Björn Lindau

Method for Handling Model Growth in Nonrigid Variation Simulation of Sheet Metal Assemblies

In automotive industry, virtual tools and methods are becoming increasingly important to ensure robust solutions as early as possible in the development processes. Today, techniques exist that combine Monte Carlo simulations (MCS) with finite element analysis (FEA) to capture the parts nonrigid geometric behavior when predicting variation in a critical dimension of a subassembly or product. A direct combination of MCS with full FEA requires high computational power and the calculations tend to be very time consuming. To overcome this problem, the method of influence coefficients (MIC) was proposed by Liu and Hu in the late 1990s. This well-known technique has since then been used in several studies of nonrigid assemblies and sensitivity analysis of the geometric fault propagation in multistation assembly processes. In detailed studies of the resulting subassemblies and levels of variation, functionality for color plots and the ability to study the geometry in arbitrary sections are desired to facilitate the analysis of the simulation results. However, when including all part nodes in combination with methods for contact and spot weld sequence modeling, the required sensitivity matrices grow exponentially. In this paper, a method is proposed, describing how traditional MIC calculations can be combined with a separate detailed subassembly analysis model, keeping the model sizes down and thus facilitating detailed studies of larger assembly structures.

Efficient Contact Modeling in Nonrigid Variation Simulation

Virtual tools and methods are becoming increasingly important in order to predict the geometric outcome in early phases of the product realization process. Method of influence coefficients (MIC) in combination with Monte Carlo simulation (MCS) is a well-known technique that can be used in non-rigid variation simulation. In these simulations, contact modeling is important to ensure a correct result. Contact modeling simulates how mating surfaces are hindered from penetrating each other, giving rise to contact forces that contribute to the deformation of the parts when assembled and the final shape of the subassembly after springback. These contact forces have to be taken into consideration in each MCS-iteration. To secure reasonable response times, the calculation of the contact forces needs to be fast. In this paper, we formulate a quadratic programming(QP) problem to solve the contact problem. The case studies presented show that node-based contact modeling can be efficiently solved through QP.

Using Forming Simulation Results In Virtual Assembly Analysis

In Car Body Assembly Shops, Body in White (BIW), non-rigid sheet metal panels are assembled into car bodies. Depending upon the achieved degree of robustness in part and tool design, the produced items tend to deviate more or less from their nominal specifications. Catching eventual non-robust solutions early on in the development phases is important to minimize time-consuming, expensive testing and trimming activities late in the development- and industrialization phases. To meet these demands, there is today an increased use of virtual forming and assembly tools within the automotive industry. Significant amounts of research have been performed in the area of forming and assembly simulations, but there is still a need to find efficient working methods. This study has focused upon how forming simulation results can be used in virtual assembly analysis. The predicted springback shapes (offset and variation) of the stamped panels are used in the assembly simulation to study the effects of the part variation when assembled, producing a sub-assembly. The method used is described, and the simulation results are reported. The case shows the potential of using forming simulation results in virtual assembly analysis. Furthermore, the strength of using the Principal Component Analysis technique to describe the part variation in assembly simulations is shown.

Joining in Nonrigid Variation Simulation

Geometrical variation is closely related to fulfillment of both functional and esthetical requirements on the final product. To investigate the fulfillment of those requirements, Monte Carlo (MC)-based variation simulations can be executed in order to predict the levels of geometrical variation on subassembly and/or product level. If the variation simulations are accurate enough, physical tests and try-outs can be replaced, which reduce cost and lead-time. To ensure high accuracy, the joining process is important to include in the variation simulation. In this chapter, an overview of nonrigid variation simulation is given and aspects such as the type and number of joining points, the joining sequence and joining forces are discussed.

Inspection Data to Support a Digital Twin for Geometry Assurance

Geometrical variation is a problem in all complex, assembled products. Recently, the Digital Twin concept was launched as a tool for improving geometrical quality and reduce costs by using real time control and optimization of products and production systems. The Digital Twin for geometry assurance is created together with the product and the production systems in early design phases. When full production starts, the purpose of the Digital Twin turns towards optimization of the geometrical quality by small changes in the assembly process. To reach its full potential, the Digital Twin concept is depending on high quality input data. In line with Internet of Things and Big Data, the problem is rather to extract appropriate data than to find data. In this paper, an inspection strategy serving the Digital Twin is given. Necessary input data describing form and shape of individual parts, and how this data should be collected, stored and utilized is described.

EFFICIENT COMPLIANT VARIATION SIMULATION OF SPOT WELDED ASSEMBLIES

© 2019 by ASME. During product development one important aspect is the geometric robustness of the design. This is due to the fact that all manufacturing processes lead to products with variation. Failing to properly account for the variability of the process in the design phase may lead to expensive redesign. One important tool during the design phase in many industries is variation simulation, which makes it possible to predict and optimize the geometric quality of the design. However, despite the increase in computer power, calculation time is still an obstacle for the wider use of variation simulation. In this article, we propose a new method for efficient compliant variation simulation of spot-welded sheet metal assemblies. The method is exact, and we show that the method leads to time savings in simulation of approximately 40-50% compared to current state-of-the-art variation simulation.

Non-rigid variation simulation using the Sherman-Morrison-Woodbury formulas

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.

Challenges Moving from Physical into Virtual Verification of Sheet Metal Assemblies

Within industry there is an established need for enhanced virtual tools and methods to improve product tolerance setting and conditions for successful manufacturing of non-rigid assemblies. A significant amount of research has been performed in the area, but there is still a need to find efficient working methods and the right preconditions in practice. This paper reports experiences and findings made during recently performed virtual matching and trimming of sheet metals in a real automotive industrial setting. A case is presented, demonstrating the possible use of the Computer Aided Tolerance(CAT) tool RD&T, (Robust Design & Tolerancing), in order to predict the geometric behavior of non-rigid parts when assembled. Scanned parts are used as input and the analysis is performed using the described virtual platform instead of physical type-bound rigging equipment traditionally used for conflict, gap and final springback analysis. The proposed working procedure, and the reasons behind it, are presented. The need of additional radical and incremental innovations is brought into light, in order to make earlier predictions in the product realization process. Furthermore, it is discussed whether the necessary changes in working procedures can impose innovation barriers in the future.

Using Morphing Techniques in Early Variation Analysis

Today, in order to be competitive in a fierce global car market, higher demands are placed on the Perceived Quality (PQ) of the products. The end customers visual impression of fit and finish are one of several factors influencing the overall PQ. When assessing the PQ of split-lines, the assumed geometric variation of the ingoing parts is an important prerequisite for trustworthy visualization and for correct judgments. To facilitate early decision making in conceptual phases, new demands are set on virtual tools and methods to support the engineers. In this study, a method for early evaluation of the impact of geometrical variation on PQ of split-lines is proposed. Starting from an exterior styling model, mesh morphing techniques have been used to distort the exterior model according to measurement data acquired in running production. Morphing techniques have also been used to adopt previous structural design solutions onto the new styling, in order to make an early assumption of the assembly stiffness. The used method is described and adopted in an industrial case. The study shows that the presented technique can be used to create continuous and correlated datasets. Non-rigid part behavior can be included in early PQ evaluations, even if final CAD/FEA engineering design models do not yet exist.

Aspects of fixture clamp modeling in non-rigid variation simulation of sheet metal assemblies

Today there is an increased use of CAT-tools (Computer Aided Tolerancing) within the automotive industry. These kinds of virtual tools are getting increasingly important to ensure robust solutions as early as possible in the development processes, to minimize the use of test series and thereby reduce lead times and development costs. This paper focuses upon modeling of fixture locating scheme and the aspect of how many degrees of freedoms (DoF) a clamp actually locks. The clamps control part movement allowance, and it is of importance to investigate the influence from the friction forces between the clamping units and the fixated parts. Simulated forces in non-steering directions are compared to friction forces measured in real body shop production equipment. The non-rigid variation simulations have been performed based upon the Method of Influence Coefficients (MIC) and additional functionality for contact modeling, force estimation and weld sequence analysis. There are a variety of alternatives of how to build the simulation model and the made choices obviously influence the simulation results. The industrial case study shows significant differences in both estimated in-plane forces and geometric results after springback for different choices of modeling alternatives. It demonstrates the difficulties in taking the friction force into consideration in variation simulation of sheet metal assembly processes.