Today, maintenance and repair has become very important in the manufacturing industry. Maintenance and repairs affect the service life of the equipment as well as their efficiency. An efficient solution to prevent downtime is to predict equipment failure. Therefore, accurate and correct prediction of breakdown events in the field of predictive maintenance can be very useful. In general, each prediction will be accompanied by a certain amount of error, which in various ways tries to control this error or limit it to a reasonable amount. Therefore, one of the topics in recent studies, especially in predictive maintenance, is the discussion of improving forecast accuracy. In this thesis, a framework has been proposed that specifies when the system under review will need maintenance and repairs to prevent downtime as much as possible
