Variation Simulation for Deformable Sheet Metal Assemblies Using Finite Element Methods

1997 ◽  
Vol 119 (3) ◽  
pp. 368-374 ◽  
Author(s):  
S. Charles Liu ◽  
S. Jack Hu

Traditional variation analysis methods, such as Root Sum Square method and Monte Carlo simulation, are not applicable to sheet metal assemblies because of possible part deformation during the assembly process. This paper proposes the use of finite element methods (FEM) in developing mechanistic variation simulation models for deformable sheet metal parts with complex two or three dimensional free form surfaces. Mechanistic variation simulation provides improved analysis by combining engineering structure models and statistical analysis in predicting the assembly variation. Direct Monte Carlo simulation in FEM is very time consuming, because hundreds or thousands of FEM runs are required to obtain a realistic assembly distribution. An alternative method, based on the Method of Influence Coefficients, is developed to improve the computational efficiency, producing improvements by several orders of magnitude. Simulations from both methods yield almost identical results. An example illustrates the developed methods used for evaluating sheet metal assembly variation. The new approaches provide an improved understanding of sheet metal assembly processes.

Author(s):  
D Brujic ◽  
M Ristic

Accurate dimensional inspection and error analysis of free-form surfaces requires accurate registration of the component in hand. Registration of surfaces defined as non-uniform rational B-splines (NURBS) has been realized through an implementation of the iterative closest point method (ICP). The paper presents performance analysis of the ICP registration method using Monte Carlo simulation. A large number of simulations were performed on an example of a precision engineering component, an aero-engine turbine blade, which was judged to possess a useful combination of geometric characteristics such that the results of the analysis had generic significance. Data sets were obtained through CAD (computer aided design)-based inspection. Confidence intervals for estimated transformation parameters, maximum error between a measured point and the nominal surface (which is extremely important for inspection) mean error and several other performance criteria are presented. The influence of shape, number of measured points, measurement noise and some less obvious, but not less important, factors affecting confidence intervals are identified through statistical analysis.


Author(s):  
Andrea Corrado ◽  
Wilma Polini

Tolerance analysis represents the best way to solve assembly problems in order to improve the quality and to reduce the costs. It is a critical step to design and to build a product such as an aircraft and its importance is grown up in the past years. This work presents a method for the tolerance analysis of an assembly involving free-form surfaces with large dimensions. The assembly is a tail beam, a structural component of an aircraft that is constituted by five parts of large dimensions. The influence of the tolerances applied to the five components of the tail beam on the value of the gap at the interfaces among the parts has been deeply investigated. A set of control points have been distributed on the free-form surfaces of the tail beam; its number and its distribution have been opportunely designed. Moreover, the influence of the tolerances on the other requirements of the tail beam connected with the motion drive has been studied. Tolerance analysis has involved the choice of the assembly tools and sequence too. The assembly jigs are mated with the assembly components through pins that are inserted into tooling holes located on the assembly components. The fit conditions have been modeled and the tolerances of the tooling hole have been opportunely chosen. Each tolerance of the tail beam components has been modeled by means of a probability density function. Monte Carlo approach has been used to obtain the statistical distribution of the assembly requirements, once dimensions and geometry of the tail beam components have been perturbed inside the tolerance ranges. Monte Carlo simulation has been carried out by a well-known computer-aided tolerance software, eM-Tolmate of UGS®.


Author(s):  
Jaime A. Camelio ◽  
S. Jack Hu

Dimensional variation is one of the most critical issues in the design of assembled products. This is especially important for the assembly of compliant, non-rigid parts since clamping and joining during assembly may introduce additional variation due to part deformation and springback. This paper presents a new methodology to predict sheet metal assembly variation using the components geometric covariance. The approach combines the use of principal component analysis and finite element methods to estimate the effect of components variation on assembly variation. Principal component analysis is applied to extract deformation patterns from production data, decomposing the component covariance in the individual contribution of these deformation “modes”. Finite element methods are used to determine the effect of each deformation “mode” over the assembly variation. The proposed methodology allows significant reduction in the computation effort required for variation analysis in sheet metal assembly. A case study is presented to illustrate the methodology.


2021 ◽  
Vol 50 ◽  
pp. 101301
Author(s):  
A.Z. Zheng ◽  
S.J. Bian ◽  
E. Chaudhry ◽  
J. Chang ◽  
H. Haron ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document