Proactive maintenance is effective to keep the normal operation of equipments and mechanical systems and so on. Early detection of anomalies followed by malfunction of the equipments and systems is essential for working order. This paper proposes a prognosis system that includes two functions. One is remote monitoring which detects anomalies by comparing sensor data with a threshold data, and another is data-mining which detects anomalies using statistical analysis. We have developed the prognosis system and have confirmed the effectiveness of preventing machine-trips.
