New sensor for data collection on cranes Montarent
Noah le Roy third year Technical Business Administration at the Hogeschool van Amsterdam developed a sensor for on cranes of Techport company Montarent for his internship. This sensor independently collects data making it possible for the company to predict the maintenance of the cranes.
Montarent is a specialist in mobile tower cranes and glass robots. They would like to do predictive maintenance, but for the company it is a challenge to get the right data from the cranes. This is why they put out an internship assignment through Techport and ended up asking Noah to look at how they can do predictive maintenance through data. Noah: "If you know how a trend is going normally, then you can also tell when something is not going normally. You can tell from data when something deviates from a certain pattern, think about vibrations, heat development or change in energy consumption. A change in a pattern often means the beginning of failure. It will still work, but it will break down at some point. With maintenance, you can prevent this vaa possible."
Noah arrived at a Proof of Concept for Montarent: "We first identified the exact problem and looked at what exactly do we want to detect. We did this based on the data from the crane's onboard computer and the ERP system that contains all the maintenance performed in recent years. We could see that an anomaly recurs more often. However, we needed slightly different data to map the deviation properly. So I built a sensor that can collect data independently. The sensor has been on the crane, but not for a long time yet. The batteries now last for 5 days but we actually want to go to a month. That's what Montarent is going to work on. Maybe we will do this through solar panels. My internship is almost finished now, but I will continue at Montarent for a while. After all, I've now implemented one way of detection and want to try another way as well."