Reliability analysis study using weibull model

In this project, a guideline to clean and process data that will be used for reliability analysis is developed. As raw data sets often contain many issues that might hinder the quality of the results obtained from reliability analysis, life data samples of a component are used to simulate the proces...

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Bibliographic Details
Main Author: Ng, Ding Yuan
Other Authors: Pang Hock Lye, John
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/149222
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Institution: Nanyang Technological University
Language: English
Description
Summary:In this project, a guideline to clean and process data that will be used for reliability analysis is developed. As raw data sets often contain many issues that might hinder the quality of the results obtained from reliability analysis, life data samples of a component are used to simulate the process of data cleaning. This is performed by using modules such as Pandas and NumPy within the Python programming language, together with an open-source software called Jupyter Notebook. By doing so, this project hopes to demonstrate how common issues that exist within raw data sets can be handled.The cleaned data will then be used to perform reliability analysis to predict the life cycle of the component using the Weibull distribution model. Since there are different statistical methods that can be used to formulate the model, the project also evaluates the different methods by comparing and analysing their results.