RELIABILITY ASSESSMENT FOR AN AUTOMOBILE CRANKSHAFT UNDER RANDOM LOADING

This paper presents the stochastic process for reliability  assessment based on the fatigue life data under random loading for structural health monitoring of an automobile crankshaft due tofatigue failure. This is based on reported failure of the component due to the effect of the random loads that acts on the component during its operating condition over a given period of time. Since there are significant limitations of the experimental analysis in terms of actual loading history, therefore, the reliability assessment is considered to be less accurate. Hence, the reliability assessment based on fatigue life data using the Markov process by incorporating loading data to synthetically generate loading history has been proposed in this study. The Markov process has the capability of continuously updating the loading history data to reduce the intervals between each data point for reliability assessment based on the fatigue life data. The accuracy of the proposed monitoring system for reliability assessment was validated through its statistical method. The reliability assessment from the Markov process corresponded well by providing an accuracy of more than 95% when compared towards the actual sampling data. The reliability of the crankshaft based on the fatigue life assessment provides a highly accurate  for the improvement and control of risk factors in terms of structural health monitoring by overcoming the extensive time and cost required for fatigue testing