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M-11 EGR Oil Filter Pressure Delta Beaded Filter Correction Factor

M-11 EGR Oil Filter Pressure Delta Beaded Filter Correction Factor. Jennifer Van Mullekom, Ph. D. Correction Factor.

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M-11 EGR Oil Filter Pressure Delta Beaded Filter Correction Factor

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  1. M-11 EGR Oil Filter Pressure Delta Beaded Filter Correction Factor Jennifer Van Mullekom, Ph. D.

  2. Correction Factor • The introduction of a new beaded filter into the M-11 EGR Test has resulted in a mean shift in the mild direction and a three fold decrease in the variation of the test for reference Oil E.

  3. M-11 EGR OFPD Data Beaded Filters

  4. How do we correct this shift in severity and precision so that we maintain the integrity of the test as set forth in API Category CI-4? These limits were set at the start of the category and define performance. Generally, oils with a true mean performance below 275 are good, those between 275 and 340 are borderline, and those with a true mean performance above 340 are poor oils. Maintaining Level of Severity

  5. Maintaining Level of Severity • What does this mean? • Good oils maintain or improve pass rate • Poor oils maintain or decrease pass rate • Borderline- “gray area”

  6. Proposed Correction Factors • Square Root • Mean correction factor • Precision correction factor • Natural Units • Mean correction factor • Precision correction factor

  7. Sqrt Mean Corr. Factor Details • Take square root of OFDP. • Add 3.15. • Square the sum. Example: My OFPD result is 144. The square root of 144 is 12. The sum of 12 and 3.15 is 15.15. After squaring 15.15 and rounding, I get 230.

  8. Sqrt Precision Corr. Factor • Take square root of OFDP. • Add 6.68- The pass limit from the old filter data is 2.06 standard deviations above the mean. Calculate the value 2.06 standard deviations above the mean with the improved precision on the beaded filters. Calculate the difference. • Square the sum.

  9. Natural Units • Mean correction factor • Add 66.19 • Precision correction factor • Add 99.86 • In natural units the pass limit for the old filters is 2.42 standard deviations above the mean. A pass limit 2.42 standard deviation units above the mean for the beaded filters was calculated. The difference in the two limits is 99.86.

  10. To Transform or Not to Transform? • The matrix data was transformed due to problems with variability. These could be due to the filters or the oils. • In examining Oil E, normal probability plots and tests indicate that both the old filter data and the new filter data are normal. • Issues • Are all oils that go through this test “normal”? • If we eliminate the transformation now, we may have to re-institute it when we change filters and reference oils in the near future.

  11. What is the impact of the correction factors? • Use simulations to investigate the effect of the correction factors on the pass rate for good, borderline, and fail oils for a one test pass, a pass within two tests, and a pass within three tests. • Graphs follow- The first blue bar is the benchmark. Compare all correction factor pass rates to this bar. The maroon bar is what happens if we do nothing. Again in order to maintain the integrity of API CI-4, the pass rate with the correction factor should stay the same or improve for good oils; it should stay the same or decrease for poor oils.

  12. One Test Pass

  13. Two Test Pass

  14. Three Test Pass

  15. Conclusions • Failure to use a correction factor will result in poor oils passing this parameter on the test. This changes the definition of CI-4. • The correction factor based on precision (both square root and natural units) results in reducing the passing percentage for all oils- good or poor. This also changes the definition of CI-4. • The correction factor based on mean in transformed (square-root) units coupled with the natural improvement in precision results in a higher probability of passing for good oils and a lower probability of passing for poor oils. This option maintains, and even improves the integrity of CI-4.

  16. Conclusions Continued • The correction factor based on mean natural units coupled with the improvement in precision results in a higher probability of passing for good oils and a lower probability of passing for poor oils. This option maintains, and even improves the integrity of CI-4.

  17. Recommendation • Adopt mean correction factor in either transformed units or natural units. • Advantage • Maintains the integrity of CI-4 • Improves discrimination between good and poor oils • Avoids complication of future shifts due to parts/hardware changes

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