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Malfunctions of machines, time-consuming maintenance and related production inefficiency pose major challenges to companies, making it all the more important that these production processes are able to function quickly, precisely, and undisturbed.
With the help of Predictive Maintenance, you are able to increase the availability and productivity of your equipment and systems and protect yourself from unnecessary costs for operation, maintenance, and repair. Based on experience rules, statistical methods or smart algorithms, failures or wear can be predicted, maintenance can be planned with pinpoint accuracy and processes can be automated.
The IoT solution developed for Feintool makes it possible to evaluate the causes of downtime based on machine operating data and make predictions for necessary maintenance. This allows for significant reductions in maintenance and service technician inspections. Defects can be addressed before the machine breaks down.
Device Insight has implemented an algorithm for robot manufacturer KUKA that predicts when the next maintenance is due for a specific robot type. Maintenance costs and downtime can therefore be reduced by up to 50 percent.
