基于麻雀搜索算法考虑病患流的医院诊疗设备维护优化研究

针对医院诊疗设备出现故障后对病人的影响不可控、产生的维修费用高等问题，提出了一种基于病患流分布不均的预防性维护决策模型。首先，针对医院诊疗设备退化速度受病患流分布影响的特点，采用病患流因子反映其人流量变化规律，并基于设备衰退演化规则构建了设备退化过程模型。其次，通过将量化的诊疗设备故障风险成本以及延迟或提前维护带来的变动成本纳入成本计算体系，提出了病患流分布不均状况下以故障风险值为约束的设备维护策略。最后，采用麻雀搜索算法进行寻优获取关键初始变量，并对模型进行数值仿真分析，结果表明，新维护策略在保障诊疗设备可靠度的同时，也能保持较低的维护成本。

Maintenance optimization of medical equipment considering patient flow distribution based on the sparrow search algorithm

To solve the problems of uncontrollable impact on patients and high maintenance costs after the failure of hospital diagnosis and treatment equipment, a preventive maintenance decision-making model based on uneven distribution of patient flow was proposed. Firstly, in view of the characteristics of the hospital treatment equipment degradation rate affected by the distribution of patient flow, the patient flow factor was used to reflect the changing law of its human flow, and the equipment degradation process model was constructed based on the equipment degradation evolution rule. Secondly, by incorporating the quantified cost of diagnosis and treatment equipment failure risk and the variable cost caused by delayed or early maintenance into the cost calculation system, an equipment maintenance strategy that constrains the failure risk value under the uneven distribution of patient flow was proposed. Finally, through the sparrow search algorithm (SSA) optimization to obtain the key initial variables, and numerical simulation analysis of the model, the results show that the maintenance strategy proposed in this paper can ensure the reliability of the diagnosis and treatment equipment while maintaining a low maintenance cost.