Research And Development Of Cutting Parameter Intelligentized Choosing System

Along with the development of the Numerical Control technology, it is very important to determine reasonable cut parameter when NC processing. What kind of cutting parameter is also an important aspect of mechanical techniques. Whether the cutting parameter is appropriate will directly influence cost, productivity and the quality of product. Since the factor of determining cutting parameter is numerous and mutually restricted, thus determine the best cutting parameter is relatively difficult. Using artificial intelligent technology to determine cutting parameter can raise the intelligence of the NC system and then establish good foundation for CIMS system integrated.Based on the research of engineering database and metal cutting processing principle, author research and develop a set Cutting Parameter Intelligentized Choosing System. This system has certain intelligence and can be used in actual production to guide the cutting parameter determining. The main research contents of this thesis are as follows:1 Based on analyzing task, adopt IDEF method to build mould and build the mould for the overall structure of this system. Furthermore establish each system son- mould structure. Using object oriented method, carry out the design of system program.2 After the research for engineering database, combining this system specific engineering database demand, establish the entity-relationship diagram for cutting parameter engineering database and convert the entity-relationship diagram to relation model. Based on database management system supporting, realize thecutting parameter engineering database structural design and functional requirement.3 Based on Fuzzy theory, adopt Fuzzy Evaluation method to evaluate metal material's machinability according to metal's physical mechanical properties. Adopt Fuzzy Cluster method to sort the material according machinability's similarness. By this way, we can greatly extend the scope of the cutting parameter database's application.4 By studying mechanical optimization method , combining theory of metal cutting processing, summarize the optimization function by the cutting parameter as optimization aim and corresponding restraint condition. Adopt one of optimization methods -compound shape method - to calculate cutting parameter's optimization result.5 Based on studying artificial nerve network theory, establish the nerve network model of cutting parameter. Use Back Propagation algorithm (BP algorithm) as system's nerve network learning method. System has realized cutting parameter nerve network intelligentized choosing function. Realize the intelligence of systemin some degree. This method has certain advance and theoretical meaning.In conclusion, this thesis has certain practicality and advance.