Optimal tolerance allocation for five-axis machine tools in consideration of deformation caused by gravity

Many tolerancing problems on mechanical assemblies involve a functional requirement depending on a chain of parallel dimensions on individual parts. In these one-dimensional cases, simple methods are available for the analysis and the allocation of dimensional tolerances. However, they are difficult to extend to geometric tolerances, which must be translated into equivalent dimensional tolerances; this allows the analysis but makes the allocation generally impossible without Monte Carlo simulation and complex search strategies. To overcome this difficulty, the paper proposes a way of dealing directly with geometric tolerances in the allocation problem. This consists in expressing the functional requirement as a linear model of geometric tolerances rather than equivalent dimensional tolerances; the coefficients of the model (sensitivities) are calculated considering both the dimension chain and the standard definition of the geometric tolerances. The approach can be combined with any constrained optimization method based on sensitivities. The optimal scaling method, previously proposed for dimensional tolerances, is extended to geometric tolerances and used in two examples to demonstrate the simplicity of the overall workflow and the quality of the optimal solution.

Section: Literature Reviewmentioning

confidence: 99%

Allocation of geometric tolerances in one-dimensional stackup problems

Armillotta

2022

“…Based on finite element analysis, Fan J et al established a tolerance allocation optimal method which can reduce total manufacturing cost about 11.5% considering small deformation of five axis machine tools as constraints. [32].…”

Section: Introductionmentioning

confidence: 99%

Precision allocation method of large-scale CNC hobbing machine based on precision-cost comprehensive optimization

Wang

2023

In modern machine tool design, precision is an important index to characterize machine tool performance. and precision allocation has become a key task. Since middle 20th century, the precision allocation method using optimization technology to balance manufacturing cost and quality has gradually developed. But most methods mainly take the cost minimization as the goal to optimize the precision allocation. As the precision and manufacturing cost are a pair of factors to be comprehensively considered, balance between them is needed to meet different design requirements. This paper proposes a comprehensive optimization method to trade-off between precision and cost. A multi-object precision allocation optimization model aiming at minimizing fuzzy manufacturing cost and comprehensive precision of machine tool is constructed. A multiobject optimization algorithm to solve the model is designed, combining the multi-objective grey wolf optimization algorithm with multi-objective decision analysis method TOPSIS. A case study based on a large-scale hobbing machine shows that the comprehensive optimization of manufacturing cost and machining precision is realized by using the proposed multi-object precision allocation optimization method.

“…Accuracy optimization design is a way to improve the machining accuracy by reasonably distributing geometric errors to the key parts of machine tools [4][5][6][7][8]. Due to the degree of influence for each geometric error on machining accuracy has significant differences.…”

Section: Introductionmentioning

confidence: 99%

An approach to enhancing machining accuracy of five-axis machine tools based on a new sensitivity analysis method

Tao

Fan

et al. 2022

Self Cite

Identification of key geometric errors is an essential prerequisite for improving the machining accuracy of five-axis machine tools. This paper presents a new sensitivity analysis (SA) method to extract key geometric errors, and then to improve the machining performance of machine tools by compensating key geometric error components. Development of geometric error prediction model is involved to obtain geometric error values at arbitrary positions at first. Based on the multi-body system theory and flank milling theory, the machining error model is developed, which considers 37 geometric errors. Then, a new SA method is introduced by taking the machining error model as sensitivity analysis model and taking the geometric errors as analytical factors. Meanwhile, a sensitivity index, which has the characteristics of simple expression and clear physical meaning, is proposed, i.e., the peak value of the machining error caused by each geometric error. Moreover, the simulations analysis is carried out to obtain the sensitivity coefficient of each geometric error and the key error components. Finally, the validity and correctness of the proposed method is demonstrated by the experiments. Furthermore, the SA method can be extended to multi-axis machine tools.