Classic remote maintenance involves the maintenance of spatially remote IT systems, plants, machines or computers. The connection to the computer to be maintained is established by data transmission, which is temporarily released by the user for certain maintenance levels - hardware, software, data files - with special consideration of data protection.
In classic remote maintenance, a distinction is made between offline remote maintenance and online remote maintenance. Predictive maintenance has evolved from the latter. In offline maintenance, the faults that occur are detected and recorded internally by a computing unit or computer and transmitted to the centrally available diagnostic program, which analyzes the faults offline.
In contrast, in online maintenance, the service technician gains access to the machine or computer to be maintained via an online connection. In this case, the user interface of the machine being serviced is displayed on the service technician's screen, and the technician immediately recognizes the effects of the actions he or she has performed.
In addition to the classic approaches, there is also the predictive approach of Predictive Maintenance. Predictive maintenance involves transmitting the measured values of the machines and systems recorded by the sensors to a maintenance center and drawing conclusions about imbalances and vibrations and defined fault types from the recorded noises, speeds and temperatures, and using correlations, comparison models and algorithms to derive the future functional readiness and probable failure of the component - for example, a seal or a bearing. Through the Internet, plants and machines - production facilities, wind turbines, aircraft turbines, printing presses, motor vehicles, oil presses, power plants, solar fields, and many more - can be predictively monitored and maintained worldwide using predictive maintenance. Certain maintenance tasks can be carried out directly from the maintenance center, without the need for service technicians on site. The data transmitted by the measuring stations, sensors and probes is referred to as Smart Data because it is intelligent data with a high information content.
The objective of predictive maintenance is to reduce downtime, because even the shortest downtime can result in enormous costs. Just think of the failure of a power plant, a production facility or a wind turbine. Predictive maintenance technology, which is currently still limited to industrial plants and machines, will soon also find its way into consumer electronics and household appliances via the Internet of Things( IoT). The technology is being used more and more in motor vehicles. Diagnostic data can be transmitted directly to the workshop or the manufacturer.