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- W4233178477 abstract "Unreasonable maintenance strategy will increase maintenance cost and reduce the efficiency of CNC (Computer Numerical Control) machine tools. Therefore, not only the degradation state of components but also their coupling effect should be considered to obtain a scientific and reasonable system-level maintenance strategy because of the dependence among different components of CNC machine tools. This study proposes a group maintenance strategy of CNC machine tools considering economic dependence, structural dependence, and stochastic dependence among critical components and optimizes the group maintenance strategy. The model of group maintenance of CNC machine tools is composed of four sub-models: sub-model of component degression, sub-model of group maintenance decision, sub-model of imperfect maintenance, sub-model of maintenance cost. Utilizing the model of group maintenance of CNC machine tools, the time, objectives, and measure of maintenance can be decided according to the degression state and failures of components. And then, the cost of each maintenance can be calculated. In the group maintenance model, economic dependence and structural dependence among components are quantified by cost, while stochastic dependence is quantified by failure intensity. On that basis, the Monte Carlo method is used to simulate the machine tool operation process, and the long-term maintenance cost of CNC machine tools corresponding to a certain failure intensity threshold is calculated. Finally, genetic algorithm is used to optimize the failure intensity thresholds of preventive maintenance and group maintenance. A numerical example verifies the effectiveness of the proposed optimization method for the group maintenance strategy." @default.
- W4233178477 created "2022-05-12" @default.
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- W4233178477 date "2021-07-27" @default.
- W4233178477 modified "2023-09-27" @default.
- W4233178477 title "Group maintenance strategy of CNC machine tools considering three kinds of maintenance dependence and its optimization" @default.
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- W4233178477 doi "https://doi.org/10.1007/s00170-021-07752-6" @default.
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