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 collect condition data of machine components, combine it with information from third-party systems (e.g. ERP or CRM) and analyze it to predict the optimal maintenance time. Predictive maintenance, or PM for short, enables early detection of impending failures, accelerates processes and avoids production downtimes – SO THE EXPECTATION.
Predictive maintenance is currently the most discussed and questioned maintenance-repair-overhaul strategy. A recent study conducted by the World Economic Forum and the consulting firm Accenture shows that the hopes placed in PMs are not unjustified. 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.