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For a quick and easy criticality assessment, you can use a risk assessment method.

Risk = [Likelihood] x [Consequence]

"Likelihood" can be estimated from MTBF (if available) or estimated based on knowledge and experience.

1 = MTBF less then 1 year

2 = MTBF 1-2 years

3 = MTBF 2-5 years

4 = MTBF 5-10 years

5 = MTBF more than 10 years

Consequence, in a maintenance and reliability context, is reduction in plant capacity (among other things, please feel free to add other factors).

0 = Plant Shut Down

1 = 50% reduction in capacity

2 = 20% reduction

3 = 10%

4 = 5%

5 = 2%

and so on.

Multiply the consequence factor by the likelihood factor, and the equipment with the lowest scores are the most critical.

I sincerely hope this helps.

For a quick and easy criticality assessment, you can use a risk assessment method.

Risk = [Likelihood] x [Consequence]

"Likelihood" can be estimated from MTBF (if available) or estimated based on knowledge and experience.

1 = MTBF less then 1 year

2 = MTBF 1-2 years

3 = MTBF 2-5 years

4 = MTBF 5-10 years

5 = MTBF more than 10 years

Consequence, in a maintenance and reliability context, is reduction in plant capacity (among other things, please feel free to add other factors).

0 = Plant Shut Down

1 = 50% reduction in capacity

2 = 20% reduction

3 = 10%

4 = 5%

5 = 2%

and so on.

Multiply the consequence factor by the likelihood factor, and the equipment with the lowest scores are the most critical.

I sincerely hope this helps.

I have been using 9 questions for scoring criticality as it is standard policy. 

I like what Jim offered in that accounts for the extra capacity units in parallel that exist to increase overall reliability. For example, when you have 10 of the same equipment unit and you can run 100% expected throughput with 7 units, you need a way to adjust the criticality scores accordingly. 

I have not seen a way that reflects what really happens when you have 1 of the 10 down, 2, 3, 4 down for example. Just because there are three extras does not mean you reduce PM frequency on all 10. To preserve R&M budget, management may choose to make one or two temporarily inactive. An inactive state PM should be activated to provide a minimum PM to preserve it for future use. If there is only one out of ten down for repair or overhaul the reaction (or work order priority for the next unit down) is not the same as if there were 3 or 4 down out of ten down (which would be a production loss). 

I wonder if anyone else feels this way about how we score criticality of equipment with many "extra" identical units that exist because each tends to have a relatively high failure rate? When equipment is determined to be an "A" critical asset, it gets special attention to keep it from failure frequency and consequence. Could so much special care be applied to improve the equipment that it finally becomes a critical "B" asset and some "B" assets then become "A" assets? I wonder this when I see a very high priority work order written on a "C" critically scored asset and wonder how that happens. Was it scored wrong or did someone forget it's criticality ranking?   

In Ramesh Gulati's, Maintenance and Reliability Best Practices (Second Edition)  page 97, Critical safety items get the highest scored criticality. "Critical to continued production of primary product" gets the next highest criticality score. "Ancillary (support) system to main production process" gets the next highest score. "Stand-by unit in a critical system" gets a lower score. "Other ancillary assets" scores the lowest of these. The current method and assumptions I have been using do not say all of these things these things, but the groups I gather to score asset criticality are thinking about how many extras they have, no matter how many times I tell them the assumption says not to. 

For a quick and easy criticality assessment, you can use a risk assessment method.

Risk = [Likelihood] x [Consequence]

"Likelihood" can be estimated from MTBF (if available) or estimated based on knowledge and experience.

1 = MTBF less then 1 year

2 = MTBF 1-2 years

3 = MTBF 2-5 years

4 = MTBF 5-10 years

5 = MTBF more than 10 years

Consequence, in a maintenance and reliability context, is reduction in plant capacity (among other things, please feel free to add other factors).

0 = Plant Shut Down

1 = 50% reduction in capacity

2 = 20% reduction

3 = 10%

4 = 5%

5 = 2%

and so on.

Multiply the consequence factor by the likelihood factor, and the equipment with the lowest scores are the most critical.

I sincerely hope this helps.

I have been using 9 questions for scoring criticality as it is standard policy. 

I like what Jim offered in that accounts for the extra capacity units in parallel that exist to increase overall reliability. For example, when you have 10 of the same equipment unit and you can run 100% expected throughput with 7 units, you need a way to adjust the criticality scores accordingly. 

I have not seen a way that reflects what really happens when you have 1 of the 10 down, 2, 3, 4 down for example. Just because there are three extras does not mean you reduce PM frequency on all 10. To preserve R&M budget, management may choose to make one or two temporarily inactive. An inactive state PM should be activated to provide a minimum PM to preserve it for future use. If there is only one out of ten down for repair or overhaul the reaction (or work order priority for the next unit down) is not the same as if there were 3 or 4 down out of ten down (which would be a production loss). 

I wonder if anyone else feels this way about how we score criticality of equipment with many "extra" identical units that exist because each tends to have a relatively high failure rate? When equipment is determined to be an "A" critical asset, it gets special attention to keep it from failure frequency and consequence. Could so much special care be applied to improve the equipment that it finally becomes a critical "B" asset and some "B" assets then become "A" assets? I wonder this when I see a very high priority work order written on a "C" critically scored asset and wonder how that happens. Was it scored wrong or did someone forget it's criticality ranking?   

In Ramesh Gulati's, Maintenance and Reliability Best Practices (Second Edition)  page 97, Critical safety items get the highest scored criticality. "Critical to continued production of primary product" gets the next highest criticality score. "Ancillary (support) system to main production process" gets the next highest score. "Stand-by unit in a critical system" gets a lower score. "Other ancillary assets" scores the lowest of these. The current method and assumptions I have been using do not say all of these things these things, but the groups I gather to score asset criticality are thinking about how many extras they have, no matter how many times I tell them the assumption says not to. 

For a quick and easy criticality assessment, you can use a risk assessment method.

Risk = [Likelihood] x [Consequence]

"Likelihood" can be estimated from MTBF (if available) or estimated based on knowledge and experience.

1 = MTBF less then 1 year

2 = MTBF 1-2 years

3 = MTBF 2-5 years

4 = MTBF 5-10 years

5 = MTBF more than 10 years

Consequence, in a maintenance and reliability context, is reduction in plant capacity (among other things, please feel free to add other factors).

0 = Plant Shut Down

1 = 50% reduction in capacity

2 = 20% reduction

3 = 10%

4 = 5%

5 = 2%

and so on.

Multiply the consequence factor by the likelihood factor, and the equipment with the lowest scores are the most critical.

I sincerely hope this helps.

For a quick and easy criticality assessment, you can use a risk assessment method.

Risk = [Likelihood] x [Consequence]

"Likelihood" can be estimated from MTBF (if available) or estimated based on knowledge and experience.

1 = MTBF less then 1 year

2 = MTBF 1-2 years

3 = MTBF 2-5 years

4 = MTBF 5-10 years

5 = MTBF more than 10 years

Consequence, in a maintenance and reliability context, is reduction in plant capacity (among other things, please feel free to add other factors).

0 = Plant Shut Down

1 = 50% reduction in capacity

2 = 20% reduction

3 = 10%

4 = 5%

5 = 2%

and so on.

Multiply the consequence factor by the likelihood factor, and the equipment with the lowest scores are the most critical.

I sincerely hope this helps.