传统备件管理中的ABC分类法，针对备件消耗量进行预测。传统的备件的AB

The ABC classification method in traditional spare parts management predicts the consumption of spare parts. The traditional ABC classification of spare parts has the characteristic of uncertainty, while the BP fuzzy neural network prediction method is a prediction method specifically aimed at uncertainty. It is a highly nonlinear system with self-learning ability, which can theoretically be Approximate any non-linear function defined in the density with arbitrary accuracy, mainly adopts the neural network-based machine learning method, and establishes the ABC prediction model of spare parts based on the BP fuzzy neural network by determining the network structure and network training. The model comprehensively considers the different effects of various factors that affect the consumption of spare parts on the classification of spare parts, so that the forecast results are more reasonable and more realistic. <br>For companies like D Company with many and complex production equipment, the rationality of its spare parts storage strategy is directly related to the amount of spare parts storage and the effective operation of production equipment. In D company spare parts management

The ABC classification in traditional spare parts management, which predicts spare parts consumption. The traditional ABC classification of spare parts has the characteristics of uncertainty, and BP fuzzy neural network prediction method is a prediction method specifically for uncertainty, it is a highly nonlinear system with self-learning ability, which can theoretically approach any non-linear function defined in the density in any precision, mainly using the machine learning method of neuron network, and establishing the spare parts prediction model based on BP fuzzy neural network by determining network structure and network training. The model takes into account the different effects of various factors affecting spare parts consumption on the classification of spare parts, so as to make the prediction results more reasonable and more realistic.<br>For enterprises with many and complex production equipmentsuch as Company D, the rationality of its spare parts storage strategy is directly related to the amount of spare parts storage and the effective operation of production equipment. In company D spare parts management.

ABC classification method in traditional spare parts management is used to forecast the consumption of spare parts. The traditional ABC classification of spare parts has the characteristics of uncertainty, and BP fuzzy neural network prediction method is a kind of prediction method for uncertainty. It is a highly nonlinear system with self-learning ability. In theory, it can approach any nonlinear function defined on the density at any precision. It mainly adopts the machine learning method based on neural network The ABC prediction model of spare parts based on BP fuzzy neural network is established by determining the network structure and training. The model comprehensively considers the different effects of various factors affecting spare parts consumption on spare parts classification, which makes the prediction results more reasonable and more in line with the reality.<br>For a company like company d with many and complex production equipment, the rationality of its spare parts storage strategy is directly related to the amount of spare parts storage and the effective operation of production equipment. In the spare parts management of D company