Beyond the Flanges
Robert X. Perez
Understanding Dirty Data:
Comparing MTBR, MTBF,
and MTBPM
When I was first asked to define MTBF, MTBR,
and MTBPM, I wasn’t sure why. Of all the myriad
reliability metrics employed, I had to ask myself,
“Why were these singled out?” It wasn’t until I ran across the
following definition from PIP did I understand:
Process Industry Practices (PIP) defines Mean Time
Between Repairs as: “The most common measure of operat-
ing reliability typically stated as the average operating calendar time between required repairs for a particular piece of
machinery, type of machinery, class of machinery, operating
unit or plant. MTBR is not Mean Time Between: (a) Failures, (b) Planned Maintenance, or (c) any other categorization of shutdowns. MTBR calculations include Repairs due
to (a) Failures, (b) Planned Maintenance, or (c) any other
categorization of Repair events.”
I was surprised to find all three reliability metrics of
interest mentioned here. As I thought more about this PIP
definition, I began to realize why these metrics are so important and why they need to be better understood.
was written for: maintenance personnel. I have worked in
maintenance organizations for over 20 years, so I feel somewhat qualified to present the maintenance perspective on
maintenance data analysis.
Let’s first consider a hypothetical pump timeline (see
Figure 1).
We can see that this timeline is composed of various event
types, i.e. failures, repairs,
and PM events. Ideally, we
would like to know how long
a new or refurbished pump
lasts before it fails. But there
is always a trade-off between
theory and practice. In reality, you are usually only able
to determine the average or
mean between time between
failures or repairs. Reliability theory tends to deal
with failure data, while maintenance organizations deal with
maintenance events. “But aren’t failures and maintenance
events the same thing?” you ask. My response is, “Not at all.”
Maintenance events fall to many categories, such as:
• Repairs to restore pumps to serviceable conditions
• Regular internal pump inspections
• Preventative maintenance events, such as oil changeouts
• Predictive maintenance events, such as data collections
• Preemptive repairs that are done before a pump actually
fails
• Maintenance activities that are not associated with a
pump but are credited to a pump’s functional location
due to the proximity of the work
Reliability theory tends to deal with failure
data, while maintenance personnel deal with
maintenance events. Failures and maintenance
events are not the same thing at all.
Dealing with Dirty Data
Before I define the reliability terms in question, I want to
provide some perspective on the person that the PIP standard
Only the first category actually pertains to a known
pump failure. It should be noted that the second category is
Installation
Repair
Repair
Failure
Failure
PM
PM
