Research On Material Classification Of Wind-electric Assemble Plant

In the World War II, Materials Management appeared to solve problems raised in the Aviation Industry. It solves materials problems coming from the perspective of the entire company, including coordination of the collaboration between different suppliers, so that the cooperation between the different materials and performance meet the design requirements; provide communicative platforms for different suppliers and between suppliers and corporate department; control of material flow rate and so on. Materials Management can effectively address issues such as conflicts from inventory control and ease the pressure on material costs, so improve production management efficiency.Material classification is a material management basis, and its managerial level largely determines the level of wind power in the assembly and production management and production efficiency, at the same time, materials classification management also involves the selection of vendor classification, procurement, inventory control, materials management and other aspects. Therefore, the efficient management of scientific classification of materials assembled for the wind power business is of great strategic significance. Assembly of the wind power business model and algorithm classification of materials research, paper proposed materials classification model based on Rough Set (RS) and Support Vector Machine (SVM), expected to solve the problem of sample data and excessive indicators. Paper studies the following aspects:First, the paper summarizes domestic current research of material management and material classification, summarizes the main contents of this article and the overall framework, and proposes innovation of this paper.Secondly, research the common ways of materials classification, associated base theory of Rough Sets and Support Vector Machine.Again, build a wind power assembly evaluation index system of enterprise material classification, and put forward the technical train of thought using Rough Set(RS) to reduce attribute and Support Vector Machine(SVM) to classify materials, at first application of rough set attribute reduction redundancy and simplify the training set and test set, designed to reduce the SVM classifier complexity and improve the classification accuracy of SVM classifier. It is a full use of both advanced ability on noise suppression of SVM, but also to make up for the Rough Set to noise-sensitive defects, enhanced classification and anti-jamming capability of fault tolerance. On this basis, the paper establishes the model of material classification based on RS and SVM, and the model solution procedure is described in detail.Finally, based on the theory, the model is applied to an actual engineering company, and the classification results were compared, the results show that materials based on RS and SVM classification model can achieve higher levels of classification accuracy, the model has some engineering applications.