Research And Development Of The Intelligent System To Choose The Milling Parameters

It is an important and implicated work to choose the reasonable machining parameters during the design of the machining process. The key issues are to decide these indexes of the machining quality, productivity, cost and the utilization of equipments. With the application of advanced manufacturing techniques, it increases the importance of planning the reasonable cutting time because the auxiliary time of the process is continuously reduced and the rate of the cutting man-hour and the total man-hour is more outstanding. With the development of the machining method of the.little scraps and no scraps, it is the prominent position in machining operation to choose reasonable milling parameters of, because the rate of the machining die sharing the total cutting man-hour is enlarging and the rate of the milling operation in machining die is rapidly rising. In milling processing, to get the reasonable results and calculate the possible cutting parameters is very difficult in the process of new materials, new methods and new equipments applied to decide the machining parameters. The milling parameters are influenced by many factors, such as a machine tool, a cutting tool, the materials of the work-piece, the quality of the work-piece achieved, the allowed period and the cost to achieve the work-piece. So, a new method is needed to rapidly and accurately decide the milling parameters of amilling operation in designing the machining technology.The system offers a platform to rapidly get the reasonable cutting parameters for milling operations. It has the characteristic that the users can obtain their requirements of machine work-piece according to some owned information and the rationality. It is inevitable to increase the enterprise's competitive ability in market by the reasonable process (period, cost, profit, and so on) to manufacture work-piece according to the choice of the reasonable cutting parameters.Based on the database, the system can rapidly and reasonably decide the cutting speed, the feed of a cutting-tool's tooth, the cutting depth by the condition of cutting tool, material of work piece, and the required quality. The VC++6. 0 is chosed as the platform to develop the system. The database depends on the SQL Sever2000 database. The algorithms are the RGA and BP-RAGA. My main achievements are as follows:1 The optimization of the milling parameters of a milling operation has been developed and the alternate interfaces were developed using the programming method of orient object.2 After the entity-relationship model is converted to the relation model, the design of engineering database of milling parameters has been completed by using the common relation database.3 Based on the effect of the work-piece' s physical mechanical properties to its machinability, the Fuzzy Evaluation method and Fuzzy Cluster method has been used to evaluate and sort the work-pieces.4 Based on the theories of the cutting metal, the study has developed the conditional optimization model by the functions of milling parameter's optimization, the functions of the constraint condition of machine tool, cutting tool, material,etc, and the RGA algorithm.5 The system can realize the intelligent optimization of milling parameters by the artificial neural network using the BP-RAGA algorithm and the continuously refreshing cutting parameters.