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.