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Im Luftfahrtbereich haben sich kohlenstofffaserverstärkte Kunststoffe (CFK) wegen ihrer hohen spezifischen Festigkeiten und Steifigkeiten längst als Konstruktionswerkstoffe etabliert. In der Großserienfertigung von Automobilkarosserien kommt diese Materialgruppe jedoch nur zögerlich zum Einsatz. Offensichtlich sprechen noch viele Argumente für den Einsatz von metallischen Werkstoffen: Denn auch Leichtmetalle und pressgehärtete Stähle ermöglichen immer höhere Leichtbaugrade, ohne dabei signifikante Kostensteigerungen zu generieren. Zudem sind Fertigungs- und Montageabläufe für Metallkarosserien etabliert und weitgehend frei von Entwicklungsrisiken. Vor diesem Hintergrund erscheint es schwer, mit neuen Leichtbaumaterialien und den zugehörigen Bauweisen einen Durchbruch erzielen zu können. Dabei zeigt das Produktsegment der Supersportwagen schon deutlich, dass zusätzliche Leichtbaupotentiale durch beanspruchungsgerecht gestaltete und optimierte CFK-Strukturen für den Automobilbau eröffnet werden. Bislang lassen sich derartig optimierte CFK-Strukturen jedoch kaum wettbewerbsfähig in Großserie realisieren. An dieser Stelle ergeben sich Chancen und zugleich neue Herausforderungen für die Produktentwickler: Zum einen sind Faserverbundbauweisen zu erarbeiten, mit denen die Leichtbaupotentiale von CFK weitgehend ausgereizt werden. Zum anderen ist die automatisierte Fertigung bei hohen Taktraten zu ermöglichen. Die Lösung beider Teilaufgaben setzt den Einsatz geeigneter materialspezifischer Konstruktionsmethoden voraus.

This thesis examines an automated method to detect surface deformations on automotive panels for the purpose of quality control along a manufacturing assembly line. Automation in the automotive manufacturing industry is becoming more prominent, but quality control is still largely performed by human workers. Quality control is important in the context of automotive body panels as deformations can occur along the assembly line such as inadequate handling of parts or tools around a vehicle during assembly, rack storage, and shipping from subcontractors. These defects are currently identified and marked, before panels are either rectified or discarded. This work attempts to develop an automated system to detect deformations to alleviate the dependence on human workers in quality control and improve performance by increasing speed and accuracy. Some techniques make use of an ideal CAD model behaving as a master work, and panels scanned on the assembly line are compared to this model to determine the location of deformations. This thesis presents a solution for detecting deformations of various scales without a master work. It also focuses on automated analysis requiring minimal intuitive operator-set parameters and provides the ability to classify the deformations as dings, which are deformations that protrude from the surface, or dents, which are depressions into the surface. A complete automated deformation detection system is proposed, comprised of a feature extraction module, segmentation module, and classification module, which outputs the locations of deformations when provided with the 3D mesh of an automotive panel. Two feature extraction techniques are proposed. The first is a general feature extraction technique for 3D meshes using octrees for multi-resolution analysis and evaluates the amount of surface variation to locate deformations. The second is specifically designed for the purpose of deformation detection, and analyzes multi-resolution cross-sections of a 3D mesh to locate deformations based on their estimated size. The performance of the proposed automated deformation detection system, and all of its sub-modules, is tested on a set of meshes which represent differing characteristics of deformations in surface panels, including deformations of different scales. Noisy, low resolution meshes are captured from a 3D acquisition, while artificial meshes are generated to simulate ideal acquisition conditions. The proposed system shows accurate results in both ideal situations as well as non-ideal situations under the condition of noise and complex surface curvature by extracting only the deformations of interest and accurately classifying them as dings or dents.

This thesis examines an automated method to detect surface deformations on automotive panels for the purpose of quality control along a manufacturing assembly line. Automation in the automotive manufacturing industry is becoming more prominent, but quality control is still largely performed by human workers. Quality control is important in the context of automotive body panels as deformations can occur along the assembly line such as inadequate handling of parts or tools around a vehicle during assembly, rack storage, and shipping from subcontractors. These defects are currently identified and marked, before panels are either rectified or discarded. This work attempts to develop an automated system to detect deformations to alleviate the dependence on human workers in quality control and improve performance by increasing speed and accuracy. Some techniques make use of an ideal CAD model behaving as a master work, and panels scanned on the assembly line are compared to this model to determine the location of deformations. This thesis presents a solution for detecting deformations of various scales without a master work. It also focuses on automated analysis requiring minimal intuitive operator-set parameters and provides the ability to classify the deformations as dings, which are deformations that protrude from the surface, or dents, which are depressions into the surface. A complete automated deformation detection system is proposed, comprised of a feature extraction module, segmentation module, and classification module, which outputs the locations of deformations when provided with the 3D mesh of an automotive panel. Two feature extraction techniques are proposed. The first is a general feature extraction technique for 3D meshes using octrees for multi-resolution analysis and evaluates the amount of surface variation to locate deformations. The second is specifically designed for the purpose of deformation detection, and analyzes multi-resolution cross-sections of a 3D mesh to locate deformations based on their estimated size. The performance of the proposed automated deformation detection system, and all of its sub-modules, is tested on a set of meshes which represent differing characteristics of deformations in surface panels, including deformations of different scales. Noisy, low resolution meshes are captured from a 3D acquisition, while artificial meshes are generated to simulate ideal acquisition conditions. The proposed system shows accurate results in both ideal situations as well as non-ideal situations under the condition of noise and complex surface curvature by extracting only the deformations of interest and accurately classifying them as dings or dents.

This thesis examines an automated method to detect surface deformations on automotive panels for the purpose of quality control along a manufacturing assembly line. Automation in the automotive manufacturing industry is becoming more prominent, but quality control is still largely performed by human workers. Quality control is important in the context of automotive body panels as deformations can occur along the assembly line such as inadequate handling of parts or tools around a vehicle during assembly, rack storage, and shipping from subcontractors. These defects are currently identified and marked, before panels are either rectified or discarded. This work attempts to develop an automated system to detect deformations to alleviate the dependence on human workers in quality control and improve performance by increasing speed and accuracy. Some techniques make use of an ideal CAD model behaving as a master work, and panels scanned on the assembly line are compared to this model to determine the location of deformations. This thesis presents a solution for detecting deformations of various scales without a master work. It also focuses on automated analysis requiring minimal intuitive operator-set parameters and provides the ability to classify the deformations as dings, which are deformations that protrude from the surface, or dents, which are depressions into the surface. A complete automated deformation detection system is proposed, comprised of a feature extraction module, segmentation module, and classification module, which outputs the locations of deformations when provided with the 3D mesh of an automotive panel. Two feature extraction techniques are proposed. The first is a general feature extraction technique for 3D meshes using octrees for multi-resolution analysis and evaluates the amount of surface variation to locate deformations. The second is specifically designed for the purpose of deformation detection, and analyzes multi-resolution cross-sections of a 3D mesh to locate deformations based on their estimated size. The performance of the proposed automated deformation detection system, and all of its sub-modules, is tested on a set of meshes which represent differing characteristics of deformations in surface panels, including deformations of different scales. Noisy, low resolution meshes are captured from a 3D acquisition, while artificial meshes are generated to simulate ideal acquisition conditions. The proposed system shows accurate results in both ideal situations as well as non-ideal situations under the condition of noise and complex surface curvature by extracting only the deformations of interest and accurately classifying them as dings or dents.

This thesis examines an automated method to detect surface deformations on automotive panels for the purpose of quality control along a manufacturing assembly line. Automation in the automotive manufacturing industry is becoming more prominent, but quality control is still largely performed by human workers. Quality control is important in the context of automotive body panels as deformations can occur along the assembly line such as inadequate handling of parts or tools around a vehicle during assembly, rack storage, and shipping from subcontractors. These defects are currently identified and marked, before panels are either rectified or discarded. This work attempts to develop an automated system to detect deformations to alleviate the dependence on human workers in quality control and improve performance by increasing speed and accuracy. Some techniques make use of an ideal CAD model behaving as a master work, and panels scanned on the assembly line are compared to this model to determine the location of deformations. This thesis presents a solution for detecting deformations of various scales without a master work. It also focuses on automated analysis requiring minimal intuitive operator-set parameters and provides the ability to classify the deformations as dings, which are deformations that protrude from the surface, or dents, which are depressions into the surface. A complete automated deformation detection system is proposed, comprised of a feature extraction module, segmentation module, and classification module, which outputs the locations of deformations when provided with the 3D mesh of an automotive panel. Two feature extraction techniques are proposed. The first is a general feature extraction technique for 3D meshes using octrees for multi-resolution analysis and evaluates the amount of surface variation to locate deformations. The second is specifically designed for the purpose of deformation detection, and analyzes multi-resolution cross-sections of a 3D mesh to locate deformations based on their estimated size. The performance of the proposed automated deformation detection system, and all of its sub-modules, is tested on a set of meshes which represent differing characteristics of deformations in surface panels, including deformations of different scales. Noisy, low resolution meshes are captured from a 3D acquisition, while artificial meshes are generated to simulate ideal acquisition conditions. The proposed system shows accurate results in both ideal situations as well as non-ideal situations under the condition of noise and complex surface curvature by extracting only the deformations of interest and accurately classifying them as dings or dents.

Im Luftfahrtbereich haben sich kohlenstofffaserverstärkte Kunststoffe (CFK) wegen ihrer hohen spezifischen Festigkeiten und Steifigkeiten längst als Konstruktionswerkstoffe etabliert. In der Großserienfertigung von Automobilkarosserien kommt diese Materialgruppe jedoch nur zögerlich zum Einsatz. Offensichtlich sprechen noch viele Argumente für den Einsatz von metallischen Werkstoffen: Denn auch Leichtmetalle und pressgehärtete Stähle ermöglichen immer höhere Leichtbaugrade, ohne dabei signifikante Kostensteigerungen zu generieren. Zudem sind Fertigungs- und Montageabläufe für Metallkarosserien etabliert und weitgehend frei von Entwicklungsrisiken. Vor diesem Hintergrund erscheint es schwer, mit neuen Leichtbaumaterialien und den zugehörigen Bauweisen einen Durchbruch erzielen zu können. Dabei zeigt das Produktsegment der Supersportwagen schon deutlich, dass zusätzliche Leichtbaupotentiale durch beanspruchungsgerecht gestaltete und optimierte CFK-Strukturen für den Automobilbau eröffnet werden. Bislang lassen sich derartig optimierte CFK-Strukturen jedoch kaum wettbewerbsfähig in Großserie realisieren. An dieser Stelle ergeben sich Chancen und zugleich neue Herausforderungen für die Produktentwickler: Zum einen sind Faserverbundbauweisen zu erarbeiten, mit denen die Leichtbaupotentiale von CFK weitgehend ausgereizt werden. Zum anderen ist die automatisierte Fertigung bei hohen Taktraten zu ermöglichen. Die Lösung beider Teilaufgaben setzt den Einsatz geeigneter materialspezifischer Konstruktionsmethoden voraus.

M. Tech. (Department of Mechanical Engineering, Faculty of Engineering and Technology), Vaal University of Technology. / The purpose of this study was to develop a design synthesis approach that can be used to reach an optimal design solution (in terms of the strength, stiffness and weight) of automotive body structures during the conceptual stages of the design process. Two conceptual model variants; standard sedan and open-top unitary body structures that were made from the same platform were analysed for their maximum bending moment, stresses, deflections and their maximum load carrying capacity. Topology optimization was also undertaken in order to find a lightweight design of the body structures. The body structures were modelled using three different modelling techniques, namely; the simple beam model, the simple structural surface (SSS) method and the finite element (FE) method. The simple beam model was used to determine the axle reaction forces and the maximum bending moment of a body structure that was subjected to static and dynamic loading conditions. Dynamic load factors and an extra safety factor were used to simulate the dynamic bending loads. The factors were varied from 1.0 to 4.5 with a step of 0.5. It was found that the maximum bending moment under dynamic loading is simply a multiple of the static maximum bending moment and they both occur at a position that is close to the rear part of the front seats. The effects of different geometries on the strength, stiffness and the weight of body structures were studied using the finite element method. The two conceptual models were made into four different plane FE models with each concept having two different FE models. The panels of these models were constructed as simple structural surfaces and were based on the SSS analysis of the standard sedan. The models were subjected to bending and torsion load cases. Each load case was varied similarly for 19 different iterations until the yield point was reached for each FE model. It was also found that the load-displacement graphs were linear for loading within the elastic range, even if there are subassemblies that are missing. However, it was found that this relationship ceases to apply once the body structures are subjected to the torsion loads that are above the yield load. It was also found that the qualitative response to torsion loads was similar for all four body structures. However, the quantitative response was quite observable. It was found that the stiffness can be reduced by at least 37% by omitting subassemblies for the same platform and almost the same mass of the body structure. In addition, the effects of different materials on the strength, stiffness and the weight of body structures were also studied. It was found that lightweight designs can be achieved by using lightweight materials. However, both the bending and torsion stiffness were observed to be reduced or increased in proportion to the Young’s modulus or modulus of elasticity of the material that was used to construct the models. It was also noted that, the stiffness to weight ratio remained almost the same for the same models made from different materials. Topology optimization was undertaken in order to determine alternative load paths of the body structures. The two conceptual models were made into four different solid FE models. It was observed that the load paths remain similar for different volume fraction constraints for similar models under similar loading conditions. It was also noted that at least 20% in weight savings and at least 5% in torsion stiffness improvement can be achieved when topology optimization is used to determine the alternative load paths for a standard sedan model. Besides, the load carrying capacity was found to remain similar. However, the bending stiffness was noted to have reduced due to the reduction in the mass of the structure. In contrast, it was found that for an open-top model, both the bending and torsion stiffnesses were reduced in proportion to the reduction in the mass of the body structure. In addition, it was observed that a further reduction in the mass of the open-top body structure can also significantly reduce its load carrying capacity. Although the stiffness of the optimized open-top model was noted to have reduced due to the reduction in the mass of the structure. The stiffness to weight ratio of the optimized body structure was higher than that of the non-optimal structure.

This investigation identifies how CAD models of typical automotive body assemblies could be defined to allow a continuous optimisation of the number of iterations required for the final design and the number of variants on the basis of Parametric Associative Design (PAD) and how methodologies for the development of surfaces, parts and assemblies of the automotive body can be represented and structured for a multiple re-use in a collaborative environment of concept phase of a Product Evolution (Formation) Process (PEP). The standardisation of optimised processes and methodologies and the enhanced interaction between all parties involved in product development could lead to improve product quality and reduce development time and hence expenses. The fundamental principles of PAD, the particular methodologies used in automotive body design and the principles of methodical development and design in general are investigated. The role which automotive body engineers play throughout the activities of the PEP is also investigated. The distribution of design work in concept teams of automotive body development and important methodologies for the design of prismatic profile areas is critically analysed. To address the role and distribution of work, 25 group work projects were carried out in cooperation with the automotive industry. Large assemblies of the automotive bodies were developed. The requirements for distributed design work have been identified and improved. The results of the investigation point towards a file based, well structured administration of a concept design, with a zone based approach. The investigation was extended to the process chain of sections, which are used for development of surfaces, parts and assemblies. Important methods were developed, optimised and validated with regard to an update safe re-use of 3D zone based CAD models instead of 2D sections. The thesis presents a thorough description of the research undertaken, details the experimental results and provides a comprehensive analysis of them. Finally it proposes a unique methodology to a zone based approach with a clearly defined process chain of sections for an update-safe re-use of design models.