Maintenance Personnel Optimization Model of Vehicle Equipment Based on Support Task

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.

Shift Scheduling for Railway Corrective Maintenance Personnel Balancing

“…Lu et al (2021) conducted a study by evaluating the constraints related to work and tasks in order to find the number of personnel who will provide the workforce. Song et al (2021) have developed an integer programming approach to minimize the number of maintenance personnel. Breugem et al (2022) have proposed a linear programming, column generation approach that takes into account the duty costs and the additional duty costs on Dutch urban railways.…”

“…Maintenance duties of train equipment are assigned to personnel (Song et al, 2021). The sequence of tasks reveals the labor costs of maintenance personnel.…”

Analysis and research on electromechanical equipment maintenance based on 3D printing technology

“…Set the screw plasticizing temperature to 160℃, the forming temperature to 175℃, the nozzle diameter to 0.4 mm, and the printing speed to 30 mm/s. Select the floor height of 0.1, 0.2, 0.3, and 0.4mm respectively, and print 10 mm×50 mm×3 mm cuboid model, compare the surface finish of printed samples and the adhesion between layers, and repeat printing, comparison, and recording [6].…”

Application of Decision Tree and Machine Learning in New Energy Vehicle Maintenance Decision Making

“…By introducing machine learning, we have allowed the concept of decision trees to transcend the limitations of human intuition, enabling it to handle data volumes and complexities far beyond the processing capacity of the human brain. They are not only able to make judgments based on existing data but also learn from the data and continuously optimize their own decision rules, which is the irreplaceable significance of decision trees in the real world [10][11][12]. Decision trees also have a place in machine learning because of the interpretability of their models, which is especially important in domains that require a transparent decision-making process [13][14].…”