WHAT CAN BE LEARNED FROM THE NUMBER?
This is the point where most asset management processes go wrong. Many models in use today will set a criticality ranking based solely on the scoring range. For example, an asset which scores between 75 and 100 may be considered “critical”, while an asset that scores less than 25 may be “expendable”. This practice undermines the entire concept of criticality analysis. The organization might as well give each asset a number from 1 to 5 and call all things equal. This grouping of scores provides no meaningful data for establishing or revising asset management plans, nor does it delineate between “critical” assets to illustrate which assets are regulatory controlled, mission critical, or simply unreliable.
We need to recognize that all assets are not created equal. We also need to remember that the model we are trying to implement is an “analysis”, which by definition means to scrutinize or examine the data collected to gain knowledge for the purpose of making intelligent, data-driven decisions. The results of our analysis should not only identify those assets that are within the top 20%, but should also indicate the leading characteristic that makes each asset critical.
Using the Table 1 example, we might conclude that the “No. 12 Cooling Water Pump” is a critical asset as it falls within the top 20% guidelines, but the score of ‘80’ alone tells us nothing about how to manage this “critical” asset. Because we categorized the risk attributes, we are able to quickly identify that by reducing the consequences associated with a single-point-failure, through Single Minute Exchange of Die (SMED), ready service spares, or properly managed critical spares inventory, we can lower the criticality ranking, allowing Maintenance and Operations to focus their efforts on the truly unreliable, unpredictable assets.
The last post next week will talk about "managing assets by criticality"
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