Knowledge Extraction And Application Of Production Manufacturing Information

With wide applications of Enterprise Manufacturing Information System (EMIS), the process data in a developing enterprise are becoming more and more, and the homologous problems expose out gradually. In the past, the questions that the enterprises met were that there were insufficient data or the data could not be provided enough in time for the management. After the enterprises adopt the manufacturing information system, however, the enterprises data are increasing violently with the growth of time. As a result, except for the normal statistical data, a great deal of historical data and knowledge are put off. Therefore, the data maintenance is much more difficult then ever, the enterprise data could not be effectively used. Moreover, the enterprise often fails to discover and extract potential knowledge from the large deal of the enterprise data for its decision-making process.Association Rule (AR) algorithm is one of effective approaches for discovering the relationships between different data properties in a great deal of complicated data. At the same time this algorithm still lacks the concrete applications in the manufacturing information system, and its operating efficiency is very low. Therefore, it is becoming the key problem in the application process to transform the calculating results to well-organized knowledge for further applications.In this dissertation, by means of the multi-agent theory, the process of discovering knowledge is divided as the task dispatching agent, the mining agent and the categorizing agent. With the high performance of multi-agents, this new approach can obtain a higher operating efficiency than before, the management and utilization of the enterprise knowledge be integrated into the system, and thus the applied integration of the detection and the management for the enterprise manufacturing knowledge can be also carried out.The purpose of the dissertation is to build up a set of comprehensive analytical applied systems of knowledge according to the manufacturing information system. Throughout analyzing a great deal of historical data of the enterprise, the valid data adopted in the enterprise of the manufacturing information system can be made...