Penilaian taburan hayat lesu komponen automotif dengan bebanan ekstrem melalui pendekatan ciri hayat taburan dan fungsi keboleharapan
Extreme event always occur on a moving vehicle such as violation of the hole or a large object on the road. The strong shock can cause damage to vehicle components. It is different for the normal road condition that is not contributes to any extreme load. Failure of a component that is caused extrem...
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Online Access: | http://eprints.utem.edu.my/id/eprint/14810/1/Penilaian%20Taburan%20Hayat%20lesu%20Komponen%20Automotif%20Dengan%20bebanan%20Ekstrem%20Melalui%20Pendekatan%20Citi%20Hayat%20Taburan%20dan%20Fungsi%20Keboleharapan%2024pages.pdf |
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| Summary: | Extreme event always occur on a moving vehicle such as violation of the hole or a large object on the road. The strong shock can cause damage to vehicle components. It is different for the normal road condition that is not contributes to any extreme load. Failure of a component that is caused extreme load events such as strong shock can affect the overall quality and reliability of the vehicle component groups. As such, the study needs to be done to address the behavior of failure data using the fatigue life and reliability characteristics of extreme fatigue life failure statistical approach. The study can also be done by developing a characterization of life distributions based data and configuration best match load to allow a generalized prediction. The research involves testing the fatigue life and cyclic strain fatigue life data generation using Monte Carlo simulation based on the parameters of probabilistic stress cycle curve. Features for all parametric distributions were analyzed by the method of parameter estimation approaches rank regression method on X, rank regression method on Y and the method of maximum likelihood estimation for the Weibull, lognormal and generalized extreme value distributions. Assess the suitability of the life distribution for the reliability of extreme fatigue life can be seen through a probability density function, cumulative distribution function and also through their reliabilities obtained. For verification, steering knuckle component service load conditions is compared with stub axle component service burden and found comparative studies lead to the same decision. The contribution of this study is to introduce generalized extreme value distribution applications in the mechanical domain where overall comparisons found that the method using the generalized extreme value distribution is more flexible and satisfied the failure of extreme life curve given. The study also found that the developed method capable of predicting the relationship between the load configuration and shape of the distribution of a component failure studied. This approach can contribute to reduced time of experimental testing which is emphasis in the production process components. This implication provides a particularly significant impact on the development of the country's automotive industry.
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