Research On Intelligent Design System For Aluminum Extrusion And The Key Technologies

Aluminum profile parts, with the advantages of lightweight, high strength, good workability and anticorrosion, are widely used in aircraft, automotive and decoration. Extrusion is the dominating manufacturing method of aluminum profiles. At present, most domestic factories that manufacture aluminum profiles still adopt traditional method in the design and manufacturing. The process and mould design mainly depend on experience, and the fabrication of mould needs trial-and-error tests, which results in low efficiency, high cost and long developing period. Moreover, the product quality cannot be guaranteed. Short developing period, high quality and low cost are the three key elements for the competition in the global manufacturing market in 21st century. The ability of product innovation is the most important factor for coping with the competition. The innovation ability is resulted from effective knowledge supply and the driving of high-tech, which are based on the research and development of new theoretical system and corresponding key technology.In present study, Knowledge-based Engineering is introduced into die design of aluminum profile extrusion. In the framework of knowledge-based intelligent design system of aluminum profile extrusion, the intelligent design method is studied. The finite element method and finite volume method are compared, and a FVM multi-stage simulation method is put forward. A die bearing optimization method based on numerical simulation and artificial intelligence is also proposed.The production status of aluminum profile extrusion is analyzed and the state-of-art of corresponding research is summarized. In the framework of advanced manufacture technology and theory of product design innovation, the evolution of intelligence technology is studied. The establishment, evolution and application of KBE are introduced. Then a viewpoint is pointed out that introduction of KBE into die design of aluminum extrusion is an effective way to improve the designintelligence and innovation.A deep research on KBE technology is carried out. The definition and connotation of KBE are given. The difference between KBE and expert system is analyzed from the aspects of geometrical applicability, knowledge-based modeling, knowledge management and self-studying. Several key technologies of KBE, knowledge expression, knowledge reasoning, knowledge acquisition and multiplying, are studied.The methods of constructing feature models for aluminum profile and the key elements of die design are developed. Knowledge framework is constructed with an object-oriented knowledge language AEKL, which is used to study integrated knowledge modeling and knowledge reasoning technology. The case retrieving method of aluminum profile extrusion is developed with knowledge language AEPCRL.Based on the shortcoming analysis of finite element method (FEM) and finite volume method (FVM) in simulating thin-walled aluminum extrusion, a finite volume multi-stage simulation technology is proposed to simulate extrusion process of thin-walled aluminum part. With the FVM multi-stage simulation method, mesh rezoning in FEM simulation is avoided. Moreover, the problem of computer resource shortage in FVM one-step simulation can be solved efficiently. Finer Euler mesh can be obtained through reducing meshing scope in single step. Therefore the simulation problem of thin-walled aluminum profile extrusion is solved successfully.An optimization model for die bearing design of aluminum extrusion is presented, which integrates ameliorated BP neural network, numerical simulation and genetic algorithm. The area of extrusion section is divided into several elements and the bearing values of them are given as the input parameters of network training specimen by using the orthogonal method. The target value of the model is mean-squared error of velocity after forming. Finite volume method is used in the numerical simulation to get the target value of specimen and the general optimization solution is attained through genetic algorithm. Theoptimization of process parameters can not only be realized with this method, but also the time of numerical simulation can be reduced greatly through prediction of artificial neural network.The architecture of KBE system for aluminum extrusion die design is studied. Then an intelligent design KBE system for aluminum profile extrusion system KBAES is established, taking AutoCAD as developing platform and Autodesk ObjectARX API as developing tool. The functions of the system are demonstrated with an example. The design results of die dimension, die profile layout, die bearing, die strength, extrusion press and extrusion barrel are obtained. Then the design scheme is verified with numerical simulation. So, the effectiveness of the system is verified.