Although the Predictive Maintenance technologies themselves can get quite complicated, the basic concept of PdM is simple enough: Most industrial equipment does not suddenly break down and stop working. The truth is equipment breaks down gradually – over a period of weeks or months. Furthermore, it gives off numerous warning signals along the way. These early warning signs – for instance, slight changes in temperature, vibration or sound – can be detected by PdM technologies. As a result, PdM gives you time to plan, schedule and make repairs – before the equipment fails.
The following graph illustrates this concept:
It’s important to note that maintenance costs are an outcome of focusing on increasing asset reliability. Your initiative to measure, manage, and improve the health of your assets will the base of improving asset reliability.
With regard to the often utilized P-F Curve (above), most “maintenance initiatives” focus on Point F and try to “manage the event’. When your focus is on asset health, your focus is on Point P – “early identification and elimination of the defect”. So, as soon as an inspection (though either a PM or condition monitoring) can identify that a defect is present (Point P – “Early Signal”), that asset is RED (unhealthy)!
This early identification of the defect can enable the proactive workflow model (above). This is in marked contrast to merely utilizing the technologies to optimize a run to failure maintenance strategy. If you have an optimized PM/condition monitoring process that is failure mode driven, that process (including inspections and follow-up work) drives 75-85% of your workflow. If you plan and schedule your work, execute the work with precision, and have a continuous improvement process – you will be a pace setter.
Many companies begin a Predictive Maintenance program by first choosing one of the most common technologies – like vibration analysis. After they get some basic training and experiment for awhile, they start applying the technology to their most critical equipment.
Makes sense, right? Wrong. Let’s go back to the basic concept of predictive maintenance. Almost all equipment gives off early warning signals – such as changes in temperature, vibration or sound – before it fails. These warning signals, or failure modes, can be detected with certain condition monitoring technologies.
The problem is that one or two technologies alone can’t detect the majority of the warning signals in your plant. As a result, a single-technology PdM program will miss far more faults than it catches.
So the key to a successful PdM program is to make sure it is highly sensitive to the failure modes of your equipment. That’s why you need to apply multiple technologies, so you can detect the majority of failure modes in your plant. Consider for example the table below comparing PdM technologies for an AC induction motor.
Ultimately, it’s your equipment’s failure modes and criticality that determine which technologies you apply. Not the other way around. The concept is simple. But you’d be surprised how many companies get this backwards.
Also, a multi-technology approach lets you double-check and confirm “fault findings” between technologies. Plus, it allows you to catch problems with one technology that might be missed by another. But the biggest reason to apply multiple technologies is this: There is little, if any, payback from using just one or two PdM technologies. You will miss most of the early warning signals that occur, so the equipment will fail anyway.
The payback comes from integrating a full range of technologies across a high percentage of your asset base. That’s why the fundamental starting point for a PdM program is: Understanding all the failure modes in your plant, and applying the technologies that will detect them.