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DATA
How much valuable information are you losing because of
inconsistencies in the information that was entered into your
data management system We have all heard the saying,
“garbage in, garbage out,” but what does that really mean
FALK 1040-EZ
FALK 1040EZ
FALK 1040EZ
To the human eye, the above example shows three gearboxes that are the
same make and model, but to a computer that is processing data for the
generation of failure models, maintenance expenses tracking, and spare
parts stock lists, there are three different make and models of gearboxes.
The differences in the descriptions are subtle - an extra space or a dash -
but these extra characters create different gearbox units. The same applies
to a mere typographical error.
Now, imagine that you have 500 gearboxes in your plant. All of them
are a Falk 1040EZ, and ALL of them have a slightly different entry for
their make, model, or description. How much time is wasted scrubbing
the data before a failure model can be created Running a simple failure
model might take an hour or two, but the data preparation can add
weeks to that time line. Are you tracking maintenance costs collectively
by make and model You could be seeing costs spread over multiple
categories that should be grouped into one, and this gives an artificially
low result for problem component types. This can increase the space
required for parts storage through unnecessary duplication of parts, based
on the component categories.
Data entry is often overlooked as a menial task. However, good data
entry is the backbone of a reliable maintenance program. To increase
the consistency of data entry, knowledge and understanding of the
information being entered is needed, as well as the know-how to research
and make corrections when discrepancies are found.
Stacy Heston is a Subject Matter Expert in Lubrication with Allied Reliability. She is a Certified
Lubrication Specialist (CLS), OMA, CMRP, MLA, and MLT. http://www.linkedin.com/in/stacyheston