scholarly journals Joining in Nonrigid Variation Simulation

10.5772/65851 ◽  
2016 ◽  
Author(s):  
Kristina Wärmefjord ◽  
Rikard Söderberg ◽  
Björn Lindau ◽  
Lars Lindkvist ◽  
Samuel Lorin
Keyword(s):  
Variation Simulation

A Framework for Non-Nominal Visualization and Perceived Quality Evaluation

2011 ◽  
Author(s):  
Ola Wagersten ◽  
Karin Forslund ◽  
Casper Wickman ◽  
Rikard So¨derberg
Keyword(s):  
Industrial Process ◽  
Perceived Quality ◽  
Product Development Process ◽  
Functional Quality ◽  
Quality Aspects ◽  
System Solution ◽  
Comprehensive Framework ◽  
Variation Simulation ◽  
Support Evaluation

Perceived Quality clusters different aspects that influence the customer’s perception of non-functional quality on a product that are perceive through senses. All together those aspects and the harmony between them reflect the producer’s ability to control product parameters and thereby also mirror the functional quality of the product. High Perceived Quality cannot be added to the product at the end of the developing process. Project prerequisites, system solution, factory capability etc. are criterion to succeed. Therefore, it is important to be able to evaluate Perceived Quality early in the process when product system solutions and architecture are defined, although data maturity is low. This paper presents a comprehensive framework to manage and support evaluation of Perceived Quality aspects in a product development process. The framework is based on an industrial process in combination with recent research within the field. The framework focuses on activities that can be performed at different stages in the developing process based on maturity of the CAD or styling data. For example, if the styling data is divided into different components by split-lines it has reached higher level of maturity then styling data that not has been divided. Consequently, the choice of applied method is based on data maturity, regardless phase in the developing process. The framework contains methods based on several different simulation and analysis techniques. Design methods, Computer-Aided Tolerancing and FEA based non-rigid variation simulation are represented in the framework.

scholarly journals Variation Simulation of Fixtured Assembly Processes for Compliant Structures Using Piecewise-Linear Analysis

2005 ◽  
Author(s):  
Michael L. Stewart ◽  
Kenneth W. Chase
Keyword(s):  
Piecewise Linear ◽  
Element Model ◽  
Linear Analysis ◽  
Elastic Analysis ◽  
Variation Analysis ◽  
Linear Elastic ◽  
Final Assembly ◽  
Compliant Part ◽  
Assembly Operations ◽  
Variation Simulation

While variation analysis methods for compliant assemblies are becoming established, there is still much to be done to model the effects of multi-step, fixtured assembly processes statistically. A new method is introduced for statistically analyzing compliant part assembly processes using fixtures. This method yields both a mean and a variant solution, which can characterize an entire population of assemblies. The method, called Piecewise-Linear Elastic Analysis, or PLEA, is developed for predicting the residual stress, deformation and springback variation resulting from fixtured assembly processes. A comprehensive, step-by-step analysis map is presented for introducing dimensional and surface variations into a finite element model, simulating assembly operations, and calculating the error in the final assembly. PLEA is validated on a simple, laboratory assembly and a more complex, production assembly. Significant modeling issues are resolved as well as the comparison of the analytical to physical results.

Complex Fastener Model for Simulation of Airframe Assembly Process

2020 ◽  
Author(s):  
Sergey Lupuleac ◽  
Aleksandr Smirnov ◽  
Julia Shinder ◽  
Margarita Petukhova ◽  
Maria Churilova ◽  
...  
Keyword(s):  
Contact Interaction ◽  
Stiffness Matrix ◽  
Complex Model ◽  
Assembly Process ◽  
Optimization Analysis ◽  
Global Modeling ◽  
Aircraft Assembly ◽  
Simulation Results ◽  
Variation Simulation ◽  
Model Dimension

Abstract The complex model of fastener for the global modeling of aircraft assembly with regard to compliance and contact interaction of parts is introduced in the paper. The presented complex fastener model incorporates such effects as the stiffness of fastening elements; the loosening of fasteners and also the failure of fasteners (if the load exceeds the maximal value that fastener can hold). This model can be implemented for all types of fastening elements in variation simulation and assembly optimization analysis. It provides more realistic simulation results at expense of higher model dimension. The fastener is modeled as having an additional stretching stiffness. The option of fastener loosening is included by implementation of additional contact node in each fastening element. This option allows taking into account the pre-tension in fasteners and also enables the modeling of installation and removal of fasteners without change of stiffness matrix.

Nonlinear Material Model in Part Variation Simulations of Sheet Metals

2019 ◽  
Vol 19 (2) ◽  
Author(s):  
Soner Camuz ◽  
Samuel Lorin ◽  
Kristina Wärmefjord ◽  
Rikard Söderberg
Keyword(s):  
Material Model ◽  
Nonlinear Material ◽  
Isotropic Hardening ◽  
Elastoplastic Material ◽  
Processing Unit ◽  
Central Processing ◽  
Physical Experiments ◽  
Linear Relationships ◽  
Influence Coefficients ◽  
Variation Simulation

Current methodologies for variation simulation of compliant sheet metal assemblies and parts are simplified by assuming linear relationships. From the observed physical experiments, it is evident that plastic strains are a source of error that is not captured in the conventional variational simulation methods. This paper presents an adaptation toward an elastoplastic material model with isotropic hardening in the method of influence coefficients (MIC) methodology for variation simulations. The results are presented in two case studies using a benchmark case involving a two-dimensional (2D) quarter symmetric plate with a centered hole, subjected to both uniaxial and biaxial displacement. The adaptation shows a great reduction in central processing unit time with limited effect on the accuracy of the results compared to direct Monte Carlo simulations.

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
Keyword(s):  
Monte Carlo Simulation ◽  
Finite Element ◽  
Monte Carlo ◽  
Sheet Metal ◽  
Finite Element Methods ◽  
Free Form ◽  
Direct Monte Carlo Simulation ◽  
Free Form Surfaces ◽  
Variation Simulation ◽  
Sheet Metal Assembly

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.

Non-Rigid Variation Simulation Using the Sherman-Morrison-Woodbury Formulas

2017 ◽  
Author(s):  
Samuel Lorin ◽  
Björn Lindau ◽  
Lars Lindkvist ◽  
Rikard Söderberg
Keyword(s):  
Product Development ◽  
Manufacturing Process ◽  
Computation Time ◽  
Statistical Distribution ◽  
Influence Coefficient ◽  
Substantial Saving ◽  
Variation Simulation ◽  
Important Activity

Variation simulation is one important activity during early product development. It is used to simulate the statistical distribution of assemblies or sub assemblies in intended manufacturing process to assure that assembly, function and aesthetical properties comply with the requirements set. In non-rigid variation simulation, components or sub assemblies can deform during assembly. To simulate non-rigid variation the Method of Influence Coefficient (MIC) is typically used. Solving the necessary sensitivity matrices used by MIC is time consuming. In this article we will apply the Sherman-Morrison and Woodbury formula (SMW) for updating the sensitivity response in the different assembly steps. It is shown that SMW can lead to substantial saving in computation time, when compared to the standard MIC.

Simulation and Optimization of Airframe Assembly Process

2018 ◽  
Author(s):  
Sergey Lupuleac ◽  
Nadezhda Zaitseva ◽  
Maria Stefanova ◽  
Sergey Berezin ◽  
Julia Shinder ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Statistical Analysis ◽  
Problem Solving ◽  
Contact Problem ◽  
Quality Measures ◽  
Assembly Process ◽  
Variation Analysis ◽  
Simulation And Optimization ◽  
The Mathematical Model ◽  
Variation Simulation

An approach for simulating the assembly process where compliant airframe parts are being joined by riveting is presented. The foundation of this approach is the mathematical model based on the reduction of the corresponding contact problem to a Quadratic Programming (QP) problem. The use of efficient QP algorithms enables mass contact problem solving on refined grids, which is needed for variation analysis and simulation as well as for the consequent assembly process optimization. To perform variation simulation, the initial gap between the parts is assumed to be stochastic and a cloud of such gaps is generated based on statistical analysis of the available measurements. The developed approach is illustrated with two examples, simulation of A350-900 wing-to-fuselage joining and optimization of A320 wing box assembly. New contact quality measures are discussed.

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