In the early 1990s, the continuous casting plant at Iscor’s Pretoria Works faced a serious operational problem: sticker breakouts.

A breakout in a continuous caster is not merely a production interruption. It involves molten steel escaping from the partially solidified strand, with the potential for extensive equipment damage, prolonged production downtime and significant risk to personnel.

By 1993, the Pretoria Works caster was experiencing approximately two to three sticker breakouts per month. Rather than purchase a proprietary commercial detection system, a small multidisciplinary engineering team set out to understand the phenomenon and develop an in-house solution.

The result was a continuous caster breakout detector combining mould temperature measurement, supervisory control, mathematical modelling and an expert-system decision engine.

It became an early example of what would now be described as industrial condition monitoring combined with real-time predictive control.

What Is a Sticker Breakout?

During continuous casting, molten steel at approximately 1540 °C is poured into a water-cooled copper mould.

As the steel contacts the mould walls, its outer surface begins to solidify. A solid shell therefore develops around a still-molten core while the strand is continuously withdrawn from the mould at approximately 1 metre per minute.

Under normal operating conditions, mould powder provides lubrication between the solidifying strand and the copper mould.

If lubrication becomes inadequate, friction may increase sufficiently for part of the solidifying steel shell to stick to the mould wall near the meniscus.

The strand, however, continues moving downwards.

The result is a tear in the newly formed shell.

Because this occurs beneath the surface of the molten steel, the operator cannot see it. As withdrawal continues, the tear propagates downward through the mould. Unless the shell can heal before reaching the mould exit, molten steel escapes from the strand.

This is the sticker breakout.

The consequences can include damage to the mould and downstream segments, lost steel, substantial repair effort and several hours of production downtime.

The Engineering Problem

At the time, Pretoria Works had no practical means of predicting or detecting a developing sticker breakout.

Commercial detection systems were available, but their installed cost was estimated at between R2 million and R3 million. They also presented another engineering disadvantage: their proprietary nature made them difficult to understand, modify and optimise for local casting conditions.

For the project team, this presented an opportunity.

Could the plant develop a system internally that was:

• effective at detecting developing sticker breakouts;
• fast enough to allow corrective action;
• inexpensive compared with proprietary alternatives;
• based on standard, maintainable hardware;
• understandable by plant engineering and maintenance personnel;
• adaptable to the particular behaviour of the Pretoria caster; and
• capable of improving the plant’s understanding of the continuous casting process itself?

A preliminary investigation was therefore approved.

The ultimate objective was ambitious: reduce the breakout frequency to less than one per year.

Detecting a Breakout Through Temperature

The key to detecting a sticker breakout lies in understanding what happens thermally when the steel shell sticks to the mould.

Thermocouples installed in the mould allow the temperature distribution across its faces to be monitored continuously.

A developing sticker produces a characteristic change in this temperature pattern.

Rather than relying on a single temperature limit, the project sought to identify the spatial and temporal temperature behaviour associated with a developing tear.

This required much more than installing instrumentation.

Temperature histories had to be gathered during actual casting operations, archived and compared with plant events. Literature describing the theoretical breakout mechanism was then compared with what was actually observed on the caster.

Over time, recognisable patterns emerged.

The engineering challenge was then to convert those patterns into mathematical rules capable of distinguishing a genuine developing sticker from the many normal temperature variations occurring during casting.

From Plant Data to an Expert System

Development proceeded along two parallel paths.

The first concentrated on refining the physical measurement system.

The second concentrated on developing a software decision-support system capable of evaluating the measured temperatures and determining whether a sticker breakout was developing.

The system ultimately combined:

• mould-mounted thermocouples;
• signal acquisition hardware;
• personal computers communicating over a NetBIOS network;
• commercial supervisory control and data acquisition software;
• a proprietary decision-support application written in C++;
• mathematical breakout-prediction algorithms;
• operator displays; and
• integration with the plant programmable logic controller.

For the early 1990s, this was an unusually distributed and software-intensive industrial control application.

Importantly, most of the system was constructed from commercially available, off-the-shelf components.

Only the specialised temperature-sensing arrangement and the breakout decision software were proprietary developments.

This deliberately avoided the “black box” problem associated with proprietary commercial systems. Plant engineers could understand how the system worked, maintenance personnel could replace standard components, and the detection parameters could be modified if operating conditions changed.

Engineering Was Only Part of the Project

A technically correct detector would have achieved little without the cooperation of the people operating and maintaining the caster.

The core project team consisted of three people:

Alf Jansen van Rensburg — project leader, Process Control
Nico Davies — hardware, supervisory control and data acquisition
Christelle du Raan — development of the expert-system decision logic

However, the effective project team was considerably larger.

Maintenance personnel modified the mould, installed instrumentation and supported thermocouple replacement.

Production personnel contributed their operating experience.

This proved particularly important.

Operators had accumulated considerable practical knowledge concerning mould lubrication, casting behaviour, mould powder and abnormal operating conditions. Their anecdotal observations helped the engineering team interpret temperature behaviour that could not be understood from theory alone.

The development process therefore became a combination of:

theoretical knowledge + measured plant data + operator experience

That combination was fundamental to the performance of the finished system.

Human-Machine Interface Design

The operators were also actively involved in determining how information should be presented.

Different representations of mould temperature behaviour were evaluated, with operating personnel identifying those that best matched their understanding of the casting process.

Control-room operators, shift personnel and engineers were trained to interpret the system.

Mould operators were trained in the actions required following a breakout warning.

Initially, the principal response was to reduce strand withdrawal speed, providing additional time for the torn shell to heal.

As confidence in the detector increased and false alarms became sufficiently rare, the system progressed from decision support to automatic intervention.

When a sticker was detected, the casting machine could be stopped automatically through the plant PLC, although the operator retained a short opportunity to override the automatic action.

This represented an important transition.

The system was no longer simply monitoring the process.

It had become part of the process control strategy.

Measuring the Results

The operational results were substantial.

Before installation of the detector, the Pretoria Works continuous caster averaged approximately:

2 sticker breakouts per month

Immediately following commissioning, this reduced to approximately:

1 breakout every 2 months

The breakout frequency had therefore fallen to approximately one quarter of its previous level.

The project report calculated the average cost of a breakout at R359,379, including production downtime, labour, equipment damage and lost steel.

Development of the complete system, including engineering labour and purchased equipment, was calculated at approximately:

R1.025 million

The cost of the system was consequently recovered through approximately the first three prevented breakouts.

Those prevented breakouts occurred within approximately the first two months of operation.

The annual saving resulting from reducing the breakout rate from two per month to 0.5 per month was conservatively calculated at approximately:

R6.47 million per year

The corresponding increase in steel slab production was calculated at approximately:

7,752 tonnes per year.

At the target production rate of 45,000 tonnes per month, the project was estimated to reduce the variable production cost of steel slab by approximately 1.92%.
All monetary values quoted above are historical South African rand values from the original 1996 project report and should not be interpreted as present-day values.

Benefits Beyond Production

The financial return was significant, but the system produced several other benefits.

Improved Safety

A breakout releases molten steel into the caster structure.

Preventing the event therefore reduced the exposure of production and maintenance personnel to both the breakout itself and the difficult cleanup and repair activities that followed.

Reduced Maintenance Work

Preventing damage to the mould and caster segments reduced emergency maintenance work.

Workshop capacity previously consumed repairing breakout damage could instead be directed towards preventive maintenance and other productive work.

Improved Process Information

The temperature monitoring system gave production personnel far greater visibility into conditions within the mould.

Among other things, the temperature distributions could provide information regarding the effectiveness of mould lubrication.

This allowed operating personnel to respond to inadequate lubrication before it developed into a more serious condition.

Improved Slab Quality

Better mould lubrication does not merely reduce the probability of sticking.

It also contributes to improved slab surface quality.

The breakout detector therefore became useful not only as a protective system, but also as a process diagnostic instrument.

Knowledge Retention

Because the system was internally developed and deliberately constructed from understandable components, the knowledge remained within the organisation.

Detailed documentation and training material were developed for production, maintenance and engineering personnel.

The system therefore became part of the plant’s accumulated technical knowledge rather than remaining a proprietary technology understood only by an external supplier.

Designing for Maintainability

Maintainability was an explicit design objective from the beginning.

The thermocouples were standard commercial components.

The computer and data-acquisition hardware consisted largely of standard products.

Detection parameters were accessible through the expert-system interface, subject to password protection.

The C++ source code was retained so that future engineers could modify the application if required.

This approach proved successful.

The completed breakout detector was sufficiently stable that its maintenance burden was extremely small, apart from occasional replacement of mould thermocouples.

That design philosophy remains relevant today.

Industrial systems often remain in service far longer than the computers, software packages and communications technologies originally used to construct them.

A system built around open interfaces, understandable logic and replaceable components has a much better chance of remaining supportable throughout its operational life.

Lessons From the Project

Looking back three decades later, several aspects of the project remain particularly relevant to modern industrial automation.

1. Understand the Process Before Automating It

The project did not begin with software.

It began by understanding the physical mechanism that produced the failure.

Only once the thermal behaviour of a developing sticker was understood could meaningful detection logic be developed.

2. Plant Data Must Be Interpreted in Context

Raw temperature data was not enough.

The theoretical models had to be reconciled with actual plant behaviour.

Production knowledge was essential to explaining deviations from theory.

3. Operators Are Part of the Control System

The people operating the caster were not treated merely as end users.

Their knowledge influenced the detection model, the interface and the operating response.

That involvement was important in establishing confidence in the system.

4. Transparency Has Engineering Value

The decision to avoid a proprietary black-box solution provided benefits extending well beyond initial capital cost.

It allowed the plant to understand the technology, modify it and use it as a platform for further process investigation.

5. Automation Should Be Introduced According to Confidence

The system initially provided warnings and operator guidance.

Only after sufficient operating experience demonstrated reliable detection and a sufficiently low false-alarm rate was automatic machine intervention introduced.

This remains a sound philosophy for implementing predictive control systems.

6. The Greatest Value May Be the Knowledge Created

The detector prevented costly failures, but it also created a new capability.

Continuous mould temperature measurement provided metallurgical and process engineers with a platform for studying the influence of casting speed, mould oscillation, mould taper, mould powder, superheat and other parameters on caster behaviour.

The project therefore evolved from solving one operational problem into providing a broader process-development tool.

From Expert Systems to Modern Predictive Analytics

The terminology used today would be different.

A similar project might now be described using terms such as:

• edge computing;
• predictive analytics;
• anomaly detection;
• multivariable condition monitoring;
• machine learning;
• digital twins; or
• industrial artificial intelligence.

But the fundamental engineering problem has not changed.

Measurements must reliably represent the physical process.

The failure mechanism must be understood.

The distinction between normal process variation and an incipient failure must be identified.

The detection system must respond quickly enough to matter.

And operators must trust the result.

The Continuous Caster Breakout Detector developed at Pretoria Works achieved these objectives using the technology available in 1993–1994.

Perhaps the most important lesson from the project is therefore not about any particular technology.

It is that deep process understanding, good instrumentation, disciplined analysis and close cooperation between engineering, operations and maintenance can solve problems that initially appear to require expensive proprietary solutions.

That principle remains as valid today as it was thirty years ago.

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