Turn around time prediction of aero engines grouped based on specific repair
Aircraft Engine Overhaul Divisions overhaul aero engines that have encountered unexpected failure during flight operation. The process of overhauling damaged parts sometimes doesn't involve only refurbishing damaged parts or component replacement, but also investigating into the root c...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | http://hdl.handle.net/10356/54782 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Aircraft Engine Overhaul Divisions overhaul aero engines that have encountered
unexpected failure during flight operation. The process of overhauling damaged
parts sometimes doesn't involve only refurbishing damaged parts or component
replacement, but also investigating into the root cause behind failure. It is mandated
by aviation authorities to find out reasons behind an engine failure as flight safety
has to be accounted for. In an Engine Overhaul Division (EOD) every engine needs
to be overhauled within a certain fixed number of days or overhauling Tum Around
Time (TAT). But when engines need to be repaired for certain failure and
investigated into failure, the process can consume extra days from the fixed Engine
Tum Around Time (TAT) without keeping up with the target. This delay can have
an impact on engine availability for airline customers as airlines would have
planned flight operations based on availability of engines. Delay or unavailability of
engine can entail costs in terms of fleet management and also human factors, if a
failure repeats itself leading to catastrophe. This also reflects on the productivity
and competitiveness of the EOD.
This study focuses on predicting the delay encountered by engines which have a
specific repair and investigation requirement. The repair engines overhauled in an
Engine Overhaul Division are classified into six groups based on similar failure
symptoms. Based on past engine data, the delays in TAT of engines are calculated
and suitable forecasting methods are identified to predict future delays. Two
forecasting models, namely the Method of Moving Averages and Non Linear Grey
Bernoulli method are used to generate suitable forecasts. Accuracy of the forecast is
evaluated using error diagnostic Mean Absolute Percentage Error (MAPE). The
results are compared between the actual recorded values and the predicted values
generated by the forecasting methods. On comparing the results it was found that
both forecasting methods have performed well with reasonable forecasting power.
Also, one group of investigation demonstrated high MAPE possibly suggesting
improper regrouping. |
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