We propose a maintenance policy for new equipment on a repair-refund maintenance strategy in this paper and derive the optimal lease period from the lessor’s perspective based on independent and identical distribution of historical failure data which obey power law process. The cost model of a full refund and a proportional refund is studied, and the corresponding optimal leasing period is determined by reducing the expected total cost rate to the largest extent. We use a numerical example to illustrate the proposed cost model and analyze the sensitivity of related parameters. Furthermore, we show that the proportional refund policy is preferable than a full refund to the lessor. Finally, according to the simulation outcome, the proposed methods are effective and instructions for lessor in regard to equipment lease are provided.
Based on the analysis of traditional state maintenance strategy and big data-based state maintenance strategy, this paper builds a transformer state duration simulation model based on Monte Carlo method and builds an annual cost model based on the running state of the transformer. Finally, a typical case is selected to simulate a time series of 8760 hours of transformer operation under two operational inspection strategies, and the annual cost is calculated separately. The example shows that the annual cost of the transformer is lower under the big data-based inspection strategy.
The maintenance tasks in present studies for the maintenance optimization of multi-component systems are mostly simplex, while the compound maintenance that integrates several kinds of maintenance types existing in practice are seldom studied. To optimize the compound maintenance intervals of multi-component systems, the group maintenance strategy was introduced in this paper, the maintenance cost structure and composition were analyzed from system point of view, and the mathematical models were established for expected maintenance cost per unit time. Finally, a numerical example was illustrated to prove the validity of the strategy and models above.
This paper proposes a novel Reliability Associated Cost (RAC) model for machine tools throughout its lifetime that considers two different failure consequences, immediate failure and product rejections increase failure. A maintenance strategy of corrective maintenance combined with overhaul utilized to the maintenance activities of machine tools in the current paper. Markov reward approach is developed for computing of the costs incurred by both failure consequences and maintenance activities and system average availability throughout the machine tools life cycle. The Genetic Algorithm is used to find the optimal repair rates layout and overhaul moments that provide a minimal expected cost of system operation and maintenance actions and satisfies the desired availability requirement. A numerical example is presented in order to illustrate the approach and the results show that the proposed technique can significantly cut the RAC for machine tools.
Cost Comparison Based on Transformer Operating State Under Two Kinds of Inspection Strategies
