کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1133375 | 1489073 | 2016 | 13 صفحه PDF | دانلود رایگان |
• Remaining useful life (RUL) is predicted considering stochastic dependence.
• Model the degradation level of some components effect on the RUL of other component.
• An dynamic opportunistic maintenance decision is presented based on the RUL.
• The trade-off between reducing the RUL and the set-up cost is considered.
• The strategy is adaptive through updating maintenance zone and grouping structure.
This paper presents a dynamic opportunistic condition-based maintenance strategy for multi-component systems. The strategy is based on real-time predictions of the remaining useful life under the simultaneous consideration of economic and stochastic dependence. First, the effect of a component’s degradation level on the remaining useful life of other components is considered. The remaining useful life of components that have a stochastic dependence on one another is predicted using stochastic filtering theory. Given the condition monitoring history data, we model the effect of a component’s degradation level on the remaining useful life of other components. And a penalty cost evaluates the additional cost of shifting the maintenance time. This allows us to determine the optimal trade-off between reducing the remaining useful life of some components and decreasing the set-up cost of maintenance. An optimization model is then established by choosing the dynamic opportunistic maintenance zone and optimal group structure that minimizes the long-term average maintenance cost of the system. A numerical example including three multi-component systems is presented. The results show that our proposed method maximizes production efficiency on the premise of ensuring system reliability, and reduces the system operation and maintenance costs.
Journal: Computers & Industrial Engineering - Volume 93, March 2016, Pages 192–204