Echelon usage is an important usage and control method for double-life equipment considering calendar life, which can improve the utilization rate of equipment life and give full play to the economic benefits of the equipment. However, the life indicator considered by the most common echelon usage method is single, and most methods evaluate the echelon usage through the echelon uniformity of working life. The conclusions obtained are limited for the usage and control of double-life equipment, so it is necessary to study the life evaluation method considering calendar life. In this paper, by analyzing the life consumption law of double-life equipment, the recursive method is used to calculate the controllable life range in the process of echelon usage. The evaluation method of working life distribution considering calendar life is proposed. The equipment life reserve is evaluated according to the unit task quantity of the equipment. The results show that the new method can quickly analyze the equipment beyond the usage and control range, evaluate the distribution of working life more accurately, reflect the shortage of equipment reserve life, and has guiding significance for the usage and control of equipment.
Optimizing the aircraft equipment usage scheme of different units according to their task intensity has great significance in improving aircraft reliability and health management. This paper studied the modeling and solving methods of the rotation and echelon usage problems of aircraft equipment measured by dual-life indexes, one of which cannot be controlled. In order to maximize the waste rate of the rotation quantity, echelon uniformity index, life matching index and life utilization index, a decision-making model of the equipment rotation and echelon usage problem under uncertainty was constructed, and an improved NSGA-III with a variable length chromosome was proposed. An improved segmented coding method and operators were proposed, and the repeated individual control mechanism was used to improve the population diversity. When the scale of the problem was large, this method could search a wider range in a short time and obtain more feasible solutions, which verified the feasibility of this method.
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