Data Mining Technology In Supply Chain Inventory Control

The key problem to modern enterprises is how to manage fund-flow , materials-flow and information-flow synthetically; how to balance all the resources such as human power, fund, materials, equipments, technology, information and time and how to fully utilize the resources of an enterprise.This thesis explored how to apply data mining technology to the inventory controlling and optimization of supply chain management and designed a data mining prototype system toward the key enterprise of supply chain management in order to discover new knowledge during the course of manufacturing and selling. This can guide the enterprise during routine activities and decrease the cost and increase the producing efficacy.This thesis analyzed the concept of data mining technology, practice situation and development tendency. Then we made comparable analysis on these two open source data mining system and select Weka as the core of this system. According to the character of continuous enterprise in SCM, we announced a clustering approach for high dimensional data and provide the programs of resolving the enterprise inventory model using genetic algorithm.In succession, we pointed out several essential problems of constructing a data warehouse and provide inventory models toward the data warehouse of continuous enterprise. Based on the Model-View-Controller pattern we announced a data mining Prototype System which had a Weka core inside.According to the character of continuous enterprise applying genetic algorithm to resolve the model of assuring the well-balanced production and aiming at minimum raw material cost of enterprise, we showed the usefulness and advantage of data mining technology toward the inventory management of continuous enterprise. Based on the progress we made in this thesis we planed the next steps research work.