Geometric robustness and dynamic response management by structural topometry optimisation to reduce the risk for squeak and rattle

Historically, squeak and rattle (S&R) sounds have been among the top quality problems and a major contributor to the warranty costs in passenger cars. Geometric variation is among the main causes of S&R. Though, geometric variation analysis and robust design techniques have been passively involved in the open-loop design activities in the predesign-freeze phases of car development. Despite the successful application of topometry optimisation to enhance attributes such as weight, durability, noise and vibration and crashworthiness in passenger cars, the implementation of closed-loop structural optimisation in the robust design context to reduce the risk for S&R has been limited. In this respect, the main obstacles have been the demanding computational resources and the absence of quantified S&R risk evaluation methods. In this work, a topometry optimisation approach is proposed to involve the geometric variation analysis in an attribute balancing problem together with the dynamic response of the system. The proposed method was used to identify the potential areas of a door component that needed structural reinforcement. The main objective was to enhance the design robustness to minimise the risk for S&R by improving the system response to static geometrical uncertainties and dynamic excitation

Variation Analysis considering manual assembly complexity in a CAT tool.

Virtual geometry assurance is a key component of today´s product development. Much of the virtual geometry assurance is done in Computer Aided Tolerancing (CAT) tools. Earlier research has shown that manual assembly complexity influences the geometrical quality of the product and that assembly tolerances are seldom used in CAT simulations for manual assembly parts. In this study a method for including manual assembly complexity in variation analysis in CAT is introduced and discussed.The method has been tested and implemented in a CAT tool using a real industrial case with promising results

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

Geometrical Variation Mode Effect Analysis (GVMEA) for Split Lines

The visual quality is a large contributor to the over-all quality impression of a product. For a complex, assembled product the visual quality is often judged by the geometrical quality in its split lines, where parallel split lines with small gaps and no flush usually are the desirable outcome. The gap, flush and parallelism in the split lines are affected by the variation on part level, variation in the joining process and the design concept itself. The visual sensitivity of a split line is also important in this context, e.g. if a split line is hidden, its visual quality is not important. In this paper, the ideas from traditional failure mode effect analysis (FMEA) are adapted to a geometry assurance context, where the visual impression of split lines is in focus. The visual sensitivity, as well as the probability of non-nominal outcomes, are included in the analysis. The probabilities of non-nominal outcomes are calculated using advanced non-rigid variation simulation based on Monte Carlo simulation combined with finite element analysis. In this way, all forces and bending due to joining and non-nominal geometries can be included. The goal of the suggested geometrical variation mode effect analysis (GVMEA) is to rank the split lines from the most critical one to the least critical one for the visual quality of a product. This is done by calculating a risk priority number for each split line. In this way, the split lines with the highest risk to impair the visual quality of a product can be identified and hopefully fixed. The method is demonstrated on a ready-to-assemble chest, i.e. on an example from the furniture industry

Individualizing Locator Adjustments of Assembly Fixtures Using a Digital Twin

Implementing the concept of a digital twin in full production provides enough data on each individual assembly for real-time control of production processes. Taking advantage of this opening, this paper proposes individualized locator adjustments as a new method to improve the geometrical quality of assemblies. In this method, all locators in the assembly fixture can be adjusted for each individual assembly based on the scan data of the mating parts of that assembly. The optimal adjustment of every locator for each individual assembly is obtained using an optimization algorithm and nonrigid variation simulation tools (computer-aided tolerancing tools). This method is applied to three industrial cases and geometrical variations and the mean deviation from nominal positions are compared to nonindividualized adjustments and also when there are no adjustments. The results show that applying this method, an improvement of up to 81% in geometrical variation and 78% in the mean deviation of assemblies can be obtained compared to assemblies without adjustments. These improvements are 60% and 57% higher than nonindividualized adjustments of locators for the variation and the mean deviation, respectively. Moreover, a modification on the optimization algorithm has been proposed that reduces the amount of required adjustments

Critical joint identification for efficient sequencing

Identifying the optimal sequence of joining is an exhaustive combinatorial optimization problem. On each assembly, there is a specific number of weld points that determine the geometrical deviation of the assembly after joining. The number and sequence of such weld points play a crucial role both for sequencing and assembly planning. While there are studies on identifying the complete sequence of welding, identifying such joints are not addressed. In this paper, based on the principles of machine intelligence, black-box models of the assembly sequences are built using the support vector machines (SVM). To identify the number of the critical weld points, principle component analysis is performed on a proposed data set, evaluated using the SVM models. The approach has been applied to three assemblies of different sizes, and has successfully identified the corresponding critical weld points. It has been shown that a small fraction of the weld points of the assembly can reduce more than 60% of the variability in the assembly deviation after joining

Evaluation of geometric tolerances using strain energy density

Traditionally, the geometric quality of assembled products has been evaluated by deviation from nominal values. However, the increased use mixed materials in especially automotive industry, in combination with an increased use of non-rigid simulation, open up for other evaluation criteria to complement the traditionally used deviation. The stiffness of a part or subassembly will, in combination with its deviation from nominal, give rise to different amounts of energy needed to join it to other parts. In this paper, the energy needed for joining is suggested as an evaluation criterion, complementary to geometric deviation, to judge the severity of the deviation

Design of the top tether component for the premium car market segment: Case study of Volvo Cars

The positive correlation between successful car design and high perceived quality is indisputable. In the highly competitive premium car market segment, the implementation of methods for perceived quality evaluation is an integral part of the strategic development plans of car manufacturers. However, to correctly define the perceived quality requirements and address market opportunities, the car manufacturers need to capture diverse customer demands. This study seeks to understand how customers perceive and prioritize attributes that are associated with the perceived quality of the premium car market segment. During the study, we evaluated the next generation top tether design concepts for Volvo Cars sedan models S60 and S90. The top tether is the part of an ISOFIX system used to connect a forward-facing child seat in a car and is a critical safety component significantly reducing potential injuries. We applied the Perceived Quality Attributes Importance Ranking (PQAIR) methodology to understand the importance of different perceived quality attributes from a customer perspective. In other words, we investigated the meaning of “premiumness” for the customers, applied to the specific car component. This approach was tested on 200 respondents representing the customer target group and was performed in collaboration with Volvo Cars technical experts. Our results verify the rationality of the applied method and indicate the improvement of engineering practices regarding the evaluation of perceived quality

Efficient spot welding sequence simulation in compliant variation simulation

Geometric variation is one of the sources of quality issues in a product. Spot welding is an operation that impacts the final geometric variation of a sheet metal assembly considerably. Evaluating the outcome of the assembly, considering the existing geometrical variation between the components can be achieved using the Method of Influence Coefficients (MIC), based on the Finite Element Method (FEM). The sequence, with which the spot welding operation is performed, influences the final geometric deformations of the assembly. Finding the optimal sequence that results in the minimum geometric deformation is a combinatorial problem that is experimentally and computationally expensive. For an assembly with N number of welds, there are N! possible sequences to perform the spot welding operation. Traditionally, spot welding optimization strategies have been to simulate the geometric variation of the spot-welded assembly after the assembly has been positioned in an inspection fixture, using an appropriate measure of variation. In this approach, the calculation of deformation after springback is one of the most time-consuming steps. In this paper, the cause of variation in the deformations after the springback, between different sequences is identified. The relative displacements of the weld points in the assembly fixture, when welded in a sequence, is the source of such behavior. Capturing these displacements leads to large time savings during sequence optimization. Moreover, this approach is independent of the inspection fixture. The relative weld displacements have been evaluated on two sheet metal assemblies. The sequence optimization problem has been solved for the two assemblies using this approach. The optimal sequence, the corresponding final assembly deformations, and the time-consumption have been compared to the traditional approach. The results show a significant correlation between the weld relative displacements in the assembly fixture, and the assembly deformation in the inspection fixture. Considering the relative weld displacement makes each assembly evaluation less time-consuming, and thereby, sequence optimization time can be reduced up to 30%, compared to the traditional approach

Automated and interactive evaluation of welding producibility in an multidisciplinary design optimization environment for aircraft components

The automation capabilities and virtual tools within engineering disciplines, such as structural mechanics and aerodynamics, enable efficient Multidisciplinary Design Optimization (MDO) approaches to evaluate and optimize the performance of a large number of design variants during early design stages of aircraft components. However, for components that are designed to be welded, in which multiple functional requirements are satisfied by one single welded structure, the automation and simulation capabilities to evaluate welding-producibility and predict welding quality (geometrical deformation, weld bead geometrical quality, cracks, pores, etc) are limited. Besides the complexity of simulating all phenomena within the welding process, one of the main problems in welded integrated components is the existing coupling between welding quality metrics and product geometry. Welding quality can vary for every new product geometrical variant. Thus, there is a need of analyzing rapidly and virtually the interaction and sensitivity coefficients between design parameters and welding quality to predict welding producibility. This paper presents as a result an automated and interactive welding-producibility evaluation approach. This approach incorporates a data-based of welding-producibility criteria, as well as welding simulation and metamodel methods, which enable an interactive and automated evaluation of welding quality of a large number of product variants. The approach has been tested in an industrial use-case involving a multidisciplinary design process of aircraft components. The results from analyzing the welding-producibility of a set of design variants have been plotted together with the analysis results from other engineering disciplines resulting in an interactive tool built with parallel coordinate graphs. The approach proposed allows the generation and reuse of welding producibility information to perform analyses within a big spectrum of the design space in a rapid and interactive fashion, thus supporting designers on dealing with changes and taking fact-based decisions during the multidisciplinary design process