舰炮武器装备智能化维修保障研究

Study on intelligent maintenance and support of naval gun weapons

舰炮是水面舰艇装备数量最多、使用最频繁的武器装备,以往以预防性维修为主、临抢修为辅的维修方式,容易同时出现“维修不足”和“维修过剩”等现象,导致维修成本居高不下。以智能化战争时代精益管理需求为牵引,提出了一种基于维修资源视情供应的舰炮武器装备智能化维修保障体系,并建立了以保障周期最短、保障成本最低为目标的区域舰炮武器装备器材调剂供应的优化决策模型,引入了离散化海鸥算法(seagull optimization algorithm,SOA)进行求解,仿真结果表明:该模型算法可有效提供优化的供应方案,并在收敛速度和寻优效果方面有一定优势。

With the largest number in use among all weapon equipment,naval guns are the most frequently used on surface ships.In the past,preventive maintenance was the main maintenance method,supplemented by emergency repair.As a result,“insufficient maintenance” and “excess maintenance” are prone to occur at the same time,which leads to high maintenance costs.Based on the demand of lean management in the era of intelligent warfare,this study proposes an intelligent maintenance and support system for naval gun weapon equipment based on the situational supply of maintenance resources,and establishes an optimization decision-making model for the allocation supply of regional naval gun weapon equipment with the goal of the shortest support period and the lowest support cost.The discrete Seagull Optimization Algorithm(SOA) is introduced to solve the problem.The simulation results show that the model algorithm can effectively provide an optimized supply scheme,which has certain advantages in convergence speed and optimization effect.