Supervisory System for Supporting Decision-Making Process in Proactive Maintenance of Technical Object

The proactive maintenance involves the advances warming of the failure possibility, that can bring the attention of maintenance personnel to impending danger, and realizing preventive and corrective operations. The paper describes the application type of HMI/ SCADA equipped with tools created using soft computing techniques applied to design the fuzzy predictive models of time between failures, and to aid decision-making process of user by collected in database heuristic maintenance strategy. The method of off-line and on-line learning predictive models was based on the genetic algorithm and recursive least squares algorithm. The application of supervisory system was tested on the laboratory stand equipped with the physical model of an overhead travelling crane.