Dieser Beitrag stellt ein neues, hybrides Modell für die Entwicklung mechanischer und mechatronischer Systeme vor. Ziel ist es, die derzeitig bestehende Lücke zwischen abstrakten Funktionsmodellen und sehr konkreten, geometrieorientierten 3D-CAD-Modellen zu überbrücken. Das hier vorgestellte SkiPo-Modell beschreibt die Interaktionen zwischen den Komponenten eines Systems basierend auf den zugehörigen Material-, Energie- und Signalflüssen. Ergänzt wird diese abstrakte Darstellung mit Skizzen, die wichtige Konstruktionsentscheidungen in einer strukturierten, semistandardisierten Weise dokumentieren. Das Ziel dieser hybriden Modellierung ist es, die unvermeidbaren Iterationen zwischen abstrakten und sehr detaillierten Betrachtungen von mechanischen und mechatronischen Systemen in der frühen Phase der Produktentstehung zu unterstützen. In Erprobungen mit Studentengruppen zeigte sich, dass dieser Modellierungsansatz das Verständnis und die Kommunikation im Team fördern kann.

Dieser Beitrag stellt ein neues, hybrides Modell für die Entwicklung mechanischer und mechatronischer Systeme vor. Ziel ist es, die derzeitig bestehende Lücke zwischen abstrakten Funktionsmodellen und sehr konkreten, geometrieorientierten 3D-CAD-Modellen zu überbrücken. Das hier vorgestellte SkiPo-Modell beschreibt die Interaktionen zwischen den Komponenten eines Systems basierend auf den zugehörigen Material-, Energie- und Signalflüssen. Ergänzt wird diese abstrakte Darstellung mit Skizzen, die wichtige Konstruktionsentscheidungen in einer strukturierten, semistandardisierten Weise dokumentieren. Das Ziel dieser hybriden Modellierung ist es, die unvermeidbaren Iterationen zwischen abstrakten und sehr detaillierten Betrachtungen von mechanischen und mechatronischen Systemen in der frühen Phase der Produktentstehung zu unterstützen. In Erprobungen mit Studentengruppen zeigte sich, dass dieser Modellierungsansatz das Verständnis und die Kommunikation im Team fördern kann.

There is shift in the Architectural / Engineering / Construction and Facility Management (AEC&FM) industry toward performance-driven projects. Assuring good performance requires efficient and reliable performance control processes. However, the current state of the AEC&FM industry is that control processes are inefficient because they generally rely on manually intensive, inefficient, and often inaccurate data collection techniques. Critical performance control processes include progress tracking and dimensional quality control. These particularly rely on the accurate and efficient collection of the as-built three-dimensional (3D) status of project objects. However, currently available techniques for as-built 3D data collection are extremely inefficient, and provide partial and often inaccurate information. These limitations have a negative impact on the quality of decisions made by project managers and consequently on project success. This thesis presents an innovative approach for Automated 3D Data Collection (A3dDC). This approach takes advantage of Laser Detection and Ranging (LADAR), 3D Computer-Aided-Design (CAD) modeling and registration technologies. The performance of this approach is investigated with a first set of experimental results obtained with real-life data. A second set of experiments then analyzes the feasibility of implementing, based on the developed approach, automated project performance control (APPC) applications such as automated project progress tracking and automated dimensional quality control. Finally, other applications are identified including planning for scanning and strategic scanning.

There is shift in the Architectural / Engineering / Construction and Facility Management (AEC&FM) industry toward performance-driven projects. Assuring good performance requires efficient and reliable performance control processes. However, the current state of the AEC&FM industry is that control processes are inefficient because they generally rely on manually intensive, inefficient, and often inaccurate data collection techniques. Critical performance control processes include progress tracking and dimensional quality control. These particularly rely on the accurate and efficient collection of the as-built three-dimensional (3D) status of project objects. However, currently available techniques for as-built 3D data collection are extremely inefficient, and provide partial and often inaccurate information. These limitations have a negative impact on the quality of decisions made by project managers and consequently on project success. This thesis presents an innovative approach for Automated 3D Data Collection (A3dDC). This approach takes advantage of Laser Detection and Ranging (LADAR), 3D Computer-Aided-Design (CAD) modeling and registration technologies. The performance of this approach is investigated with a first set of experimental results obtained with real-life data. A second set of experiments then analyzes the feasibility of implementing, based on the developed approach, automated project performance control (APPC) applications such as automated project progress tracking and automated dimensional quality control. Finally, other applications are identified including planning for scanning and strategic scanning.

[pt] Projetos de engenharia dependem de modelos CAD 3D complexos durante todo o seu ciclo de vida. Esses modelos 3D contêm milhões de geometrias que impõem desafios de armazenamento, transmissão e renderização. Trabalhos anteriores empregaram com sucesso técnicas de correspondência de formas baseadas em aprendizado profundo para reduzir a memória exigida por esses modelos 3D. Este trabalho propõe um algoritmo baseado em grafos que melhora o agrupamento não supervisionado em espaços profundos de características. Essa abordagem refina drasticamente a precisão da correspondência de formas e resulta em requisitos de memória ainda mais baixos para os modelos 3D. Em um conjunto de dados rotulado, nosso método atinge uma redução de 95 por cento do modelo, superando as técnicas não supervisionadas anteriores que alcançaram 87 por cento e quase atingindo a redução de 97 por cento de uma abordagem totalmente supervisionada. Em um conjunto de dados não rotulado, nosso método atinge uma redução média do modelo de 87 por cento contra uma redução média de 77 por cento das técnicas não supervisionadas anteriores. / [en] Engineering projects rely on complex 3D CAD models throughout their life cycle. These 3D models comprise millions of geometries that impose storage, transmission, and rendering challenges. Previous works have successfully employed shape-matching techniques based on deep learning to reduce the memory required by these 3D models. This work proposes a graph-based algorithm that improves unsupervised clustering in deep feature space. This approach dramatically refines shape-matching accuracy and results in even lower memory requirements for the 3D models. In a labeled dataset, our method achieves a 95 percent model reduction, outperforming previous unsupervised techniques that achieved 87 percent and almost reaching the 97 percent reduction from a fully supervised approach. In an unlabeled dataset, our method achieves an average model reduction of 87 percent versus an average reduction of 77 percent from previous unsupervised techniques.

This diploma thesis primarily deals with the transmission error issue which is one of the dominant sources of vibration in gear pairs and transmission systems. The vibrations subsequently generate noise which is often subjected to increasingly stricter demands across the industry, including the automotive one. It turns out that reducing the peak-to-peak value of the transmission error has a beneficial effect on the vibro-acoustic properties of gears and gear pairs. This thesis aims to determine the transmission error under static conditions, since a gear pair with a low static transmission error is a good assumption for a low transmission error even under dynamic effects. The resulting values of the transmission error can be influenced already during the design of the gear macro-geometry. It is also suitable to apply micro-geometric adjustments – modifications to the gear teeth. For this reason, the search part of the thesis is dedicated to theoretical knowledge, especially concerning the geometry of gears, modifications of teeth and the overall transmission error and its determination. The transmission error can be determined in several ways, including a technical experiment. However, due to time and financial reasons, this is not always possible, and therefore, the possibility of using numerical simulations is offered. In this thesis, the approach using stress-strain quasi-static contact analysis using the finite element method in Ansys Workbench software is used. The advantage is, among other things, a good comparability of results. The input to the FEM analysis is 3D CAD geometry – in this case, it is specifically a helical gear pair with parallel axes. The model/assembly of this gear pair is created in PTC Creo software fully parametrically, so it is possible to generate arbitrary gear pair configurations by changing the input parameters, which significantly saves time. At the end of this diploma thesis, the stress-strain analysis of various gear configurations is evaluated, with respect to the equivalent stress and contact pressure. Furthermore, the static transmission error – its graphs and peak-to-peak values – is determined from FEM analyses for different gear geometry, including tooth modifications, and for various loading torques. Last but not least, the effects of contact/overlap ratio and centre distance are evaluated.

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