First of all, we need to understand the P-F curve, the P-F range, and predictive technology planning, which is critical in building a predictive maintenance program.
Understanding the P-F curve, as most of us know, is what will help a maintenance or reliability manager sell the need for predictive technologies such as vibration analysis, oil analysis, and so on. This should also be implemented properly by reducing the amount of reactive maintenance being performed on your plant. What the original P-F curve will not do is maximize the benefit of the predictive program without effective application of the tools.
Below is the P-F curve that most people are familiar with.
The x-axis of the curve represents the Time (T) or the Operating Age, and the y-axis represents the resistance to failure. Starting at the top left of the curve and moving to the right, we find the point P, known as Potential Failure. This is the point in time that, when using some predictive tool, can first detect the fault.
As we continue to move along this curve, the resistance to failure continues to fall until we find the point F, known as the Functional Fault. This is the point in time when the resistance of the components to the fault has deteriorated to a point where it can no longer perform the intended function.
The elapsed time between point P and point F is known as the P-F range.
The known value in the P-F range of a component for a specific failure mode is that it will now define the condition-based inspection interval (predictive techniques).
When defining the oil collection interval, we must now, with a high level of confidence, be able to detect the failure of this component, plan a replacement or restoration task, and repair the component before the failure occurs. In doing so, we now replace what was previously a reactive task without proper planning of the range of use of the predictive tool in question.
The introduction of the P-F curve to condition-based monitoring tasks provided a much needed innovative change in a world where Preventive Maintenance was seen as the only option to avoid emergency/demand maintenance. The use of the P-F curve quickly evolved into the maintenance world for a new era of “proactive maintenance” for companies that could afford the new and expensive predictive technologies associated with Predictive Maintenance.
Companies that invested in technologies such as Vibration Analysis, Oil Analysis and other techniques paid large sums for equipment acquisition and training to develop internal Predictive Maintenance teams and shortly after making these investments began to share success stories and savings that could be generated from detected failures and secondary damages associated with emergency maintenance.
Thus, each type of equipment has its oil collection interval based on the study of the P-F curve for the specific equipment and, therefore, the frequencies of analysis are different in the most diverse applications and equipment.
It is worth remembering that when we treat, for example, a semiannual sample and this one has a PF that determines an interval of collection of oil between collections of 250 hours, we are not doing monitoring of the conditions, but a punctual analysis of the conditions of a certain equipment at a given moment, thus leaving a very large GAP of reality, since the trend is not being evaluated and, consequently, we can be close to the F point, which is where it presents the functional failure.
It is therefore essential that the recommended oil collection interval for a given type of equipment is met so that the evolution of some type of wear can be evaluated and the potential failure time can be identified.