Study On Network Centric Machining Features Recognition Method

Network centric design and manufacturing is a rising product development mode that has expansive foreground. Based on the demand of network centric design and manufacturing, the thesis focuses on the research on network centric machining features recognition by using divide and conquer strategy, and presents a network centric machining features recognition method as well as develops a validating prototype system.The thesis is organized as follows:Chapter 1 introduces the feature-based CAD/CAM technique and summarizes current status of automated feature recognition; then introduces several representative automated feature recognition system; furthermore, analyzes the demand of network centric design and manufacturing; the chapter ends with the primary research contents and objectives of the thesis.Chapter 2 presents the machining features recognition method by using divide and conquer strategy. The foundation of the method is automated feature recognition algorithm based on minimal condition sub-graph as well as the division strategy adopting. Firstly, a complex part is divided into several blocks; then every decomposed block is recognized; finally, the results of recognition are combined to build the feature model of the complex part. The technique of "shell combination" and "lost faces reconstructing" are discussed in detail.Aiming at the demand of network centric design and manufacturing, chapter 3 introduces the design and implementation of network centric machining features recognition. It includes the design of network centric machining features recognitionprocess and the parallel between network transferring and machining features recognition. Then the procedure of implementing network communication using Winsock is discussed. Finally, the reliability and security of the transferring are analyzed.Chapter 4 is introduces the prototype system of the network centric machining features recognition. The system architecture and partial key data structures are described. Furthermore, the system interface and the concrete operations in network centric machining features recognition are illustrated by examples.The final chapter summarizes the main results and makes conclusions of the thesis. Some future research work is also envisioned.