租赁设备的状态维修决策建模与优化

随着物联网技术飞速发展,租赁设备大多安装有传感系统,可以及时地对设备关键部件和整体运行状态进行检测,进而可基于设备的健康状态为其安排更为合理的维修方案,在降低租赁商维修费用的同时,尽量少地干预客户的正常施工,并且保证租赁设备在客户施工场所的可靠运行.本文研究了基于状态检测的租赁设备的最优维修问题,研究中引入了顺序状态检测,定义了基于状态的控制限维修策略,并建立了以维修开销最小为目标的解析模型,以决策系统最优的检测间隔和预防维修阈值.除检测、维修等基本费用外,模型中还进一步考虑了租赁系统的故障罚金和故障后维修超时罚金.在模型的求解中,推导了维修干预下设备任意时刻的检测概率和状态概率分布,作为模型构建和求解的依据.数值实验结果验证并表明了面向租赁设备的基于状态的维修策略的有效性.

Optimal decision of condition-based maintenance strategy for leased equipment

With the rapid development of Internet of Things technologies, the sensing systems which can inspect the state of key components even the whole system in time, have been installed on the most leased equipments. To minimize the maintenance cost for the lessor, a more reasonable maintenance scheme should be designed according to the health state of equipment, which can reduce unnecessary inspection and maintenance actions for the lessee. The scheme can also make sure of the reliability of leased equipment in operation as well with a few interruption. In this paper, condition-based inspection and maintenance policy is proposed for leased equipment by using the sequential inspection method. In order to minimize the expected maintenance cost, a mathematic model is derived to determine the optimal inspection cycle and preventive maintenance threshold. Except for the basic costs of inspection and maintenance, the costs of fixed penalty and resulting overtime repair penalty for leased equipment are further considered in the model. To get the solution, the inspection probability and the probability distribution function of states with maintenance intervention are derived for each unit time. Numerical experimental results verified the correction and validation of the presented condition-based maintenance strategy and the corresponding models.