Development Of Machining Database System For Difficult-to-cut Materials

Because of ultra-high strength, high hardness, high toughness, high temperature resistance and corrosion resistance, difficult-to-cut materials such as titanium alloy and superalloy are widely used in the aviation industry. CNC machine tools, machining centers and flexible manufacturing system are more widely applied in the cutting processing of difficult-to-cut materials. And CAM programming and CAPP planning involved the selection of the tools and cutting parameters. It's general that selecting cutting parameters is based on the experience of actual processing in China. This has led to unstandardized cutting parameters and inefficient processing. So how to select cutting parameters has become the primary problem for the application of difficult-to-cut materials.Cutting database technology developed based on current demand. In this paper, difficult-to-cut materials database system is studied both in theory and in practice. Based on the theoretical models, a B/S mode difficult-to-cut materials database system is developed. In the development process, the workpiece material database, tool database, tool-workpiece matching database and cutting fluid database, etc. are established. The cutting data optimization and process parameters prediction are aslo realized. Case-base for turning, milling, drilling, boring are builed. And hybrid reasoning which based on rule-based reasoning and case-based reasoning is also realized. Finally a practical difficult-to-cut materials database system is developed. The database system is used in selecting cutting tool and cutting parameters which is adapted to difficult-to-cut materials.Cutting parameters are very important for cutting process. In this paper, a mathematical model to optimize cutting parameters is developed through establishing the objective functions which meet specific constraints form minimum production cost and maximum productivity. From the perspective of production management, the effects of the labor intensity of workers and machine tool consumption per unit time to the cutting parameters are analyzed. The case studies of the cutting examples are given.Tool life, surface roughness, cutting force and other process parameters in the cutting process also has an important role in cutting process. Process parameters are predicted on the basis of the collection of test data using empirical formula method.The realization of hybrid reasoning with case-based reasoning and rule-based reasoning make difficult-to-cut materials database system intelligent. By analyzing case coding, case retrieval and case modify, a specific realization method is proposed. Rule-based reasoning works when an instance of reasoning does not exist or to validating the solutions.This topic receives funding from the Chinese Postdoctoral Science Foundation (20070420208), Shandong Province, a special innovative projects post-doctoral funding (200702023), National Science and Technology Support Program key projects (2008BAF32B01 and 2008BAF32B11) and Mega-project of High-grade NC Machine Tools and Basic. Manufacturing. Equipment (2009ZX04014-043).