Research On Classification And Demand Forecasting Of Spare Parts For Production System Of Steel Enterprise

For steel enterprises, its characteristics are capital intensive and the big input andoutput. Its equipment is usually more than half of the total assets. So how to ensurenormal operation and maintenance of the production system is very necessary. Spareparts management is very important in production system. Therefore, how toreasonable and scientific manage spare parts is an important topic for productionsystem of the iron-steel enterprises. In this paper, classification and demandforecasting of spare parts for production system of steel enterprise is discussed.On the one hand, in view of the defects of common spare parts classificationmethod in the steel enterprises, this paper proposes a standard ABC classification ofthe spare parts based on BP neural network. The difference is to import the concept ofFEMA, and establish the spare parts evaluation system by critical, availability andeconomy.The BP neural network algorithm is used to classify spare parts ofproduction system in steel enterprises.On the other hand, in order to improve the accuracy of spare parts demandprediction of the production system in steel enterprises and reduce the supplyblindness of spare parts, this paper establishes a model based on BP-MC spare partsdemand prediction method. At first, in views of the characteristics of the roll, thispaper analyses the influence factors of roll demand; Then according to the monthlyproduction plan of enterprises, the demand of the12months prior and the monthlyfault time, this paper established the BP-MC model to predict the demand for spareparts.Finally, this article discusses the two methods of empirical research. The resultsshow that: spare parts ABC classification method based on BP neural network is moreComprehensive and objective then the traditional ABC classification method; Spareparts demand prediction method based on BP-MC model has higher accuracy andreliability.