IIoT-driven predictive maintenance
Bucket wheel excavators (BWEs) need robust and reliable braking systems to withstand the harsh operating and environmental conditions they are exposed to.
The right solution helps them handle power cuts while protecting the BWE’s components from shock loads.
By offering an innovative braking control setup that features Cloud computing and data analytics, Svendborg Brakes supported a premier lignite mining company in Bílina, Czech Republic, to slashing maintenance costs and downtime.
The Bílina mine, also known as Doly Bílina, is located in the North Bohemian brown coal (or lignite) basin, which covers an area of 1,400 km2 and is the largest in the region.
To extract over 9 million tonnes (9.9 million tons) of brown coal annually, mining companies leverage powerful BWEs, including the 5,700-tonne (6’300-ton) K 2000 model.
To operate close to its theoretical output of 5’500 m3 per hour at all times, the mammoth K 2000 BWE relies on nine travel drives that move the entire machine. These components use Svendborg Brakes’ two-stage hydraulic power units (HPUs) and BSFI 200 spring-applied, hydraulically-released brake calipers.
The current setup had been in place for 15 years, operating at peak performance. While the mining company was satisfied with the solution, it was interested in implementing new technologies that could further improve its operations.
The gateway to Mining 4.0
The latest advances in artificial intelligence (AI), Big Data analytics and sensor technology have been enhancing productivity and equipment lifespan by offering accurate and precise predictive maintenance and diagnostic tools. Therefore, Svendborg Brakes suggested its latest Industrial Internet of Things (IIoT) solution to minimise downtime and reduce the costs associated with scheduled and emergency maintenance.
The mining company, intrigued by these potential benefits, agreed to upgrade all nine braking systems in the K 2000 travel drives.
The new HPs collect sensor data on a variety of parameters such as system pressure, brake pad wear, position of the brake and its piston, brake fluid levels and temperature, and send them to the Cloud. There, advanced AI-driven data analytics is used to extract meaningful information on the status of the brakes and their components as well as to provide crucial predictions on expected equipment failure.
The results are accessible remotely, from anywhere, via Svendborg Brakes’ conditioning monitoring platform. As a result, operators have a clear and comprehensive real-time overview which allows them to identify anomalies as well as finding the sweet spot to conduct scheduled maintenance activities.
In particular, regular inspections can be halved, resulting in substantial decreases in downtime and maintenance costs, without affecting equipment’s service life. In fact, the responsive condition monitoring helps to extend the lifespan of key components.
Even more, as these activities require travelling to Bílina mine’s remote areas, the mining business could lower its visits to the site as well as maximise uptime in the event of equipment failure.
Just the beginning
The innovative IIoT solution installed for the K 2000 BWE has been running smoothly and successfully for over six months. Pleased with the results, the mining company has decided to install the system on every new installation from Svendborg Brakes.
Jan Mikyska, Brake System Control Specialist at Svendborg Brakes, comments: “The best outcome from this project has certainly been receiving an extremely positive feedback from one of our most loyal customers. This attests how Svendborg Brakes’ IIoT solution is a gamechanger in condition monitoring of brake systems, particularly for machines operating in harsh environments or in remote locations. We believe that solutions like this will soon become a standard and, in effect, we are receiving several businesses are inquiring about our system for their applications.”
