Manufacturing analysis and data acquisition in advanced machining
Master thesis
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https://hdl.handle.net/11250/2774256Utgivelsesdato
2021Metadata
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To cut cost of maintenance, being able to stop the machines at the right time before fault andthe possibility to implement zero defect manufacturing is an important part of manufacturingaeroplane engine parts. The purpose of this report is to test a statistical method on differentdata sources of GKN Aerospace Norway, and Sweden to see what kind of available datasetis best suited to prevent high maintenance cost and identify faults in the machine.The data sources are based on calibration data of a probe and temperature from a Carnaghivertical turning lathe machine at GKN Aerospace Norway, and vibration and runout datafrom the spindle on a GROB milling machine at GKN Aerospace Sweden. Using Principalcomponent analysis and Mahalanobis distance to analyse these datasets will give a betterpicture of what kind of data to use when implementing condition-based maintenance oroptimising fault recognition.After testing both datasets, the dataset available from the GROB machine made it possibleto see when the spindle of the machine slowly started to deteriorate before a fault happened.This was possible since the dataset had a known fault. The calibration dataset shows it ispossible to identify deviations from normal calibration, and may make it easier to analysedeviation on later calibration. The method is not implemented into either of the sites, butthis report may give more background for further work.