Used oil analysis is a tool, and like
most tools, it can be properly
used or misused, depending on
the application, user, surrounding conditions,
etc. A number of articles and publications
explain how to interpret the information in an
oil analysis report, but most fail to address
one very important issue: statistical normalcy.
What is "normal" in a data set represents the
typical average values and expected variation
within that group. It's a matter of how to view
a series of used oil analyses and how the
results can shape your view of a healthy or
ailing piece of equipment as well as the
viability of continued lube service.
Most people have heard of the Six Sigma
approach using statistics and other similar
concepts. These are applicable to the world
of lubricants as much as any other topic.
Statistical analysis can be applied in both
small and large viewpoint formats. Typically,
these are referred to as micro-analysis and
macro-analysis. Micro-analysis looks at one
specific entity and lets data develop as inputs
affect it. An example of this would be
performing a series of used oil analysis tests
on one engine with reasonably consistent
usage patterns. All inputs (lubricant, fuel,
filtration, sample cycle, etc.) are held constant
or with minimal change so the natural devel
-
opment of information can be seen. This is
done
to establish ranges and to allow for any
trends to develop. Over time, this method
-
ology can be used to decide which product
or process excels over another for a
specific application.
By DaviD E. nEw Ton, CarriEr CorporaTion/UTC
OIL ANALYSIS
Oil Analysis of
Engines
Surprising Findings from
Automotive
24
|
January - February 2016
|
www.machinerylubrication.com
