Research And Development Of Milling Database System Based On Ant Colony Neural Nerwork In Preferences Of Cutting

Milling is broadly used for the manufacture of profiled components in aerospace, automotive and mould/die industries. Cutting parameters in Milling are determined usually based on either experience or reference handbooks. How to improve machining efficiency and lower the cost is one of the important tasks explored and studied for a long time by machinists. New methods are needed to rapidly and accurately decide the parameters of a milling operation in designing the machining technology, among which building milling tools' database and providing optimized data is one of the effective methods to improve machining efficiency and lower the cutting cost.The back–propagation (BP) algorithm is the most widely used variation in neural networks. However, it has some shortcomings, such as slow convergent speed and easy convergence to the local minimum points. And the ant colony system is a novel simulated evolutionary algorithm. It has positive feedback, distributed computation, global convergence, and uses a constructive greedy heurism. The paper first analyzes the characteristics of both the ant colony system and artificial neural net (ANN), and realizes a new ant colony system which is based on ANN for choosing cutter parameter. The method has certain level of intelligence. It can improve the computing efficiency of the system and avoid a lot of algorithmic defects of BP.The paper also implements a milling database system based on the algorithm. It characterizes: ability to obtain study samples from experimental data; able to rapidly and reasonably decide cutting speed, feed of a cutting-tool's tooth, cutting depth with the condition of cutting tool, material of work piece, and the required quality; strong self-study ability from operation feedback to refine the database, improve judgment and make it more reasonable.Experiments show that the method proposed in this paper can rapidly and accurately decide cutting parameters of milling,save much time in choosing tools, cut down on labors, thus lower the processing cost. Besides, it overcomes the influence of anthropic factor during tool choice, and brings manufacturing quality under finer control.