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metadata.fyp.dc.title: Maintenance Time Prediction For Aircraft Turbine Engine Components; Removal And Replacement
metadata.fyp.dc.contributor.*: Syaza Nurnadia Binti Abdul Sani 24-Oct-2013
metadata.fyp.dc.description.abstract: The purpose of this research is to verify maintenance prediction time of aircraft turbine engine components on Removal and Replace (R&R) concept. This is carry out by applying Procedure III as stated and published in MIL-HDBK- 472. This maintainability procedure describes a method of performing maintainability prediction of ground electronic systems and equipment by utilizing the basic principles of random sampling. The rationality of utilizing the basic principles of random sampling is that because the data collection is gained faster, the data set is smaller and thus it is possible to ensure the homogeneity and to improve the accuracy and quality of data. Apart from that is because; the cost being set up is lower as it taken from independent observations. The point of application of MIL-HDBK 472 is followed in order to calculate the prediction maintenance time. This procedure is adaptable for performing maintainability predictions during design and development stage. In the last stage of making work of MIL-HDBK-472 is focuses on the verification of the maintenance prediction time as per the procedure being accomplished. Based on the calculation and comparisons data being conclude, it will determine the assertion of this research and therefore verified the aim and objectives of the study. The potential outcomes of this research activity will be a potential methodology to estimate as well as to predict the maintenance task time for specific aircraft components especially aircraft mechanical components. In addition it is also potentially to identify multi function of MIL-HDBK-472 which previously designed to predict and estimate aircraft electrical and electronic components.
metadata.fyp.dc.description: Bachelor Of Aviation Engineering Technology (Hons) Mechanical
Appears in Collections:Final Year Project - UniKL MIAT

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