Maintenance Strategy Planning
Identification of the right predictive analytics approach for critical machineries and components
Preventive?
Preventive maintenance is carried out at predetermined intervals or according to prescribed criteria, that is aimed at reducing the failure risk or performance degradation of the equipment. The maintenance cycles are planned according to the need to take the device out of service. The incidence of operating faults is reduced.
Predictive?
Predictive maintenance is a method that utilizes data analysis tools and techniques to detect anomalies in your operation and possible defects in equipment and processes so it can be fixed them before they result in failure. Ideally, predictive maintenance allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance, without incurring costs associated with doing too much preventive maintenance.
Condition based?
Condition based maintenance based on the equipment performance monitoring and the control of the corrective actions taken as a result. The actual equipment condition is continuously assessed by the on-line detection of significant working device parameters and their automatic comparison with average values and performance.
Condition based maintenance is carried out when certain indicators give the signaling that the equipment is worse, and the failure probability is increasing.
This strategy, in the long term, allows reducing drastically the costs associated with maintenance, thereby minimizing the occurrence of serious faults and optimizing the available economic resources management.
Prescriptive?
Prescriptive maintenance is transforming asset performance management with the premise, why simply predict production issues when you can prescribe fixes for them and act on the prescriptions. Prescriptive maintenance is the asset maintenance strategy that uses machine learning to adjust operating conditions for desired outcomes, as well as intelligently schedule and plan asset maintenance. Prescriptive maintenance looks for failure signatures and also provides information about how to delay or entirely eliminate equipment failure. These algorithms can comb historical data for examples of a wide variety of operating conditions, and also extract patterns and extrapolate data to provide hypothetical operating environments. The cascade of effects and consequences from small adjustments to an industrial process can be simulated by the prescriptive maintenance model, allowing for expensive and risky experimentation to be performed in a computer simulation.