Simulation Research on Equipment Battlefield Repair Based on ExtendSim Platform

doi:10.3969/j.issn.1009-086x.2025.03.022

Abstract

Abstract:

This paper constructs a simulation model for the equipment battlefield repair process under the ExtendSim simulation platform to study the impact of various maintenance support resource elements in the equipment battlefield repair process. A conceptual model of the equipment battlefield repair process was constructed； the modeling boundary was analyzed and a simulation model based on ExtendSim was constructed. On this basis， simulation was conducted on the battlefield repair process of equipment. Through analysis， it is believed that under certain simulation conditions， there is an optimal number of testing personnel and equipment， which results in relatively stable equipment utilization， support personnel utilization， task waiting time， and average task completion time， without consuming excessive maintenance resources. When the number of inspection personnel and equipment is too small， the simulation system runs extremely unstable， sometimes even unable to complete the simulation process. Conversely， an excessive number of inspection personnel and equipment does not significantly improve maintenance efficiency. The impact of equipment heavy-damage rates on the repair process is also studied. The research results of this article aim to provide technical support for the organizational decision-making process of equipment battlefield repair.

Key words: ExtendSim, battlefield repair simulation, equipment utilization rate, support personnel utilization rate, task waiting time, average task completion time

摘要：

为研究装备战场抢修过程中各维修保障资源要素的影响，构建了在ExtendSim仿真平台下装备战场抢修过程仿真模型。构建了装备战场抢修过程的概念模型；分析了建模边界，构建了基于ExtendSim的仿真模型。在此基础上，对装备战场抢修过程进行了仿真；通过分析认为，在一定仿真条件设定下，检测人员和检测设备有一个最优数量，此时设备利用率、保障人员利用率、任务等待时间和平均任务完成时间是相对稳定的，且无需消耗过多的维修资源。在检测人员和检测设备的数量过少时，仿真系统运行极不稳定，有时甚至无法完成仿真流程；而检测人员和检测设备的数量过多反而没有带来保障效率大幅提高。研究了装备重损率对抢修过程的影响，研究成果可对装备战场抢修过程组织决策提供技术手段支撑。

关键词: ExtendSim, 战场抢修仿真, 设备利用率, 保障人员利用率, 任务等待时间, 平均任务完成时间

CLC Number:

TP391.9

Xuguang TIAN, Longtao WU, Chengming ZHANG, Qinwen ZUO, Ning LIU. Simulation Research on Equipment Battlefield Repair Based on ExtendSim Platform[J]. Modern Defense Technology, 2025, 53(3): 191-199.

田旭光, 吴龙涛, 张成名, 左钦文, 刘宁. 基于ExtendSim平台的装备战场抢修仿真研究[J]. 现代防御技术, 2025, 53(3): 191-199.

Figures/Tables 15

Table 1 Operations of equipment battlefield repair

修理

撤收

换件/修复/后送

结束

Fig. 1 Status transition of equipment repair operation

Table 2 Entities of equipment battlefield repair

抢修行动	属性	功能
装备	部件列表	被修复对象
备件	备件标准	修复装备
设备人员	设备标准修复能力	修复装备执行修复
打击实体		触发修复事件

Fig. 2 Relationship between entities in equipment repair operation

Fig. 3 Main process of battlefield emergency repair

Fig. 4 Generation and distribution model of damaged parts of equipment

Fig. 5 Equipment inspection and repair process

Fig. 6 Equipment detection and emergency repair process model

Table 3 Simulation initial parameter settings

保障资源设置情况

检测设备（台）

保障人员（人）

部件检测时间延迟/h

部件维修时间延迟

0.1~0.3之间的均匀分布

根据每个部件的数据设置

Table 4 Simulation process parameter settings

仿真目标	参数设置	仿真运行次数
检测设备利用率	检测设备数量［1，10］整数	200/1 000
保障人员利用率	保障人员数量［1，10］整数	200/1 000
平均任务等待时间	检测设备数量［1，10］整数保障人员数量［1，10］整数	200/1 000
平均任务完成时间	检测设备数量［1，10］整数保障人员数量［1，10］整数	200/1 000

Fig. 7 Relationship between the utilization rate of the detection equipment and the number

Fig. 8 Relationship between the utilization rate of support personnel and the number

Fig. 9 Relationship between task waiting time and the number of support personnel

Fig. 10 Relationship between task waiting time and the number of detection devices

Fig. 11 Impact of equipment damage rate on the repair

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