I'm having some trouble trending turbofan jet engines exhaust gas temperatures (EGT). Data collected shown that EGT measured in the test cell versus EGT measured on-wing while flying is different.
EGT measured in the test cell is normalised to standard day conditions by correcting for temperature, humidity, test cell correlations etc, to give EGT hot day (EGTHD). These correction factors are fixed by the OEM. After the engines are run in the test cell, they are installed on the aircraft and their EGT measured, and then normalised to standard day condition (EGTHD) using a different set of correction factors, as a basis of comparison.
So what was observed is that EGTHD calculated in the test cell versus on aircraft is different; this difference is normally distributed with mean 0 and std dev 8. The std dev is a little high as 8 deg C is roughly 10% of EGT, and with a 3 s.d, it reaches 30%.
I have a little hypothesis on the difference: Model errors could be introduced in the normalising process. Since the multifactor regressions would result in some residuals, and assuming that these residuals are random, then the normal distribution observed should be logical as it follows central limit theorem. OEM has also mentioned that for a certain correction factor, the error is observed to be larger at extreme ends i.e residuals at the extremes are greater than in the middle part.
Now I am curious as to whether this distribution of difference is acceptable (clearly my bosses do not think so), and whether the test cell correlation has shifted out of limits. Right now I am attributing the variation to the errors introduced in the normalisation process. Is there any statistical parameter that I should ask the OEM regarding their normalising process to get a better analysis? i.e standard error, std dev of residuals etc.
Thanks in advance!