Cloud Quotation System For Mold Based On Feature Extraction Method

Mold industry is called the "mother of industry",she is the important foundation of industrial production and manufacturing.The price of the mold is the decisive factor whether the mold design and manufacturing enterprises and their customers can reach a deal,but also the mold design and manufacturing enterprises efficiency,technology and management of the centralized embodiment.With the development of the manufacturing industry,it is obvious that the quotation can no longer meet the market demand by virtue of the personal experience of the quoter of the mold enterprise alone.In the context of Germany's "Industry 4.0" and China's "Smart Manufacturing 2025",it is a practical need to design a new,robust,functional,fast and accurate quotation system by combining advanced computer technology.In this paper,feature recognition technology and cloud technology are applied to mold quotation,and a cloud quotation system based on feature recognition is implemented in NX system.The main work of this paper is as follows.(1)Define the BOM cost database.Based on the study of existing mold quotation methods,the functional and non-functional requirements analysis of the quotation system was carried out in combination with the structural characteristics of mold parts and their impact on the estimation of various types of costs of the parts,and the overall scheme design of the system was completed,and the system data management method based on BOM data table was designed,and the BOM cost database was defined to provide the corresponding specification for the system data management.(2)Define XML feature documents.The key information of mold parts and the method of feature recognition are studied in advance,and a feature recognition method based on the key structural information of mold parts is proposed.The method extracts the key structural features of rounded corner class,hole class and slot class of mold parts based on the feature recognition method based on diagram,and stores them into the feature text in the form of XML document.And the cost is estimated using the example reasoning method to achieve the process of learning from the data by retrieving,correcting and saving.(3)Design and implementation of a mold quotation system for desktop-end and cloud-end.From the actual requirements and overall design of the quotation system,the UI interface of the quotation system was designed in NX system with Block UI Styler and the corresponding functions were written in the functional logic layer to complete the development of the feature recognition-based mold quotation system;the system was tested functionally through a typical mold part and the final quotation was generated to verify the Finally,we designed the UI interface of the web side and deployed the system in Amazon Cloud to achieve the effect of one-stop mold quotation in a simple,efficient and accurate way.This thesis applies feature recognition based on key structure information and cloud technology to mold quotation for the first time,implements a mold quotation system based on feature recognition in NX system,and deploys the system to the cloud,which contains theoretical and application innovations and also provides certain reference value for the subsequent scientific research and development work in the field of mold quotation.