Dimensional Variation Analysis of Compliant Sheet Metal Assembly

2011 ◽  
Author(s):  
Na Cai ◽  
Lihong Qiao
Keyword(s):  
Sheet Metal ◽  
Variation Analysis ◽  
Dimensional Variation ◽  
Sheet Metal Assembly

Variation Analysis for Compliant Assembly

2000 ◽  
Author(s):  
S. Jack Hu ◽  
Yufeng Long ◽  
Jaime Camelio
Keyword(s):  
Sheet Metal ◽  
Assembly Line ◽  
Assembly Process ◽  
Variation Analysis ◽  
Assembly Lines ◽  
Compliant Assembly ◽  
Single Station ◽  
Dimensional Variation ◽  
Sheet Metal Assembly

Abstract Assembly processes for compliant non-rigid parts are widely used in manufacturing automobiles, furniture, and electronic appliances. One of the major issues in the sheet metal assembly process is to control the dimensional variation of assemblies throughout the assembly line. This paper provides an overview of the recent development in variation analysis for compliant assembly. First, the unique characteristics of compliant assemblies are discussed. Then, various approaches to variation modeling for compliant assemblies are presented for single station and multi-station assembly lines. Finally, examples are given to demonstrate the applications of compliant assembly variation models.

Compliant Assembly Variation Analysis Using Components Geometric Covariance

Manufacturing ◽  
2002 ◽  
Author(s):  
Jaime A. Camelio ◽  
S. Jack Hu
Keyword(s):  
Principal Component Analysis ◽  
Finite Element ◽  
Sheet Metal ◽  
Finite Element Methods ◽  
Principal Component ◽  
Deformation Mode ◽  
Component Analysis ◽  
Variation Analysis ◽  
The Individual ◽  
Sheet Metal Assembly

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.

A genetic algorithm-based fixture locating positions and clamping schemes optimization

2003 ◽  
Vol 217 (8) ◽  
pp. 1075-1083 ◽  
Author(s):  
Y G Liao
Keyword(s):  
Genetic Algorithm ◽  
Sheet Metal ◽  
Optimization Method ◽  
Form Accuracy ◽  
Dimensional Variation ◽  
Stationary Set ◽  
Machining Fixtures ◽  
Sheet Metal Assembly ◽  
Industrial Part ◽  
Selection Of

Optimizing the locator positions and clamping schemes of a fixture was proven to improve the dimensional and form accuracy of a workpiece significantly. A number of approaches have been developed to optimize the designs of sheet-metal assembly fixtures and machining fixtures. However, in these previous works, the optimal selection of the positions of locators and clamps were based on a stationary set of locator and clamp conditions; i.e. the numbers of the locators and clamps were fixed during optimization. This paper proposes a genetic algorithm (GA)-based optimization method to select automatically the optimal numbers of locators and clamps as well as their optimal positions in sheet-metal assembly fixtures, such that the workpiece deformation due to the gravity effect and resulting variation due to part dimensional variation are simultaneously minimized. The application result of a real industrial part demonstrated that the proposed algorithm effectively achieves the objective.

Optimization of Fixture and Joint Positions in Sheet Metal Assembly: The Effect of Fixture Numbers and Constraints

2011 ◽  
Author(s):  
Kambiz Haji Hajikolaei ◽  
G. Gary Wang
Keyword(s):  
Sheet Metal ◽  
Metal Forming ◽  
Optimization Method ◽  
Stochastic Methods ◽  
Objective Functions ◽  
Variation Analysis ◽  
Spring Back ◽  
Final Assembly ◽  
Deterministic Methods ◽  
Sheet Metal Assembly

Assembly process is widely used in the manufacturing processes. Fabrication processes such as machining, casting and metal forming are not perfect and introduce variation in the components. Variations of components and tools accumulate and cause the assembly variation. In this paper, after reviewing the literature and presenting sheet metal assembly variation analysis, an optimization method is used to minimize the assembly variation by optimizing the location of joints and fixtures. The model is constructed in ANSYS with three fixtures and two joints. When a black-box function calculated numerically in software is used as the objective function, using deterministic methods for optimization is not suitable because the deterministic methods need knowledge of the objective functions. Also, using stochastic methods such as genetic algorithm is not suitable because of the large number of function evaluations they normally need. In this paper, an optimization algorithm based on mode-pursuing sampling (MPS) method is used to minimize the assembly variation. The optimization method is explained and after implementing the method, results are presented. It is learned that, in addition to the number of fixtures, the constraints on neighboring fixture locations also affect the optimal fixture layout, as well as the final assembly stiffness and spring-back.

Product-Oriented Sensitivity Analysis for Multistation Compliant Assemblies

2006 ◽  
Vol 129 (8) ◽  
pp. 844-851 ◽  
Author(s):  
Jianpeng Yue ◽  
Jaime A. Camelio ◽  
Melida Chin ◽  
Wayne Cai
Keyword(s):  
Product Performance ◽  
Sensitivity Index ◽  
Final Assembly ◽  
Sensitivity Indices ◽  
Dimensional Variation ◽  
Product And Process ◽  
Pattern Sensitivity ◽  
Sheet Metal Assembly

Dimensional variation in assembled products directly affects product performance. To reduce dimensional variation, it is necessary that an assembly be robust. A robust assembly is less sensitive to input variation from the product and process components, such as incoming parts, subassemblies, fixtures, and welding guns. In order to effectively understand the sensitivity of an assembly to input variation, an appropriate set of metrics must be defined. In this paper, three product-oriented indices, including pattern sensitivity index, component sensitivity index, and station sensitivity index, are defined. These indices can be utilized to measure the variation influence of a pattern, an individual part, and/or component, and components at a particular station to the dimensional quality of a final assembly. Additionally, the relationships among these sensitivity indices are established. Based on these relationships, the ranges of the sensitivity indices are derived. Finally, a case study of a sheet metal assembly is presented and discussed to illustrate the applicability of these metrics.

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