An approach for optimal tolerance allocation of five-axis machine tools by simultaneously considering volumetric error and processing simplicity index

Optimal tolerance allocation (OTA) is one of the most effective ways to improve the machining precision of machine tools. However, the existing OTA methods have the problem that tolerance-cost models are particularly vulnerable to subjective factors, which lead to tolerance allocation scheme with poor applicability and reliability. For this reason, a novel OTA method that simultaneously considers volumetric error and processing simplicity index (PSI) is proposed in this paper. Based on the multi-body system theory and homogeneous transform matrix, the volumetric error prediction model based on tolerance of machine tools' key parts is firstly established by taking the geometric error as a bridge between tolerance and volumetric error of machine tools. Then, the weight coefficient of each tolerance parameter is calculated based on sensitivity analysis method. Moreover, PSI, which denotes the degree of processing simplicity to reach the required tolerance value, is innovatively proposed to replace manufacturing cost. And the tolerance-PSI model is established to replace tolerance-cost model. Then, an OTA model is established by minimizing volumetric error and maximizing PSI. The NSGA-II is employed to obtain OTA scheme. Finally, simulations and experiments are conducted to validate the feasibility and effectiveness of the presented method.

Automated summary

In this paper, a novel OTA method is proposed that considers the relationship between tolerance of machine tools' key parts and volumetric error. A volumetric error prediction model is established based on the bridge between geometric error and tolerance. Additionally, a Processing Simplicity Index (PSI) is introduced to replace manufacturing cost and a tolerance-PSI model is established. An OTA model is formulated to minimize volumetric error and maximize PSI. The feasibility and effectiveness of the method are validated through simulations and experiments.