Abstract
Vehicle equipment maintenance support tasks have problems such as low maintenance efficiency and unreasonable allocation of maintenance personnel. In order to further strengthen the theoretical research of vehicle equipment maintenance support, an optimization model of vehicle equipment maintenance personnel based on support task is proposed in this paper. Firstly, the maintenance workload model of vehicle equipment is constructed by analyzing the three task sources of vehicle equipment: scheduled maintenance, natural random failure, and combat damage. Then, considering the technical professional level, maintenance efficiency, and other factors of maintenance personnel, two optimization models of maintenance personnel are constructed. In view of the situation where there are enough human resources, the prediction model of the number of personnel with the minimum total number as the goal is constructed to achieve the purpose of saving human resources. Using MATLAB mixed integer nonlinear programming problem (MINP) toolbox to solve the prediction model of the number of personnel, in view of the shortage of maintenance personnel, a maintenance personnel allocation model aiming at minimizing maintenance time is constructed to maximize maintenance efficiency. In order to solve the model, the fruit fly optimization algorithm (FOA) is improved, and the group cooperation is used to update the fruit fly position. The new algorithm not only retains the essential advantages of the FOA but also solves the problem that the algorithm is easy to fall into local extreme value and improves the global optimization ability of the algorithm. Finally, two example simulations verify the effectiveness of the optimization method in this paper and provide a certain theoretical basis for maintenance personnel to optimize decision-making.
Highlights
Entering the twenty-first century, information technology weapons and equipment have gradually developed, hightech weapon ratio has increased, and the corresponding equipment support forces have been changed [1]
In order to improve the support capability of the maintenance support system and give full play to the effectiveness of the existing support resources, the allocation structure of the support force must be optimized and adjusted. e traditional maintenance support resources have a shortage of scientific calculation methods. ey mainly rely on subjective experience, historical data comparison, and other methods and lack the support of quantitative methods, which leads to bad phenomena such as low maintenance efficiency and waste of resources [2]
The current situation of vehicle equipment maintenance support is still difficult to meet the requirements of the new circumstances, and the corresponding theoretical research does not dive deep enough. ere are still some problems in terms of vehicle equipment, such as low maintenance efficiency and unreasonable allocation of maintenance personnel. e optimization of maintenance
Summary
Entering the twenty-first century, information technology weapons and equipment have gradually developed, hightech weapon ratio has increased, and the corresponding equipment support forces have been changed [1]. E contents of the research on the optimization of maintenance support resources are varied, and the methods adopted are different It mainly includes three types: RCPSP (Resource-Constrained Project Scheduling Problem), inventory control of maintenance spare parts, and prediction optimization of maintenance personnel. Literature [11] considers the resource constraints such as personnel, support equipment, workstation space, and replenishment resources and establishes a mathematical model of RSPFDO (robust scheduling problem for flightdeck operation), with the goal of maximizing the probability of completion and minimizing the expected completion time. (3) In order to maximize maintenance efficiency, in view of the shortage of maintenance human resources and the diversity of professional skills, an optimal allocation model of maintenance personnel with the goal of minimizing the cumulative repair time is constructed. (4) e traditional fruit fly optimization algorithm (FOA) is improved by using the location update method of group collaboration, which improves the defect as the algorithm is easy to fall into local extreme value. e simulation results show that the improved FOA has good solution efficiency, and the personnel allocation scheme can effectively shorten the equipment maintenance time
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