Machinery Lubrication magazine published by Noria Corporation
Issue link: http://www.e-digitaleditions.com/i/629709
www.machinerylubrication.com | January - February 2016 | 29 per million over five years of data. However, if you look at the iron wear in detail, a great storyline develops. When the oil was run longer, the iron went up and very predictably. In 2007, the average oil sample was taken at 4,500 miles, and the iron average was 10.2 ppm. Five years later, the average oil sample was taken at 8,100 miles, and the iron average was at 18.1 ppm. An 80-percent increase in mileage was mirrored in a resultant 80-percent increase in iron. That is a very predictable response curve; the wear is consistent. When oil is changed frequently, a higher iron wear metal count will be seen in the oil analysis results. There are two reasonable explanations for this phenomenon — residual oil and tribo-chemical interaction. Studies have shown that elevated wear levels after an oil change can be directly linked to chemical reactions of fresh addi- tive packages. In addition, when you change oil, no matter how much you drip into the catch basin, there is always a moderate amount left in the engine. It is estimated that up to 20 percent of the old oil remains, depending on the piece of equipment. So when you begin your new oil change interval, you are not starting at zero ppm. While the wear rate is not greatly esca- lated at the front end of the oil change interval, it certainly is not lessened by frequent oil changes either. Changing your oil early does not reduce wear rates, presuming you did not allow the sump load to become compromised. When you have reasonably healthy oil, the wear rate slope is generally flat. Only after the oil becomes compromised in some manner would you see a statistical shift in wear rates. Thus, higher wear at the front of an oil change interval is plausible, but the claim of lesser wear with fresh oil is most certainly false. Those who change oil frequently at 3,000 miles are not helping their engine, and those who leave it in for longer periods are not hurting the engine. The oil analysis results from this example showed that engine wear was generally unaffected by operational condi- tions and oil change intervals. It was also concluded that the filtration selection, oil brand and grade, as well as various service factors did not have much of an influence on the results. For this engine, it didn't make much difference what oil was used or how it was driven. The next set of data in Table 4 is from a V-8 diesel engine. These oil analysis samples represent fairly high-mileage vehi- cles, with 179 of the 527 samples from vehicles with more than 100,000 miles and many others from vehicles with more than 250,000 miles. Once again, there is a need to manipu- late the data to remove abnormalities. Forty-one samples had ultra-high copper (Cu) counts, with many readings more than 100 ppm and some more than 300 ppm. Therefore, a separate "copper prime" column was created to root out the high flyers. Although some might decry the removal of data, you can clearly see how these spikes can adversely affect what is deemed "normal." While 41 samples may seem like a large amount of data to remove, they represent only 7.7 percent of the total population, and yet their removal resulted in nearly a 79-percent drop in the "average" copper magnitude (from 16 to 3.4 ppm). To determine how the oil's life cycle affected wear rates, three sub-groups were examined: 3,500 miles, 7,500 miles and 11,500 miles. Again, higher iron wear rates were revealed toward the front of the oil change interval (see Table 5). In no way does this mean that an engine is being harmed, but it directly contradicts the mantra that more is better ("more" being more frequent oil changes and "better" being less wear). At some point the iron wear rate will begin an ascent and AL CR FE CU PB Truck A (synthetic oil and bypass filtration) 2 1 15 4 1 Truck B (conven- tional oil and filter) 2 0 14 3 5 Standard Deviation 1.2 0.5 10.5 4.3 2.5 Upper Limit 6.4 1.8 47.9 16.2 9.6 AVERAGE LEAD STANDARD DEVIATION Full Data Set 2.8 27.4 Revised Data Set 1.2 2.8 OIL MILES VEHICLE MILES AL CR FE CU CU PRIME PB 7,261.2 100,398.8 Average 2.7 0.3 16.3 16.0 3.4 2.1 4,006.1 76,147.9 Std. Dev. 1.2 0.5 10.5 53.0 4.3 2.5 19,279.6 328,842.6 Upper Limit 6.4 1.8 47.9 175.1 16.2 9.6 28,417 843,817 Max. 8 1 75 484 34 29 PPM Per 1,000 Miles 0.4 0.0 2.2 2.2 0.5 0.3 MILES 3,500 7,500 11,500 Iron PPM Per 1,000 Miles 3.0 2.3 2.0 ML Table 3. An example of how a few data points can skew the results Table 4. A macro-analysis example from a V-8 diesel engine Table 6. Oil analysis results for two diesel-engine trucks that were driven in similar circumstances but with different engine oils and filters Table 5. An example of using three sub- groups to determine how the oil's life cycle affected wear rates