Reliability-Centered Maintenance of Rapier Dragline for Optimizing Replacement Interval of Dragline Components

Abstract

Machine manufacturers’ recommendations on maintenance strategies of capital-intensive draglines are not always based on real data and therefore lead to losses from downtime. This paper proposes a preventive maintenance strategy for a dragline deployed in an opencast coal mine based on reliability-centered maintenance and failure-mode-effects analysis using real operational data. Reliability-centered maintenance replaced a cluster of critical failure components of the dragline while satisfying two specific conditions: (i) the components should be replaced at the earliest mean time to failure (MTTF) within the group and (ii) the time taken to replace all the parts should be equivalent to the maximum downtime within the group. Estimated threshold weightage factor identified twenty-six critical failure components for the preventive maintenance strategy, and clustering of components divided them into nine groups. In a group, the loss that is expected to occur by replacing some of the components before their failure, and the gain by reducing the overall maintenance downtime, has been explained through a cost-benefit analysis. The total net profit generated is calculated as US$200,178. This clustering activity also led to a reduction of annual downtime by 231 h, whose approximate market price as equivalent coal production costs $295,365.

Appendices

Appendix 1

Fig. A1

Weibull probability density function along with the histograms of various failure components of dragline

Appendix 2

Let us discuss the group i combination of replacement of tooth adapter and tooth tip simultaneously. In this group, both tooth adapter and tooth tip must be replaced at an interval of 201 h. It takes a total time of 1.44 h to replace both parts. Comparing to the original downtime by individual replacement of components, the reduction in downtime by RCM approach is as follows:

$$\mathrm{Reduction}\ \mathrm{in}\ \mathrm{downtime}= Dt-D\max =2.41-1.44=0.97.$$

Since, the components of the group must be replaced at the MTTF of tooth adapter at 201 h, though MTTF of tooth tip is 301 h, their average frequency of replacement is 26 times per year. By using Eq. (5), the hourly revenue generated by the dragline was calculated as $1279. Overall profit generated for each replacement is $1196. This value refers to the difference of product of reduction in downtime and hourly revenue generated by dragline, $1245 and the loss because of the earlier replacement of tooth tip, $49. Therefore, yearly profit for group i accounts for $31,096 (refer to Table 5).

Let us consider another group, for example, group iv making up the replacement of five components simultaneously. In this group, five components belonging to one cluster are the lower dump socket pin, hitch chain shackle, swing oil pump motor, motor armature, and blow motor. All these five components should be replaced at 1818 h. It takes a maximum time of 29 h to replace all components. Comparing to the original downtime by individual replacement of components, the reduction in downtime by RCM approach is as follows:

$$\mathrm{Reduction}\ \mathrm{in}\ \mathrm{downtime}= Dt-D\max =\left(1.61+3.00+4.1+29.02+4.91\right)-29.02=13.62\mathrm{h}.$$

Since the components of the group must be replaced at the MTTF of lower dump socket pin at 1818 h, their average frequency of replacement is 3 per year. Hence, gain in each replacement activity is $17,420. On the other hand, loss in each replacement because of the earlier replacement of components is $11,446. Therefore, net profit per replacement now becomes $5974, that leads to an overall net profit of group v as $17,922 annually. Similarly, it was calculated for the remaining groups and is mentioned in Table 5. The annual net profit was calculated as $200,178.