23 research outputs found
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
Back seat driving: hindlimb corticospinal neurons assume forelimb control following ischaemic stroke
Whereas large injuries to the brain lead to considerable irreversible functional impairments, smaller strokes or traumatic lesions are often associated with good recovery. This recovery occurs spontaneously, and there is ample evidence from preclinical studies to suggest that adjacent undamaged areas (also known as peri-infarct regions) of the cortex ‘take over' control of the disrupted functions. In rodents, sprouting of axons and dendrites has been observed in this region following stroke, while reduced inhibition from horizontal or callosal connections, or plastic changes in subcortical connections, could also occur. The exact mechanisms underlying functional recovery after small- to medium-sized strokes remain undetermined but are of utmost importance for understanding the human situation and for designing effective treatments and rehabilitation strategies. In the present study, we selectively destroyed large parts of the forelimb motor and premotor cortex of adult rats with an ischaemic injury. A behavioural test requiring highly skilled, cortically controlled forelimb movements showed that some animals recovered well from this lesion whereas others did not. To investigate the reasons behind these differences, we used anterograde and retrograde tracing techniques and intracortical microstimulation. Retrograde tracing from the cervical spinal cord showed a correlation between the number of cervically projecting corticospinal neurons present in the hindlimb sensory-motor cortex and good behavioural recovery. Anterograde tracing from the hindlimb sensory-motor cortex also showed a positive correlation between the degree of functional recovery and the sprouting of neurons from this region into the cervical spinal cord. Finally, intracortical microstimulation confirmed the positive correlation between rewiring of the hindlimb sensory-motor cortex and the degree of forelimb motor recovery. In conclusion, these experiments suggest that following stroke to the forelimb motor cortex, cells in the hindlimb sensory-motor area reorganize and become functionally connected to the cervical spinal cord. These new connections, probably in collaboration with surviving forelimb neurons and more complex indirect connections via the brainstem, play an important role for the recovery of cortically controlled behaviours like skilled forelimb reachin
Characterization of the Viral Microbiome in Patients with Severe Lower Respiratory Tract Infections, Using Metagenomic Sequencing
The human respiratory tract is heavily exposed to microorganisms. Viral respiratory tract pathogens, like RSV, influenza and rhinoviruses cause major morbidity and mortality from respiratory tract disease. Furthermore, as viruses have limited means of transmission, viruses that cause pathogenicity in other tissues may be transmitted through the respiratory tract. It is therefore important to chart the human virome in this compartment. We have studied nasopharyngeal aspirate samples submitted to the Karolinska University Laboratory, Stockholm, Sweden from March 2004 to May 2005 for diagnosis of respiratory tract infections. We have used a metagenomic sequencing strategy to characterize viruses, as this provides the most unbiased view of the samples. Virus enrichment followed by 454 sequencing resulted in totally 703,790 reads and 110,931 of these were found to be of viral origin by using an automated classification pipeline. The snapshot of the respiratory tract virome of these 210 patients revealed 39 species and many more strains of viruses. Most of the viral sequences were classified into one of three major families; Paramyxoviridae, Picornaviridae or Orthomyxoviridae. The study also identified one novel type of Rhinovirus C, and identified a number of previously undescribed viral genetic fragments of unknown origin
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 part's 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
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 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
Statistical shape modeling in virtual assembly using PCA-technique
The use of virtual assembly tools is one way to understand and improve the geometric product tolerance setting and the conditions for successful manufacturing. Recent developments enable consideration to be given to the deformability of parts (single components or subassemblies) when joined. In order to produce reliable results, the geometric deviations of the mating surfaces must be correctly assumed. In this paper, statistical shape models built on the Principal Component Analysis-technique (PCA) are proposed to be used to describe the part variation. A generalized model is presented and the underlying intentions and implications are discussed. It is demonstrated how the PCA-technique can be applied on
bigger structures. The method is exemplified using the software RD&T. In the presented case, a non-rigid sheet metal assembly is modeled and distorted to create a set of sample shapes from which a statistical model is built. In the result, the statistic representation bears a good resemblance to the distorted nominal model when the two are compared
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 customer's 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
Body in White Geometry Measurements of Non-Rigid Components: a Virtual Perspective
Increased use of virtual assembly tools within automotive industry places new demands on available geometry information. Unfortunately, the measurement results of non-rigid components depend heavily on the locating schemes used in the measurement fixtures. Non-rigid component measurements are mostly performed in an over-constrained condition, describing the shapes of the parts as presented in assembly processes or as mounted on nominal products. With these kinds of measurements, there is an information loss regarding the actual springback shapes in the stored historical geometry data. Knowledge about the components' shapes after springback is vital for virtual non-rigid fault propagation analysis.
The objective of this paper is to show the possibilities for presenting the measurement results of components as they were over-constrained, even if the parts were measured in a constrained condition (in practice limited constrained). The aim is to minimize the information loss, to spare measurement resources and to allow for better use of inspection data in assembly simulations. Predicted over-constrained measurement results in the presented cases bear reasonably good resemblance to measured over-constrained conditions when the two are compared. The ability to present both constrained and over-constrained results from one measurement setup will spare measurement resources and improve conditions for further virtual analysis and support. Furthermore, the presented cases verify the use of Method of Influence Coefficients (MIC) in the clamping step