Repairing components only after an incident has occurred – that was yesterday. Today, sensor technology and intelligent data analysis enable predictive maintenance of production machines. Thanks to the digital networking and communication of machines, workpieces and components in the Industry 4.0 environment, operators of machines and plants can continuously record status data of machine components, combine it with information from third-party systems (e.g. ERP or CRM) and analyze it to predict the optimal time for maintenance. Predictive maintenance, or PM for short, enables imminent failures to be detected early, processes to be accelerated and production downtimes to be avoided – SO THE EXPECTATION.
Predictive maintenance is currently the most discussed and questioned maintenance-repair-overhaul strategy. A recent study by the World Economic Forum and the consulting firm Accenture shows that the hopes placed in PM are not unjustified: According to the study, savings on planned repairs amount to twelve percent. Maintenance costs fall by almost 30 percent. According to the study, unplanned downtimes are reduced by 70 percent. Predictive maintenance is an important component in an Industry 4.0 environment.
Predictive maintenance is seen as a further development of previous classic maintenance strategies. Here, machine data is continuously collected, processed and analyzed in order to provide operators with concrete information about the condition of the component, system or machine. Plant operators benefit greatly from predictive maintenance. By reducing or eliminating unforeseen downtimes and associated production bottlenecks, productivity increases. Maintenance and service costs are reduced, production quality and planning reliability increase.