Mike Feinen

Predictive Maintenance and Condition Monitoring for Washing Stations

The train wash station of Luxembourg’s national railroad company (french abbreviation: CFL) cleans local and long-distance trains daily in its 200-meter-long wash hall. So-called energy chains are used so that the wash trolleys can travel on both sides of a train. These energy chains safely guide all hoses and lines for energy, compressed air, water and cleaning agents back and forth. Malfunctions and failures of these chains are extremely costly and lead to interruptions in the operating process or even to plant breakdowns. Train runs have to be postponed or cancelled. In this podcast episode, we talk about how CFL is now applying a solution that overcomes this challenge. Today, energy chains from igus are used together with intelligent sensor technology that monitors the condition of the system and maintains it in a predictive manner. How exactly are these failures prevented? Which components were to blame for the failure? How and with which tools was the whole project approached? And how are things going at the moment? Episode 88 of the IoT Use Case Podcast features these answers directly from CFL Maintenance Manager Mike Feinen. He tells how the team initiated a modernization program and implemented it together with their chosen partner igus – represented here by Richard Habering, Head of Business Unit igus® smart plastics. Smart solutions for condition monitoring and predictive maintenance – extending product runtimes & maintenance costs – a more efficient and environmentally friendly train wash station.