The load-bearing capacities of (i) self-piercing-riveted, (ii) adhesive-bonded and (iii) hybrid riv-bonded lap joints of commercial 1.5-mm-thick EN AW-6016-T4 sheets were compared under both ...quasi-static and cyclic shear-tensile loads. The joints were heat-treated to cure the adhesive and to peak-age the aluminum alloy. The joint quality/integrity was assessed based on characteristic cross-sectional features and hardness maps. Riveted joints showed notably lower static strength and fatigue performance than riv-bonded joints. Hence, the adhesive layer provided the main contribution to both the static and the cyclic load-bearing capacities of riv-bonded joints, whereas rivets contributed only little. However, if bonding was insufficient the potential capacity of the joints could not be exploited. Under quasi-static loading fracture occurred at the joint; therefore, joints of high quality/integrity were important. Even under cyclic loading at high load amplitudes fracture occurred at the joint, but at comparatively low load amplitudes fracture rather occurred at the sheets next to the joint. Hence, the joint quality/integrity mainly determines the static fracture and the low-cycle fatigue fracture, whereas the sheet properties mainly determine the high-cycle fatigue fracture.
In order to improve the quality of the body-in-white (BIW), optical coordination measurement machines (OCMM) are used to measure the dimensional variation for BIW. The big OCMM online measurement ...data with low signal-to-noise ratio makes the variation patterns recognition to be difficult and challenges the traditional statistical process control (SPC) technology and the common variation recognition approaches. In this paper, we propose an automatic and integrated method to recognise the control chart patterns (CCPs), which includes three main modules. The Jarque-Bera test is applied in the wavelet denoising module. The feature extraction module extracts a combination set of shape features and statistical features. In the classifier module, a two-hidden-layer Backpropagation neural network (BPN) is trained and tested. In the experiment, the proposed method is also compared with other CCPs recognition methods. Finally, a practice case is studied to show the application of the integrated method and validate the high recognition accuracy of the integrated system.
In design optimization, as the number of input variables increases, the convergence rate of optimization tends to decrease, and the number of function calls and design change costs tend to increase. ...Neighborhood component feature selection (NCFS) was adopted to select significant input variables. However, the parameter determination process of the NCFS incurs a high computational cost and weakens robustness. Therefore, this study proposes a normalized NCFS (nNCFS) by normalizing scales between mean loss and regularization terms via the initial dataset Additionally, in the case of a multi-response system, complex decision-making processes that involve the allocation of weights for multiple responses are required. It is possible to allocate weights by using conventional methods such as the analytic hierarchy process and entropy methods. However, the analytic hierarchy process method is highly influenced by the designer’s subjectivity, and the entropy method is unable to consider a design optimization problem. Accordingly, the feasible-improved weight allocation (FIWA) method is now proposed by considering a design optimization problem objectively. Comparing the NCFS with the nNCFS through mathematical examples, we found that the nNCFS significantly improved the computational cost and robustness. Moreover, the FIWA method selected significant input variables that yielded feasible and improved designs. Then, the nNCFS and the FIWA methods were applied to the design of the body-in-white of a vehicle. The significance of input variables was analyzed using the nNCFS, and feasible and improved designs were obtained on the basis of the significant input variables selected using the FIWA method.
•The nNCFS is proposed by normalizing scales between mean loss and regularization terms.•Robustness and computational cost of the nNCFS are significantly improved.•The FIWA method is proposed considering a design optimization problem.•Feasible and improved designs are obtained using the FIWA method.•The optimum designs are obtained using fewer significant input variables.
Modern car body production is faced by an increasing number of car models as well as individualizing options, which leads to the need for more adaptable assembly equipment, e.g. grippers and fixtures ...that can switch between models in a matter of seconds. Based on known clamping positions, automated jigs consisting of several clamps can already adapt to different part geometries.
To enable an efficient flexible jig, exactly one clamp must be assigned to each clamping point of each model taking into account different optimization criteria. Therefore, clamping points need to be grouped across all different models in the planning phase. Grouping of clamping points e.g. in order to minimize adaptation time or tooling costs is usually performed manually.
In this paper, the grouping optimization problem is formalized, and a mathematical algorithm is introduced to solve this multi-dimensional matching. The envisaged approach uses a greedy algorithm to get an initial solution, which is optimised to a technically feasible solution considering economical aspects. To conclude, a short evaluation of the achieved results - especially in comparison with expert based grouping - is given.
The thermal loading during the curing process of an adhesive-bonded joint induces residual stresses in the joint, thereby affecting its performance. The problem becomes worse in the case of a ...multi-material joint involving varying coefficients of thermal expansion (CTE) for different parts. A novel approach was developed to model the properties of automotive grade structural adhesives during the heat curing process. The material model was divided into two components: curing kinetics model and viscoelastic mechanical model. The models were calibrated using experimental data from Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA) tests performed on an epoxy-based single-component adhesive. The calibrated material model parameters were fed into a finite element simulation and the prediction results were compared to a unique set of experiments utilizing two substrate combinations of adhesive-bonded single lap shear joints. An excellent agreement between the simulated and experimental results (displacement across the bond, force applied by the adhesive) was achieved. The modeling results give a better understanding of the residual stresses and agree with the experimental trend on the effect of bondline thickness on the joint.
•T-SHCA algorithm is effective for nonlinear optimizations of frame structures with multiple variables.•Step IED target function in the inner loop of the optimization framework can improve the global ...search capability.•Cell thickness updating with PID control can improve the global search capability and lead to better robustness.•T-SHCA algorithm has high efficiency and accuacy for lightweight optimization of BIW under side collision.
Body-in-white (BIW) is a typical frame structure formed by a great many thin-walled structures, and the optimal design of its lightweight and crashworthiness is a typical nonlinear dynamic response optimization problem with multiple design variables. Here, we propose a thickness-based subdomain hybrid cellular automata (T-SHCA) algorithm to solve the lightweight design of BIW under side collision, in which there are two loops: one is the outer loop to conduct crash finite element analysis, calculate output responses, and update internal energy density (IED) and target mass; the other is the inner loop to adjust cell thicknesses according to IEDs of current cell and its neighboring cells to make the actual mass of current cells converge to target mass. The concept of "subdomain cellular automata (SCA)" model was introduced, so that the T-SHCA can solve nonlinear dynamic response optimization in discrete and separated design spaces. The step IED target update rule and the cell thickness update rule based on a PID control strategy were implemented in the inner loop to improve the global optimal solution search capability and the robustness of the proposed algorithm, respectively. The thicknesses optimization of a BIW was carried out by the proposed method and a parallel efficient global optimization algorithm to verify its convergence and efficiency. The results show that the T-SHCA algorithm can be implemented to effectively solve nonlinear dynamic response structural optimization problem with many thickness variables in discrete and separated design spaces.
7000 series aluminum alloys have particularly high strength, if compared to other aluminum alloys or even to some high strength steels. Currently, this alloy is considered on the next developments of ...automotive structures, as an enabler of improved mechanical and safety properties, associated with weight reduction, supporting the industry to fulfill fuel economy and greenhouse gases emissions regulations. Due to the proneness to hot cracking and welding embrittlement, the joining of 7000 series sheets is limited to mechanical methods, such as self-piercing rivets.
In order to provide the automotive industry with more joining methods suitable for the proposed high strength aluminum alloy, the objective of this work is to validate the resistance spot welding process of the AW-7075 alloy. The work is split in two parts: the preliminary assessment of the suitability of current welding procedures, norms and respective parameters, where the process window, weld nugget quality and electrode life-time are evaluated. Then an innovative approach is investigated, where the use of an upslope welding schedule, CuAg0.1 electrode caps, increased force and lower overall electric resistance could successfully validate the application, attending manufacturing requirements regarding welding quality, electrode life-time and process window. The resultant microstructure characteristics were analyzed with metallographic micro-sections and the phases were determined with the electron backscattered diffraction technique.
The design process of flow-oriented assembly systems is characterized by being both highly complex and time consuming. Especially those design processes categorized into robotic and multi variant ...encountered in the automotive body-in-white production stages. Unlike established manual and template-based assembly system design models, which are currently applied in industry, the here presented novel approach uses a knowledge-based search algorithm and automatically generates optimal assembly system configurations. The algorithm has been implemented in a software prototype and the results have been validated against different large-size industrial scenarios in the automotive field of body-in-white production.
The Fraunhofer IWU has been developed specialized clamping robots for production of different car-models on one fixture. One of the challenges with universal clamping of different components is the ...contact point between part and clamping device. For the optimization of the clamping contours, a software was developed with which the geometries of the clamping points can be automatically analyzed and classified. With target search criteria, the clamping position on the component can be changed so that the clamping contours are geometrically simplified. Thus, a huge reduction in the complexity of the flexible clamping device is possible.
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