不确定环境下复杂机械装配系统设备维修方法

为保障不确定环境下复杂机械装配系统的连续性并降低其维修成本，提出一种以马尔可夫决策理论为基础的设备维修策略动态选择方法。在综合考虑系统运行成本、缓冲库存成本、设备维修成本及停机损失成本的基础上，构建了装配系统可靠性成本模型。该模型以带有中间缓冲区的二级装配系统为研究对象，以设备状态和缓冲库存量为自变量，以可靠性成本为目标函数。分析了装配系统的不同运行状态，利用模拟退火算法和模糊非线性混合整数目标规划对可靠性成本模型求解，制定装配系统最优维修方法。该方法降低了装配系统停机时间，减少了设备维修次数，可为生产线设计和维修计划的制定提供依据。最后，通过算例分析验证了模型的有效性和可行性。

Equipment Maintenance Method of a Complex Mechanical Assembly System under Uncertain Environment

To guarantee continuity and decrease maintenance cost of a complex mechanical assembly system under uncertain environment, a dynamic selection method of maintenance policy based on Markov decision is put forward. On the basis of the comprehensive consideration to the cost of operating, inventory, maintenance and the cost due to the lost production, a reliability-cost model is established. The model takes the secondary production system as the research object, equipment condition and the buffer inventory as independent variables, and reliability-cost as objective function. The best maintenance policy in different conditions of production system is derived by simulated annealing algorithm and fuzzy nonlinear programming. The method decreases downtime, reduces equipment maintenance frequency, and provides basis for designing the production line and scheduling the maintenance plan. The calculation analysis of samples proves the effectiveness of the model.