Nearly every business knows what it‘s like when a machine malfunctions unexpectedly. One reason for this may be that the maintenance schedule has not been properly matched to the machine. Servicing routines are done too early or too late. Cassantec now offers condition-based prognoses that can prevent this kind of downtime problem. The Cassantec Prognostics method can predict the time window in which a fault can occur on a machine or entire installation. A prognostic approach is used to prepare an individual report for the machine or plant in question and this specifies the timing, probability and nature of the malfunction. From this the equipment operator can deduce the point in time when maintenance work will be needed. Cassantec works with the client to identify the most common types of fault that are likely to occur on a specific machine. A damage history is not required. Cassantec can also predict malfunctions that were previously not part of the machine‘s operational history. The company uses a combination of mathematical methods to produce the report. Future status trends, fault risk profiles and remaining lifespan can all be determined in this way. The prognosis is updated at regular intervals with historic and current status data and process information, including temperature, vibration data and lubricant analyses. The analysis results are presented in a decision oriented way so that optimised plans can be drawn up for servicing and maintenance work.
The prognostic tool expands the planning horizon for companies operating in the mining sector. They now have access to a transparent system for determining when maintenance work should be carried out on a particular machine or component. According to Moritz von Plate, CEO of Cassantec AG, ‚Our prognosis report takes normal condition monitoring a step further in that our system also extends the capability of preventive diagnostics. This means that a signal is only given when a time window opens in which malfunctions can occur. Cassantec Prognostics calculates the moment in the future when this time window will open and then close again, and assesses how the risk is spread across the window‘.