Early detection of malfunctions in automated warehouse technology.

Predictive Maintenance is based on extensive analyses of big data and a large number of algorithms. Networked sensors constantly monitor machine and measurement data (e.g. temperature, electrical resistance and vibrations) and collect process data that influences the behavior of the machines. The existing historical data is modeled to provide a sold basis for specific analyses and evaluations of current data. Predictive Maintenance can predict the probability that a malfunction will occur, so that system maintenance can be initiated proactively before actual failures occur.

Getting to the bottom of the causes of error

EPG's Predictive Maintenance solution has been designed specifically for use in the logistics industry and even goes one step further. Logistics companies using the LFS.wms warehouse management system can check whether unusual sensor values correlate with the order data from LFS.wms. This means, for example, that conclusions can be drawn about the cause of raised temperatures. Is the increase due to heavy load on the system or is there a technical impairment that implies an acute need for maintenance? EPG's smart service provides specific answers to these types of questions.

Predictive Maintenance as a cost-saving problem solver

Predictive Maintenance is used in a wide range of applications. The purchase pays for itself very soon, particularly in areas of heavy investment with a high degree of automation. These include shuttle vehicles, lifts or storage and retrieval systems in automated small parts and high-bay warehouses, as well as industrial trucks and conveyor technology.