基于模糊神经网络的备品备件一致性控制法

Consistent control method for spare part based on fuzzy neural network

提出了一个基于经济优化的故障件返修/替换决策算法,并基于它提出了一个备品备件基于经济优化的采购周期和需求量算法。基于器件模糊级别,提出了一个基于性能优化的定购点和采购量算法。建立了一个KSS来提供算法所需要的统计参数,建立了一个神经网络来定义算法的自适应调节常量。提出了一个库存控制法的评估模型,并利用它和"3A"控制法比较,评估结果验证了本文提出的控制法可以克服"3A"控制法存在的缺点。

A priority-economic repair/substitution decision-making algorithm for a fault part is presented,and based on it,the order cycle algorithm and the requirement algorithm are introduced targeting to priority-economic.Based on fuzzy class,an order point algorithm and an order quantity algorithm are putted forward targeted to priority-performance.A KSS and a neural network are introduced to provide the statistic parameters and the adaptable constant parameters for all algorithms.An evaluation method is introduced for inventory control method,and through it,＂3A＂ control method and the consistent control method are evaluated,the evaluation results verify that it can resolve the disadvantages of ＂3A＂ control method.