Multi-objective model fusion method for tolerance allocation orienting to accuracy and process improvement
In the process of modern mechanical product assembly tolerance optimization,multi-objective tolerance optimiza-tion models were often constructed with a simple weighted summing method,which often resulted in a poor solution per-formance and weak applicability on practical assembly sites.To improve assembly accuracy and process technology,through considering the pose changes among different key features caused by matting error,a cumulative model for assembly error transmission and a coordinated dimension chain were constructed,then the assembly and coordination errors among multiple assemblies could be predicted accurately.Based on the error data of each manufacturing process and the accumulated data of assembly accuracy,three single objective optimization models including manufacturing cost,quality loss and repair cost were established,and then a multi-objective model weight parameter distribution formula method was proposed to avoid the im-balance of tolerance data and deviation optimization direction,as well as the multi-objective tolerance optimization allocation model.The accelerated particle-swarm optimization algorithm was taken to obtain error values for each compromised error links that could improve assembly performance.The optimization of segmented wing docking assembly for a certain type of spacecraft was verified,before improving the product positioning and clamping method,the docking flush difference of wing and repair cost were reduced by 94.68％and 83.49％,respectively.With the locating contour boards,the above two as-sembly indicators were reduced by 11.21％and 8.50％,which could ensure the products'assembly accuracy and coordina-tion quality effectively.
assembly accuracyprocess optimizationtolerance allocationfusion of parametersdocking coordination
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