Cold rolling mills play an important part in aluminium production, but with producers increasingly faced with challenges to stay competitive, meet customer demand for increased product quality, and cope with a widening variety of materials, how can they ensure that at the practical level, acceptable thickness and flatness tolerances decrease, while improving throughput and yield?
One response to these business and technical challenges is through greater use of digital technologies, such as advanced data analytics. The idea is simple: if CRM operators were able to observe the status of equipment and processes in near real time, they would gain crucial insight into performance – and particularly into deviations in product quality or problems with the process. This insight would allow operators to actively manage production to better meet the various demands on them.
But achieving this is more easily said than done. Despite the conceptual simplicity of the rolling process, in reality it is a complicated operation that depends on a multitude of factors. To fully exploit the full production potential of the CRM in today’s market therefore requires a connected and integrated approach to automation optimization, control, and decision-support tools.
The good news is that CRMs are often already equipped with modern control systems that include multiple sensors to monitor and record vast amounts of data. And with sampling times in the range of milliseconds, hundreds of sensor values are recorded – more than 3GB worth a day, during mill operation. This includes measurements of flatness, tension, speed, and strip thickness.
This data is routinely exploited by service engineers for commissioning and maintenance of rolling mill devices. But this valuable resource is rarely analyzed for performance purposes due to the difficulties of manual analysis and data pattern screening – a tedious and costly endeavour by any measure.
A lost opportunity?
To help CRM operators and maintenance engineers release the potential of their raw data and efficiently analyze the performance of their systems, a technology partner is required with deep domain knowledge and the ability to draw on the latest advances in neural networks and advanced data analytics applications for operational data. This combination of practical and digital expertise helps to create a digital service solution that addresses real-world challenges.
Digital Solutions for Industrial Processes (SODA) from ABB aims to do just that. Key concepts from SODA have now been integrated into the ABB Ability™ Data Analytics for cold rolling mills solution, which forms the basis for the new-released ABB Ability™ Performance Optimization Service for cold rolling mills. Notably, this includes the ability to detect and monitor problem signatures, as well as undertake basic root cause analysis of the issue. In this way, this new digital tool provides operators with the data they need to keep track of the status of their CRM, while assessing productivity and product quality.
It does this by quickly guiding users to the relevant information and providing interactive diagrams and plots. Engineers area therefore easily able to focus on the information they need to make smarter and speedier decisions.