Intelligent supervisory system for availability estimation of automated material handling system

The paper presents the fuzzy logic approach to estimates the operating time of the system's equipments. The self-learning fuzzy model was proposed for prediction of operating time of equipments between the last to the next predicted failure based on monitoring the exploitation state of the considered system. The fuzzy model is developed in the learning process realized by Recursive Least Squares algorithm (RLS). The example of fuzzy estimator of operating time was presented as the programming application type of Human Machine Interface (HMI) tested on the laboratory stand, the overhead traveling crane, and used to monitor the availabilities and failures prediction of the considered device equipments.