Application Of Data Warehouse Technology And Data Mining Method On Failure Diagnosis Of Hydraulic Press

As 20th century is a knowledge economy age, enterprise management is transferring from material management to knowledge management. The age of pure financial capital or material resource acting as living and developing capital of enterprise gone for ever, knowledge management became new management style for enterprise, it is a most important problem for modern enterprise to manage knowledge effectively and utilize capital flow, material flow, talent flow and knowledge flow flexibly.In manufacturing enterprises process knowledge (PK) exists through the full life cycle of product planning, design, management, assemble and service and it decides the living and developing of enterprises. Process knowledge management (PKM) has become a fundamental and key work in enterprises.The whole thesis is centered on process knowledge data warehouse and deeply researches the framework of process management data warehouse and data dig mining. It includes the following parts:1. PK information model and storage technology under data-warehouse is researched. An enterprise level PK data-warehouse which employees the combination of snow modeland star model is constructed. Some data marts are framed as required for data analysis and data mining. This method can increase retrieval speed greatly and save storage space.2. The application of data mining in PKM is researched.In this thesis, grey association analysis method and GM forecasting is used to mine PK of some model hydraulic press, and get the math model and forecasting model. It is very important to guide the using, maintenance and after-sale service of hydraulic press.The system has such functions module as PK collecting, PK inquiry, PK inducting, PK reasoning, after-sale service and so on employing above research results, and has PK data mining function to help the enterprise make it clear and locate its developing direction.