Abstract
Dumpers or dump trucks are used all over the world to move overburden from many opencast mines. Diesel engines are the main driving force behind the trucks. The frequency of damage due to the failure of diesel engines is enormous. Therefore, efforts are necessary to analyze failure to reduce the downtime periods. A detailed analysis of engine failure at the subsystem level needs to be done. Reliability analysis and maintenance planning remain the norm in this regard. The obstacle faced while analysing the reliability of dumpers was the availability of a large number of data failures. In this paper, this issue is addressed by using Common Beta Hypothesis test and Meta-analysis test. The engine is divided into five subsystems. The result shows that all five subsystems pass the CBH test and Meta-analysis test. Accordingly, the failure data is grouped. The trend test of grouped failure data shows that the Failure data of two subsystems follows the independent and identically distributed characteristics while the remaining three do not follow it. The reliability is estimated for all five subsystems. Finally, fuel supply subsystems show the highest reliability while the lowest value is seen for self-starting subsystems.
Highlights
The main drive units used in dump trucks are diesel engines
After going through the recent studies on reliability analysis on small failure data, it is evident that the Common Beta Hypothesis (CBH) test and Meta-analysis test has not been seen as a possible solution for small failure data
Meta-analysis has been considered for medical studies, it has not been considered for machines
Summary
The main drive units used in dump trucks are diesel engines. Failure of components is unescapable and takes place due to the ongoing wear and tear process in working parts of the system. This deterioration can result in unexpected failures of the system which will incur a significant increase in repair cost than in scheduled maintenance or repair. To control the impact of cost, it is necessary to evaluate the reliability of the equipment and its components. Such a study will be useful for making maintenance decisions and incorporate adaptive changes in maintenance policies. A roadmap is provided using which reliability analysis could be possible for a small amount of failure data for any machinery
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