MCA meets Dustin Schiller and Simon Hausknecht, CEOs of SHG Conveyor Control of Germany, the developers of the AI-based Rip Prevent+ conveyor monitoring system now available in South Africa from Tru-Trac Rollers.
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Simon Hausknecht (left) and Dustin Schiller (right), developers of the AI-based Rip Prevent+ conveyor monitoring system.
SHG Conveyor Control was started about 18 months ago by Dustin Schiller, a mechanical engineer with experience working in the conveying industry at Continental, and Simon Hausknecht, an electrical engineer. “We came up with an idea to find a way to monitor the health of a conveyor without having to use sensitive sensor elements inside belts or remotely mounted across the length of a conveyor,” begins Schiller.
They began by looking into rip detection events: “We contacted conveyor belt users and asked them to share the historical data they had collected from their systems, particularly for periods that included rip events. We then set out to use AI to analyse this data, collected from traditional condition monitoring systems, to see if we could see any early prediction signals for the rip events that had occurred,” he tells MCA.
That was our starting point for the development – and it was very successful.
Traditional conveyor belt monitoring involves embedding wire loops into the belt that create eddy currents. It is only when the loops get broken that the rip is detected, which often means that the rip has already happened. So it is not usually a prevention system, it can only detect the rip after the event. “Our system is completely new, because it does not include any external sensor elements on the belt and we set out to find the root cause of the rip and to stop the belt before the rip occurs,” he continues.
“So we did some reverse engineering on a rip event in the loading area of a belt and we quickly found a ‘signature’ pattern in the data that was uniquely linked to the start of that event,” Dustin Schiller tells MCA, adding that this signal was not linked to any of the installed sensors on the system.
“We have developed the Rip Prevent+ system based mostly on analysing the electrical and performance characteristics of the drive pulley motor: the speed, the voltage, the amps, and the ambient temperature, amongst many others. All of this can be done by adding a small and inexpensive data monitoring unit near the motor controller,” he adds.
SHG has developed software that enables the system to be ‘tuned’ to the specific parameters of each conveyor system: its drum diameter, maximum power, torque and belt length, for example. “We are continuously monitoring a lot of data, mostly the electrical parameters. The mix of the data starting from the voltage, amps, Total Harmonic Distortion (THD), Cos Phi and other collected data gives us a specific signature. Other data such as associated the K-factor, the real, apparent and reactive power, and so on and so forth is also collected and analysed,” continues Simon Hausknecht. “Continuously running in the background is an AI-based algorithm that is looking for specific patterns. When a rock is stuck in the loading area, for example the algorithm gives us signal that we now know is associated with the beginning of a rip event. This signal was present 24-hours before a rip occurred at a customer in Germany called RPBL. The customer ignored this signal, and they didn't check the conveyor lights. 24 hours later, the belt ripped and the Rip Prevent+ System stopped the conveyor that then had a rip length of just 12 m,” he relates.
In another case during the development phase, according to Schiller, a rock was stuck in the chute of the loading area. “In that case the specific patterns was visible in the data four hours before a problem was noticed. But if the customer is not checking the system for ‘unhealthy’ warnings, then the belt will rip. Now, with our system properly integrated into the belt drive, we are able to automatically stop the conveyor line within 0.2 seconds of detecting a blockage, thus preventing the occurrence or a rip and significantly reducing the associated downtime,” he explains.
Simon Hausknecht cites a success story for this system on a mine in Australia. “Northern Star Resources is a huge gold mine with five Rip Prevent+ Systems running. 24 hours after having installed Rip Prevent+ on these conveyors, we picked up an event and it stopped the belt immediately.
The belt was stopped before any major damage was done and the problem was immediately resolved. The value of the system was proven by that one incident and this mine is now a very happy customer,” he relates. In terms of costs, traditional belt monitoring technologies rely on a steel-cored belt, which need a bottom cover of at least
6.0 mm to cover the inductive loop of the belt. This makes the solution very much more expensive. “Our system is suitable for any belt, corded, uncorded or fabric corded, and we only charge for the license and a small amount for the hardware and commissioning,” he adds.
Related benefits
“While we have started with rip prevention, we are open minded and very excited by a host of other opportunities that the system offers. If a customer has a monitoring need, we invite them to come to us. We will look at the requirements and develop a solutions free of charge, because we believe that, if one site has a problem then that solution will also be useful at other facilities all over the world,” suggests Schiller.
“We know for example, that we can use our current system, without modification, to track energy consumptions, the motor condition, the energy efficiency, and the tonnage per hour. We have dashboards for energy efficiency, costs per ton, unproductive uptime, and we can measure tonnage across the belt in most cases, to within 2.5% of a belt scale,” he says, adding that in a gravel pit in Austria where the system is operating, SHG is achieving a deviation of just 0.5% compared to the calibrated belt weighing scale.
“We are also using the system to check the external electrical network, because poor quality power from the grid can result in drastic problems for electrical motors – high THD values, for example increased the fire risks for electrical components, and PLCs can be shut down due to these disturbances,” he says. SHG plans to develop the system more and more, with gearbox monitoring already under development, for example. “We want to bring everything together to help customers identify root-cause incidents in all of their critical plant equipment, because analysing data 24/7 at high speed can result in huge customer benefits in terms of incident prevention and uptime,” adds Hausknecht.
In another contrast to the modern trend, he says that SHG’s AI-based monitoring system is an offline system that does not depend on The Cloud or an Internet connection. “We believe Cloud-based monitoring is the wrong approach for machine level intervention. IT Security is the most important part and therefore it is necessary to stay offline on the machinery level.
“SHG currently has more than 120 Rip Prevent+ systems in operation, and boasts a 100% rip event prevention record, having already detected and prevented 10 belts from ripping on the sites it is servicing.
“The Rip Prevent+ system is available to customers across Africa from Tru-Trac, and significantly, there are no upfront capital costs,” Schiller says. “Through Tru-Trac, we offer a customised easy and very rapid service, with a very modest service charge that is easily justified by improved conveyor belt reliability and uptime.”
“Over the past three decades, Tru-Trac has built a formidable reputation, extending its footprint and sales across Africa and worldwide, and the addition of the Rip Prevent+ system will be a gamechanger in the market,” concludes Jonathan Rogoff, CEO of Tru-Trac.
