1. Test Report
Differentiating Filter Performance
By
Oil Analysis Results

2. SUMMARY
Purpose
This report documents the analysis of data from a field test run jointly between Fleetguard and a major
trucking fleet in North America from April 1997 to early 1999. The test generated large amounts of oil
analysis data from three different lube filters, of low medium and high efficiency, running extended change
intervals on extended oil drains. The analysis of the data was done to determine if oil analysis alone is a
good indicator of filter performance and engine wear protection levels provided by lube filters.
The purpose of this report is to document the analysis of the data from the above described field test
and determine if oil analysis alone is a good indicator of filter performance and engine wear protection
provided by a lube filter. Oftentimes, oil analysis is considered a sure-fire means of predicting the
level of protection a filter is providing to an engine. If oil analysis were indeed a good predictor of
engine wear protection a filter provides, analysis results would provide a means of comparing
different filters and theirperformance in the field. This report attempts to determine if oil analysis is or
is not a good tool to use for these filter comparisons.
Conclusion
Results show that the oil analysis data from the filters in the field test were deemed statistically
equal. Because the oil analysis data from the filters were deemed statistically equal, oil analysis
data alone is not an acceptable means of comparing filter performance.
Field Evaluation Background/Purpose
In April of 1997, a major North American trucking fleet and a major oil company started a joint test with
Fleetguard. The original purpose of the test was to evaluate the effects of extended service intervals
on the oil and the structural durability of the filters and the engines. However, the data generated
proved to be useful in determining if oil analysis could truly differentiate filter performance. The test was
completed in early 1999.
The test was comprised of two parts:
• First, the oil company was evaluating extended oil drain intervals. The drain intervals were
extended out to 100,000 miles and beyond. Make-up oil was added when ever necessary, with a
maximum of 1 gallon at any one given time.
• Second, Fleetguard was evaluating extended service intervals of filters used on heavy duty diesel
engines. The filters were left in service for 50,000 miles on 75 vehicles and 100,000 miles on 8
vehicles. Oil samples were taken from the test vehicles at regular intervals.
Filter Component Information
Three filters were used for these evaluations.
1. High Efficiency - Single element filter, 99% efficient at 10 micron
2. Medium Efficiency - Dual element combination filter, primary element 59% efficient at 10 micron,
bypass element 98% efficient at 10 micron
3. Low Efficiency - Single element filter, 55% efficient at 10 micron
Data Description
The above described field test provided a large quantity of oil analysis data taken from a single fleet of
vehicles which were using three different levels of engine oil filtration. On top of that, some of the vehicles
1

3. which were running the medium efficiency filter were allowed to go for 100,000 miles before the filter was
changed, while the majority of the medium efficiency filters were changed at 50,000 miles. The fleet of
vehicles also was exposed to extended service oil drains where only make up oil was added (the oil was
not drained for 100,000 or more miles). The wear contaminants produced by the engine were never
flushed from the engine, although they were diluted when make up oil was added.
The oil analysis results were made up of Ion Inductively Coupled Plasma results for Aluminum,
Chromium, Copper, Iron, Lead, Tin, Silicon, Sodium, and Potassium. It should be noted that ICP tests
are unable to detect particles larger than 3 micron. Also included in the analysis results were oil vis-
cosity at 100° C and Fourier Transform Infrared results for percent soot and water content.
Hence, this test provided oil analysis results over 200,000 miles in four distinct groups:
• Medium efficiency filter w/100,000 mile changes
• Medium efficiency filter w/50,000 mile changes
• High efficiency filter w/25,000 mile changes
• Low efficiency filter w/25,000 mile changes
Note: The oil analysis data was the only piece of data available when this report was written. There
was no data showing when or how much make-up oil was added to each engine, nor was there any
data detailing the exact change interval that the filters were exposed to.
Data Analysis
To facilitate data analysis, two sets of data were pulled out of the population.
Group 2
Group 1
• Vehicles entered test with ~350,000 miles
• Vehicles entered test with ~250,000 miles
• Vehicles were under test ~200,000 miles
• Vehicles were under test ~175,000 miles
These data sets were made up of 7 & 6 vehicles respectively. The vehicles were equipped with the
following filters.
Group 1 Filters Group 2 Filters
1 - High efficiency changed at 25k miles 1 - High efficiency changed at 25k miles
2 - Low efficiency changed at 25k miles 2 - Low efficiency changed at 25k miles
3 - Low efficiency changed at 25k miles 3 - Medium efficiency changed at 100k miles
4 - Medium efficiency changed at 100k miles 4 - Medium efficiency changed at 100k miles
5 - Medium efficiency changed at 100k miles 5 - Medium efficiency changed at 50k miles
6 - Medium efficiency changed at 50k miles 6 - Medium efficiency changed at 50k miles
7 - Medium efficiency changed at 50k miles
To further facilitate the data analysis process, only a portion of the oil analysis results from each
sample in the data set were examined. The FTIR results for iron, lead & silicon and the viscosity and
soot results were singled out. These were chosen because they were hypothesized to be the best
indicators of oil degradation and engine wear.
At this point, the data sets were plotted for a visual comparison. Each of the variables (Fe, Pb, Si,
Vis@100C and soot ) was plotted separately for each of the two data groups. See Appendix A & B.
Then each of the variables was submitted to statistical analysis. An Analysis of Variance (ANOVA)
was done on each group of data.
2

4. The ANOVA test was used to determine if the means of each of the data sets for each variable was
equal. Equal means (averages) would indicate that differentiating filters may not be possible (based
on oil analysis data). Therefore, oil analysis results would not be an indicator of filter performance and
engine wear protection in field tests. Unequal means would indicate that differentiating filters may be
possible, which may indicate that oil analysis results could be an acceptable means of comparing fil-
ters. Further analysis would then have to be done to determine if a given filter (filtration level) stood
above the rest across all sets of data.
Data Interpretation
ANOVA results can be explained two different ways. The ANOVA test yields two values; the F-statistic
and the P-value.
F-statistic
F-statistic values near 1 indicate the variation between the samples and within the samples are
approximately equal. While F-statistic values well in excess of 1 indicate that there is significantly
more variation between the samples than within the samples. To determine if the sample means are
considered equal, the calculated F-value needs to be lower than the F-critical value. The F-critical
value is determined by the confidence level that at which the ANOVA test is run, the number of sam-
ples and the number of data points in the samples. The F-critical value is 2.25 for a confidence level
of 95%.
P-value
A P-value is described as the observed significance level for a statistical test. To determine if the
sample means are equal, compare the P-value to the alpha for the test. If the P-value is greater than
alpha, the sample means are equal. The test alpha value is 1 minus the confidence level. The alpha
value is .05 for a 95% confidence interval.
Results
The ANOVA tests were run at a confidence interval of 95%. The data sets in both groups of filters,
with the exception of Silicon, passed the ANOVA tests. See figure 1. In the group 1 silicon analysis,
filters 5 & 6 were not uniform with the rest, while in the group 2 silicon analysis, filter 1 was the
deviant outlying filter. See Appendices A & B.
ANOVA Results - 95% Confidence Intervals
Group 1 Group 2
F-value F-critical P-value Alpha F-value F-critical P-value Alpha
Iron 1.16 2.25 0.34 0.05 Iron 1.26 2.25 0.29 0.05
Lead 0.54 2.25 0.78 0.05 Lead 0.95 2.25 0.45 0.05
Silicon 10.02 2.25 0.00 0.05 Silicon 5.88 2.25 0.00 0.05
Viscosity 1.30 2.25 0.27 0.05 Viscosity 0.38 2.25 0.86 0.05
Soot 1.93 2.25 0.09 0.05 Soot 1.19 2.25 0.33 0.05
3

5. Figure 1 - Summarized ANOVA Results
Conclusion
Oil sampling and its related analysis results alone are not an acceptable means of differentiating filter
performance when it is based on field test data. All sample groups passed the ANOVA tests with the
exception of the Silicon sample from both groups 1 & 2. But, the outlying filters, were not the same in
both instances. Therefore, these ANOVA test failures may be due to some unseen or tested variable
unrelated to the filter.
Oil sample analysis may not be an acceptable means of differentiating filters for several reasons:
• Engine wear rates may not be identical - There are too many variables that affect this, filters being
just one of them. This could be due to driver differences and vehicle duty cycles.
• The particle size distributions for the engine wear particles may not be the same for all engines -
Particle size distribution would affect the number of particles passing under the cut point of the filter,
thus causing variations in the oil samples.
• Oil analysis tests such as ICP typically are unable to detect particles larger than 3 micron - The
results of the oil analysis tests will show a limited view of the actual condition of the oil. This is
especially true when engine failure is imminent and wear particles would be large enough to be
caught by a filter.
4

6. Appendix
Boxplots
A boxplot consists of four parts; a box, whiskers, outliers and median mark.
Median - A line is drawn across the box at the median.
Box - The bottom of the box is at the first quartile (Q1), and the top is at the third quartile (Q3) value.
The box encloses all of the values in the middle 50%.
Whiskers - Lines that extend from the top and bottom of the box to the adjacent values. The adjacent
values are the lowest and highest observations that are still inside the region defined by the following
limits:
Lower Limit: Q1 - 1.5 (Q3 - Q1)
Upper Limit: Q3 + 1.5 (Q3 - Q1)
Outliers - Points outside of the lower and upper limits and are plotted with asterisks (*).
Outlier
Upper whisker - Highest
Value within upper limit
Third Quartile Q3
Median
First Quartile Q1
Lower whisker - Lowest
value within lower limit
5

7. Appendix A - Group 1 Graphs
Group 1 - Iron Analysis
Oil Drain Intervals
161k 190k 218k 197k 187k 168k 185k
300
250
200
Fe (ppm)
150
100
50
0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6 Filter_7
Group 1 - Iron Analysis
(means are indicated by solid circles)
300
200
Fe (ppm)
100
0
Filter_2
Filter_1
Filter_3
Filter_4
Filter_5
Filter_6
Filter_7
6

8. Group 1 - Lead Analysis
Oil Drain Intervals
161k 190k 218k 197k 187k 168k 185k
120
100
80
Pb (ppm)
60
40
20
0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6 Filter_7
Group 1 - Lead Analysis
(means are indicated by solid circles)
100
90
80
70
60
Pb (ppm)
50
40
30
20
10
0
Filter_2
Filter_1
Filter_4
Filter_5
Filter_6
Filter_7
Filter_3
1 Confidential Test Report
7

9. Group 1 - Silicon Analysis
Oil Drain Intervals
161k 190k 218k 197k 187k 168k 185k
60
50
40
Si (ppm)
30
20
10
0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6 Filter_7
Group 1 - Silicon Analysis
(means are indicated by solid circles)
60
50
40
Si (ppm)
30
20
10
0
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_7
Filter_1
8

10. Group 1 - Viscosity Analysis
Oil Drain Intervals
161k 190k 218k 197k 187k 168k 185k
18.0
16.0
Viscosity @100°C (centistokes)
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6 Filter_7
Filler cut point - change interval
Group 1 - Viscosity Analysis
(means are indicated by solid circles)
15
14
Viscosity
@100°C
(centistokes)
13
12
Filter_3
Filter_2
Filter_1
Filter_6
Filter_7
Filter_4
Filter_5
9

11. Group 1 - Soot Analysis
Oil Drain Intervals
161k 190k 218k 197k 187k 168k 185k
3.0
2.5
2.0
Soot %
1.5
1.0
0.5
0.0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6 Filter_7
Group 1 - Soot Analysis
(means are indicated by solid circles)
3
2
Soot %
1
0
Filter_1
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_7
10

12. Group 2 - Iron Analysis
Oil Drain Intervals
235k 296k 226k 217k
214k 196k
400
350
300
250
Fe (ppm)
200
150
Appendix B - Group 2 Graphs
100
50
0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6
Group 2 - Iron Analysis
(means are indicated by solid circles)
400
300
Fe (ppm)
200
100
0
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_1
1 Confidential Test Report
11

13. Group 2 - Lead Analysis
Oil Drain Intervals
235k 296k 226k 217k
214k 196k
90
80
70
60
Pb (ppm)
50
40
30
20
10
0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6
Group 2 - Lead Analysis
(means are indicated by solid circles)
80
70
60
50
Pb (ppm)
40
30
20
10
0
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_1
12
Confidential Test Report 1

14. Group 2 - Silicon Analysis
Oil Drain Intervals
235k 296k 226k 217k
214k 196k
40
35
30
25
Si (ppm)
20
15
10
5
0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6
Group 2 - Silicon Analysis
(means are indicated by solid circles)
40
30
Si (ppm)
20
10
0
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_1
1 Confidential Test Report
13

15. Group 2 - Viscosity Analysis
Oil Drain Intervals
235k 296k 226k 217k
214k 196k
16.0
14.0
Viscosity @100°C (centistokes)
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Filter_1 Filter_2 Filter_3 Filter_4 Filter_5 Filter_6
Group 2 - Viscosity Analysis
(means are indicated by solid circles)
15
14
Viscosity
@100°C
(centistokes)
13
12
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_1
14
Confidential Test Report 1

16. Group 2 - Soot Analysis
Oil Drain Intervals
235k 296k 226k 217k
214k 196k
2.5
2.0
1.5
Soot %
1.0
0.5
0.0
Filter_3 Filter_5 Filter_6
Filter_1 Filter_2 Filter_4
Group 2 - Soot Analysis
(means are indicated by solid circles)
2.2
Soot %
1.2
0.2
Filter_2
Filter_3
Filter_4
Filter_5
Filter_6
Filter_1
For more information, call your Customer Assistance Representative at
LT15105
1-800-22FILTER (1-800-223-4583), fax 1-800-999-8664
©2003 Fleetguard Inc.
or visit us at www.fleetguard.com
Printed in the U.S.A.