Research Of Drawing And Document Management Of Mechanical Manufacturing Enterprise In Web-based Pdm System

CAX (CAD, CAPP, CAM, and CAE) technology applied in mechanical manufacturing enterprise widespreadly has greatly improved the ability of enterprises' research and development. At the same time, enterprise produces lots of design data and documentation in the design and production process, how to better manage these design data and technology documentation is a problem to be urgently solved. As the base of manufacturing enterprise' information integration, Product Data Management (PDM) system manages all the information and design processes which correlated to the products, in order to improve the quality and efficiency of the products design. Drawing and document management is an important part of the PDM, but also is one of the basic function of PDM system. It is mainly used to manage the data and information which comes from design process.In order to improve the level of processing drawing and document, fully meet the product functional requirement such as inquiry, browse, upload and download of drawing and document, safety management, information sharing and version control, this thesis adopts the B/S structure, ASP.NET and Microsoft SQL Server 2000 to design and realize drawing and document management module of Web-based PDM system which is appropriate for medium-and small-sized mechanical manufacturing enterprise.Firstly, this thesis analyses the present situation of drawing and document management in mechanical manufacturing enterprise, analyses the problems of drawing and document management of traditional PDM system, discusses the limitations of traditional PDM system and advantages of drawing and document management in web-based PDM system. According to modeling features of PDM system, this thesis uses object-oriented modeling method, introduces the classic object-oriented modeling language-UML and its static and dynamic modeling mechanism, builds model for the object of users, drawing and document, product structure and file dynamic model, which involving drawing and document management of PDM system, completes structured and functional analysis and safety design of drawing and document management module.Secondly, according to analyzing the importance and difficulty of automatic extraction in form-information of electronic engineering drawing and document, this thesis summarizes the method and its shortcomings of automatic extraction in form-information, proposes the automatic extraction method based on the DWGdirectX control, explains the detailed extracting process of DWG files' form-information, gives testing process, result and analysis of performance, and then gets the keywords so as to realize the automatic upload of electronic engineering drawing.Thirdly, Based on the characteristic of correlation of graphics' geometry elements of electronic engineering drawing, after parameter structure is built and data code compression and data encryption are put in practice and at the same time by using BP algorithm of artificial neural network, and later were decrypted. High efficiency and safety transmission of complex engineering graphics data is realized and an example is given.Finally, this thesis analyzes the Web technology which was used in developed system, which can realize drawing and document management; selects database and its access method, researches automatic generation technology of the product structure adopts and develops control to realize the browse and notation of two or three dimensional electronic image. Based on Q34 series of products-Roller Type Abrator which is produced by Qingdao Foundry Machinery Group Company, this thesis designs and realizes the module of examine and approve, modify, upload, download, delete, browse, notate, version management of drawing and document.Among them, management module of drawing realizes automatic extraction in drawing' form-information. It realizes compression, encryption and decryption of electronic engineering drawing by using BP algorithm of artificial neural network in the safe transport process.