The Golbal Positionging Strategy Optimization Method Of Sheet Metal Under Considering The Fixture Error

The process of sheet metal parts assembly quality control is a systematic project. People, machines, measurement, method, and other factors will affect the size of the deviation of its products. Then the properties, appearance quality and manufacturer cost will be influenced. Ultimately it will directly affect the market competitiveness of products. With the development of technology use of sheet metal is more extensive. And the assembly quality control of sheet metal is taken seriously. Fixture point optimization is one of the main ways to improve the quality of the product size. Existing fixture design is mainly dependent on designer’s experience to design, and few data support the theory. It is high precision that using the finite element method to optimize fixture points, but the method is complicated and computational efficiency is low, it is difficult to meet the needs of actual production.In response to these problems, a method is used to reduce development costs and shorten the development cycle, which use digital simulation verification process instead of the actual parts. This paper propose a new fixture positioning strategy base on the principle of 3-2-1. Then find the locator’s position of 3-2-1 with genetic optimization algorithm which base on the rigid model. Finally, a global positioning strategy optimization method will be established and taking a car left B-pillar reinforcement plate as an example. The main work is showed as follows:(1)propose the optimization of 4-2-1 positioning strategy3-2-1 locating principle that the main plane have three anchor points. Obtain the initial data with finite element analysis software which consider fixture error. A BP neural network will be established in order to fit the deformation of sheet metal. Finally, find the position of the fourth locator using genetic algorithms so that the minimum amount of deformation of parts.(2)Optimize the 3-2-1 locator’s positon base on the rigid modelDerive the fixture deviation expression and stability mathematical expressions under conditions of uncertainty, then construct multi-objective optimization function using the weighting coefficient method. Finally, the function is used to find the locator’s position of 3-2-1 with genetic optimization algorithm.(3)fixture design optimization and application examplesAccording the method of anchor holding which first select three anchor points positioning on the main plane then applied over the anchor point to find the most suitable fixture points. Take a car left B-pillar reinforcement plate as a example, When the fixtures produce errors due to wear etc. and adjust an anchor point to make the minimum distortion.