Research On The Intelligent System Of Forging Design Of Steering Knuckles

The automobile industry is the pillar industry in national economy. The forging process, which is the main method of manufacturing the key and the load-bearing automobile parts, plays an important role in the manufacture of automobile components. The steering knuckle, with many varieties and usage quantities, is mainly made from the forging process now. The steering knuckle is one of the most difficulty automobile forging parts, and the forging design level of the steering knuckle is regard as the highest of automobile forging parts. In the forging classification the steering knuckle belong to the category of fork parts. The forging process of the fork parts is muti-stages and complex forging process, so the forging design of the fork parts is very difficult.At present there are two problems in the forging manufacture of the steering knuckle. The forging process of the steering knuckle has low material utilization and high energy consumption; The new product development of the steering knuckle mainly depends on the designers' experience, which will bring the long cycle, the high cost and the large risk. This paper focuses on the studies of the forging process design and the forging intelligent design of the steering knuckle. The new forging process of the steering knuckle is developed to decrease the material utilization and energy consumption by using FEM simulations and experimental investigations. In order to find a new product development method of short-cycle, low-cost and high-quality, the expert system of the forging design of the steering knuckle is developed to supervise forging process and die design.Using finite element code DEF0RM-3D, the forging process of the typical steering knuckle is analyzed in this paper. The metal flow, the stress/strain fields, the temperature field and the load/energy curves are provided, and the forming discipline of the forging process of the steering knuckle is achieved. Moreover, the influence on forming process of the friction factor is analyzed. On the base of the analyses, the forming defect of the steering knuckle is provided to supervise forging process optimization and die design.In this paper the new forging process of a type of complex fork part is proposed to realize one-time forging on the hot die-forging press. Taking the case of SK2 forging part, the proper preforming is arranged, the blanking impression is designed, and the closed-die forging with closed-flash process for the preforging is proposed. This new process design realizes one-time forging and decreases energy consumption. Meanwhile, the horizontal forging process of the steering knuckle is studied. Taking the case of SK1 forging part, the new forging process is proposed. The new process is composed of preforming process of extruding staff and preforging process of the closed-die forging with controlled-flash. The material utilization increases significantly in the new forging process.The key technique of the neural network (NN) of the forging design of the steering knuckle is studied in this paper. The unit and the shape factor are defined to describe the feature of the forging part. The feature information of forging part is composed of both feature size and feature shape. The judging criterion is proposed to evaluate the influence on forming process of the different feature shape. Six kinds of units are defined, and the forging process of these units is studied. The forming model of the different kinds of the units is made in terms of equal volume. The shape factor is calculated by contrasting with the max energy in the forging process. The unit size revised by the shape factor is used to describe feature information of the forging part. The feature information of forging part and die are regarded as the inputting and outputting vector respectively to make the NN model of the forging process of the steering knuckle. The model includes the influence on forming process of the different feature size and feature shape. Architectures, controls parameter and learning algorithms of the NN of the forging process of the steering knuckle are also studied in the paper. The convergence and the prediction precision of the NN under different architectures, controls parameter and learning algorithms are provided, and the suggestion how to choose the parameter of the NN is proposed.Basic architecture, knowledge express and reasoning mode of the NN-based expert system is studied in this paper. The design theories and experience knowledge of the forging process and artificial intelligence technology are unified to develope the self-developed software FDesign-SK for expert system of the forging design of the steering knuckle. The experiential knowledge extracted from more than thirty kinds of forging samples of the steering knuckle is stored in this system. The system is realized with the cooperation integration of the NN and the expert system, which could avoid the default of the monotonous reasoning, difficult knowledge acquisition, no uniform knowledge representation, and et al. The framework of the system is modularization, which makes the interface operate easily. FDesign-SK is a system of opening design, and it has the good self-learning function. Therefore, the learning samples could be expanded to improve forecast accuracy and stability of the system. At last, the forging design method of application of FDesign-SK software, FEM simulation and reverse technology is proposed, which could shorten development period, lower cost and reduce workload of the designer.