Predictive maintenance for robots can be found in the Automation, Industry and Factory 4.0 and Artificial Intelligence categories. The term describes the predictive maintenance of robots using modern technologies. Sensors and smart algorithms are used to continuously monitor the condition and performance of a robot.
The aim of predictive maintenance for robots is to recognise and prevent failures and unplanned downtimes at an early stage. Instead of maintaining robots according to a fixed schedule or only repairing them when they are already broken, companies continuously analyse the data from their machines. This allows them to recognise typical signs of wear in good time and intervene in a targeted manner.
A simple example: In an automated car production facility, sensors on a welding robot constantly measure temperature, vibration and power consumption. As soon as values change, the system signals that certain parts should be serviced or replaced. This keeps production running smoothly, avoiding expensive emergency repairs and long downtimes.
Predictive maintenance for robots thus improves efficiency, reduces costs and makes production more predictable and safer overall.
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