Condition-based monitoring (CbM) or sometimes referred to as condition monitoring is the process of monitoring a parameter of condition in machinery/equipment/asset (vibration, temperature etc.), in order to identify a significant change which is indicative of a developing fault.
Predictive maintenance uses condition monitoring asset health data and transforms it into actionable insights using machine learning algorithms and artificial intelligence that determine the condition of in-service equipment in order to estimate when maintenance should be performed to eliminate unplanned downtime, reduce maintenance costs and improve manufacturing quality. Predictive maintenance reduces cost over routine or time-based preventive maintenance, because maintenance tasks are performed only when required, increasing uptime and improving productivity/throughput.
Condition-based monitoring (CbM) or sometimes referred to as condition monitoring is the process of monitoring a parameter of condition in machinery/equipment/asset (vibration, temperature etc.), in order to identify a significant change which is indicative of a developing fault.
Predictive maintenance uses condition monitoring asset health data and transforms it into actionable insights using machine learning algorithms and artificial intelligence that determine the condition of in-service equipment in order to estimate when maintenance should be performed to eliminate unplanned downtime, reduce maintenance costs and improve manufacturing quality. Predictive maintenance reduces cost over routine or time-based preventive maintenance, because maintenance tasks are performed only when required, increasing uptime and improving productivity/throughput.
