control reduces the arcing requirement in processes like ladle furnaces, hence reducing the energy bill for melt shops. Lower superheat may lead to heat rejection at casters, while higher superheat requires casters to reduce the speed, hence loss in productivity.
The primary objective of ladle tracking and crane scheduling is to make the ladle transfer more certain, and hence calculation of thermal losses more accurate. Using forecast data from the tracking and scheduling engines, the system can predict the waiting and travel time for the ladle - and thus its thermal loss during transfer - and predicts the right lift temperature at the ladle furnace to avoid excess overheating so the caster can run at the highest possible speed. The thermal model takes into account the ladle's recent tracking history to make the predictions more accurate.
An increase in caster speeds of 4-5% is observed after implementing the ladle tracking, crane scheduling and thermal model.
In addition to production optimisation, automated solutions such as those outlined above improve safety. A melt shop is a dusty, hazardous environment, with hot metal temperatures exceeding 1,600°C, Now, personnel can visualise operations on a screen and tablet devices in an air-conditioned control room with much reduced footfall on the shop floor.
ABB digital and automated solutions for steel melt shops use standard industry protocols and are therefore easily incorporated with legacy and third-party supplier systems, resulting in more informed decision-making based on information dashboards, improved service planning, and better reaction time to work orders and overall system effectiveness through reports and KPIs.
- Increased caster speeds by ensuring the correct superheat at the caster
- Improved people safety by reducing exposure to hazardous hot metal zones and allowing for decision-making based on information dashboards
- Energy savings and quality improvements by predicting the ladle's thermal loss during transfer and calculating the right temperature to avoid excess overheating
- Improved service planning by tracking the history of ladle maintenance and contact with metal
- Reduced tapping ladle delays for EAFs due to efficient crane scheduling for ladle movement
- Detailed time motion analysis of work orders and overall system effectiveness with reports and KPIs
- Backed by knowledge built up during ABB's more than 100 years in the steel industry
CASE STUDY: JSW STEEL
These benefits and others can be witnessed in India, where ABB has integrated ABB Ability™ Smart Melt Shop into a wider expansion at JSW Steel's Dolvi Works plant in Maharashtra state.
Completed in March 2021, the project has improved productivity and energy efficiency for the steel melt shop using a ladle and crane tracking system, crane scheduling system and thermal loss models to predict target temperature for ladle furnaces and ensure the correct superheat at the caster.
These innovations are expected to increase the company's EBITDA profit by approximately $2 million a year through 4% higher casting speeds, time savings of one working day per month and additional output equating to 24,000t a year.
The Dolvi Works plant now benefits from real time ladle tracking for process synchronization and better maintenance planning. The lower energy consumption means fewer consumables are used per batch and therefore a lower carbon footprint thanks to less CO₂ per tonne of steel produced.
In addition, ABB's automatic tracking and scheduling solution increases the safety of JSW Steel personnel by removing them from the busy production area during crane and ladle movements.
Biographies
Global Product Manager, Metals Digital at ABB
Tarun Mathur graduated from the Indian Institute of Technology, Mumbai, and holds a Master's degree in mathematical modelling and process control. He has held several positions in research and development, focusing on the development of advanced model-based solutions for process industries. He is currently focused on projects applying new digital technologies to optimize steel plant performance, process and quality.
