The challenge concerned “special urban transport systems such as the 3S gondola lift (editor’s note: a tricable gondola lift with two suspension ropes and one hauling rope) from Bolzano to Soprabolzano, in operation all year round for up to 18 hours per day and subject to extreme temperature fluctuations and weather conditions. Given that running time in one year is equivalent to that of a winter sports facility over five years, it is absolutely vital to avoid breakdowns,” explains Christian Scartezzini, COO of Peoplemover Service (a LEITNER AG subsidiary) and the man responsible for the digital project at LEITNER. Maintenance times need to be reduced to a few hours, and only night maintenance is generally possible, making predictive maintenance an important topic especially with regard to these systems. “Through our digital solutions, we are helping customers to minimise standstill, improve reliability and plan ahead,” says Dennis Klamer, Head of Digital Services at Klüber Lubrication, summing up the advantages of digital predictive maintenance. In the process, sensors are used to measure and analyse the condition of the oil. IoT gateways forward this data for central evaluation to a secure cloud, enabling oil changes to be performed as required. There is no need for monitoring or refills at defined intervals.