Spare parts inventory management with demand lead times and rationing

We study an inventory system that consists of two demand classes. The orders in the first class need to be satisfied immediately, whereas the orders in the second class are to be filled in a given demand lead time. The two classes are also of different criticality. For this system, we propose a policy that rations the non-critical orders. Under a one-for-one replenishment policy with backordering and for Poisson demand arrivals for both classes, we first derive expressions for the service levels of both classes. The service level for the critical class is an approximation, whereas the service level for the non-critical class is exact. We then conduct a computational study to show that our approximation works reasonably, the benefits of rationing can be substantial, and the incorporation of demand lead time provides more value when the demand class with demand lead time is the critical class. The research is motivated by the spare parts service system of a major capital equipment manufacturer that faces two types of demand. For this company, the critical down orders need to be satisfied immediately, while the less critical maintenance orders can be satisfied after a fixed demand lead time. We conduct a case study with 64 representative parts and show that significant savings (as much as 14% on inventory on hand) are possible through incorporation of demand lead times and rationing.     

Discrete-time spare ordering policy with randomized lead times and discounting

The paper considers a generalized discrete‐time order‐replacement model for a single unit system, which is subject to random failure when in operation. Two types of discrete randomized lead times are considered for a spare unit; one is for regular (preventive) order and another is for expedited (emergency) order. The model is formulated based on the discounted cost criterion. The underlying two‐dimensional optimization problem is reduced to a simple one‐dimensional one and then the optimal ordering policy for the spare unit is characterized under two extreme conditions: (i) unlimited inventory time and (ii) zero inventory time for the spare unit. A numerical example is used to determine the optimal spare‐ordering policy numerically and to examine the sensitivity of the model parameters.     

一些两段式煤气发生炉运行情况分析

两段式发生炉具有产生煤气热值较高，生产能力较大，稳定性较好等优点，目前在一些大中型企业运行良好。本文总结了一些两段炉操作运行情况，也指出了存在的一些问题，诸如煤气脱硫处理不当、停炉停产检修需调整以及应用计算机自动控制方面等问题有待于解决，最后提出一些建议。     

在备件招标采购中运用"定质比价法"初探

针对公司在备件采购中存在的质量、价格等问题，探讨了如何使用“定质比价法”这一新的招标采购方法来提高备件质量、降低成本。     

改进BP网络在航材需求预测中的应用

针对航材备件需求预测问题,在对影响航材备件需求量的多个因素进行分析研究的基础上,运用改进BP神经网络算法进行预测的仿真实验。实验结果表明,改进BP神经网络能够对积累的历史数据进行充分的应用,并且有较高的预测准确性。     

面向动用计划的车辆装备备件预测研究

针对动用计划下的车辆装备备件的消耗特点,研究了车辆装备维修备件消耗量和库存控制两个预测优化问题。考虑动用计划期内车辆装备的预防性维修和修复性维修,实现定时定程维修和自然随机故障维修下装备维修备件的消耗量的预测。在此基础上,根据备件库存检查方式的特点,建立基于定期检查策略的联合补货库存控制模型,根据模型的结构特点确定决策变量界限,并利用多类种群位置更新方式改进了果蝇优化算法。仿真结果表明,改进的果蝇优化算法具有良好的求解效率,本文所提出的优化方法可为车辆维修保障资源优化提供决策依据。     

平均保障延误时间（MLDT）建模方法研究

针对现代装备系统的精确化保障要求,对装备保障的主要参数指标MLDT进行了建模分析,主要分析了三种计算方法：图估法、解析法和基于排队论的MLDT建模理论,解决了评估MLDT指标时的定量计算问题。     

不常用备件基于AHP的ABC分类模型

分析了传统ABC分类法在不常用备件库存分类中的应用,针对传统ABC分类法的缺陷.文章应用基于AHP的ABC分类方法,将备件单价、采购提前期、年采购费用、年使用次数、备件类型、重要性等级作为分类准则,对每一备件相对准则层进行ABC分类,然后结合准则层对目标层的权重计算备件组合权重并再次进行ABC分类,建立了不常用备件基于...     

成组更换策略下的备件库存决策仿真研究

针对成组更换策略下备件需求的特点,建立了无限使用期的成组更换策略与备件库存控制联合优化仿真模型。该模型通过模拟系统在预防维修间隔期T内的维修活动,得到1个预防维修间隔期内的总费用,然后在系统运行M(M足够大)个周期下,以期望单位时间总费用最小为目标,优化预防维修间隔期T和最大库存水平S。最后,基于案例,运用MATLAB对模型进行仿真优化计算,并分析了相关参数对模型优化结果的影响。     

IP/MPLS over WDM网络生存性的研究

该文首先分析了IP/MPLS over WDM网络单层生存性和多层联合生存性,并就生存性策略的性能进行对比,然后对多层空闲资源分配进行了研究。