The PF Curve is limited due to the lack of a Y2 axis.
Take a moment and Google search PF Curves. You will find images of a positive Y-intercept curve with a negative slope that becomes more acute the further you move along the x-axis. Scrutinizing the endless examples and you will find a variety of different descriptions for the y-axis. You will find phrases like asset condition, resistance to failure, or equipment performance. These different descriptors of the y-axis are intended to describe the likelihood of failure and foreshadow the reliability to perform an intended function as it relates to time on the x-axis. If you dissect the images more thoroughly, you may see examples of another curve that sits on top of the PF Curve and is typically referenced as a cost to repair. The idea here is that as a point on the PF Curve moves further to the right, the cost to repair has a direct correlation and tends to grow exponentially. If you sift through the examples even more, you may even come across the rarest of images that show these two lines crossing. At this moment you would celebrate because would think that is the how-to book showing a magic method to connect asset strategies to life-cycle cost. There is one problem, there isn’t a y2-axis that shows the cost. What the hell? How are we supposed to train others on the PF Curve if there is no correlation to the cost?
PF Curves are the messaging imagery that asset management leaders and reliability engineers use to show the advantages of proactive versus reactive strategies on assets. Using this classic academic curve, they may strive to convince a non-believer of the value of proper asset management. They may strive to articulate a story that the value of proper asset management is realized in the future by enabling a strategy of profit protection. They may catch themselves struggling to align the message that applying the right cost now proactively rather than reactively will unlock future cost savings and reliability. You may even hear an attempt to connect the value of proactive initiatives to better sleep at night knowing that there is a low probability there is going to be a brand-damaging event from an unexpected failure. But again, it didn’t land. We still have non-believers.
The eventual failure of any equipment is inevitable. Wear and tear naturally occur with continual usage. In the same way your pair of shoes eventually get worn out after 500 miles of walking, your key plant equipment (e.g. pumps, motor bearings) will ultimately reach its functional failure point. - UpKeep.com
Within these aesthetic examples of doing the proper asset management, the story is typically non-convincing with this limited imagery because it fails to tangibly connect the PF Curve with a cost. Instead, the presenter of the PF Curve is assuming that they will land their correlation reliability and cost with just a y1-axis. Because of this, the receiver will fail to holistically connect what the cost is along the PF Curve. Instead, you will catch yourself asking them to believe you by the end. So how can we build and land this story effectively?
To articulate this message, the challenge is to approach the PF Curve being represented on the y1 and cost on the y2 axis. Start with calling your y1-axis resistance to failure. I tend to embrace this descriptor because it connects that the P (potential failure) in the PF Curve will be infant mortality and random failures failure modes the majority of the time. As you train your PF message, slowly run your finger along the line by describing the proactive work that you are doing or you are wanting to do with new AI sensors, meter-based preventive maintenance, or improved training to monitor a condition with the latest gadget. Within this proactive zone, you are messaging that cost is indeed occurring but is insurance that maintains a strong resistance to failure. You are messaging that this cost intends to increase the length of the x-axis and delay the timing of the curve starting to exponentially decrease in slope. But the rebuttal you may hear is what is the cost? Bam! We have landed the first phase.
From here, transition into your y2-axis and how it references the overlay of a cost-to-repair curve. This is a tricky transitional step in your training and has the potential for undesired tangents. Articulate your story that you cannot create a y2-axis for an entire production unit because that is where macro metrics of Maintenance Spend per RAV (replacement asset value) or the criticality of an accurate asset hierarchy. Save this training for later. Also, strive to avoid the rabbit hole that tries to group a collection of like assets (e.g. all of your motors, all gearboxes). Instead, campaign your training message on finite examples, like a singular gearbox or motor, that they can tangibly picture, touch, and understand.
Within your storyline, transition your messaging into a hypothetical intersection of the total cost to maintain and the PF-Curve over time. With your finite example, explore your proactive work’s cost of current predictive and preventive maintenance activities. Consider landing a correlation of the length of the x-axis if these proactive initiatives were to stop. Transition these strategies into the cost of your condition-based maintenance as it relates to the ability to create and complete follow-up work. Keep going back and forth to the curves stressing the proactive zone and the inevitable end of the PF Curve that indicates the asset’s failure. But if you are strategic and provoke strong asset management strategies, you will maintain the asset to the left of the intersection the majority of the time. This approach will land that we must strive to find an accepted risk within the resistance of failure at the optimum cost. You now have just trained the PF Curve and related it to cost. Well done.
A goal that we all must have in the manufacturing space under a sustainability umbrella is to delay an asset’s failure at an optimum cost. This doesn’t mean that we run all assets to failure, nor does it mean we must PM everything. Instead, we must strive to fiscally increase the x-axis and delay the intersection. To achieve this, the approach we take in training is critical for it to land.