Our company have a lot of stations fare equipment such as
ticket gate machine. Maintenance and inspection of these
require a lot of labor and cost. In this paper, we aimed to solve
this problem by applying failure detection a form of machine
learning. Currently, the system has been installed in all of our
station equipment, and has reduced the number of failures by
20% and inspections by 30%, helping to optimize our
operations. In the future, we plan to apply this method and
our knowledge of maintenance and operation to evaluate the
health and management of satellites in the space field.
Predictive maintenance, Anomaly detection, Machine learning, Station fare equipment
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