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Spare Parts Inventory Control Considering Stochastic Growth Of An Installed Base

机译:考虑已安装基础的随机增长的备件库存控制

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摘要

Installed base is a measure describing the number of units of a particular system actually in use. To maintain the performance of the installed units, spare parts inventory control is extremely important and becomes very challenging when the installed base changes over time. This problem is often encountered when a manufacturer starts to deliver a new product to customers and agrees to provide spare parts to replace failed units in the future. To cope with the resulting non-stationary stochastic maintenance demand, a spare parts control strategy needs to be carefully developed. The goal is to ensure that timely replacements can be provided to customers while minimizing the overall cost for spare parts inventory control. This paper provides a model for the aggregate maintenance demand generated by a product whose installed base grows according to a homogeneous Poisson process. Under a special case where the product's failure time follows the exponential distribution, the closed form solutions for the mean and variance of the aggregate maintenance demand are obtained. Based on the model, a dynamic (Q, r) restocking policy is formulated and solved using a multi-resolution approach. Two numerical examples are provided to demonstrate the application of the proposed method in controlling spare parts inventory under a service level constraint. Simulation is utilized to explore the effectiveness of the multi-resolution approach.
机译:已安装数量是描述实际使用的特定系统的单元数的度量。为了保持已安装单元的性能,备件库存控制非常重要,并且当已安装的基础随时间变化时,变得非常具有挑战性。当制造商开始向客户交付新产品并同意提供备件以替换有故障的设备时,通常会遇到此问题。为了应对由此产生的非平稳随机维护需求,需要仔细制定备件控制策略。目的是确保可以及时为客户提供替换产品,同时最大程度地减少备件库存控制的总成本。本文提供了一种产品的总维护需求模型,该产品的安装量根据均匀的Poisson过程而增长。在产品的故障时间遵循指数分布的特殊情况下,可以获得总维护需求的均值和方差的闭合形式解。基于该模型,制定了动态(Q,r)库存策略,并使用多分辨率方法进行求解。提供了两个数值示例,以演示该方法在服务水平约束下控制备件库存的应用。利用仿真来探索多分辨率方法的有效性。

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