Three-dimensional (3D) non-contact optical methods for surface inspection are of significant interest to many industrial sectors. Many aspects of manufacturing processes have become fully automated resulting in high production volumes. However, this is not necessarily the case for surface defect inspection. Existing human visual analysis of surface defects is qualitative and subject to varying interpretation. Automated 3D non-contact analysis should provide a robust and systematic quantitative approach. However, different 3D optical measurement technologies use different physical principles, interact with surfaces and defects in diverse ways, leading to variation in measurement data. Instrument s native software processing of the data may be non-traceable in nature, leading to significant uncertainty about data quantisation. Sub-millimetric level surface defect artefacts have been created using Rockwell and Vickers hardness testing equipment on various substrates. Four different non-contact surface measurement instruments (Alicona InfiniteFocus G4, Zygo NewView 5000, GFM MikroCAD Lite and Heliotis H3) have been utilized to measure different defect artefacts. The four different 3D optical instruments are evaluated by calibrated step-height created using slipgauges and reference defect artefacts. The experimental results are compared to select the most suitable instrument capable of measuring surface defects in robust manner. This research has identified a need for an automatic tool to quantify surface defect and thus a mathematical solution has been implemented for automatic defect detection and quantification (depth, area and volume) in 3D. A simulated defect softgauge with a known geometry has been developed in order to verify the implemented algorithm and provide mathematical traceability. The implemented algorithm has been identified as a traceable, highly repeatable, and high speed solution to quantify surface defect in 3D. Various industrial components with suspicious features and solder joints on PCB are measured and quantified in order to demonstrate applicability.

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Product visual inspection is still performed manually or semi automatically in most industries from simple ceramic tile grading to complicated automotive body panel paint defect and surface quality inspection. Moreover, specular surfaces present additional challenges to conventional vision systems due to specular reflections, which may mask the true location of objects and lead to incorrect measurements. Some sophisticated optical inspection methods have already been developed for high precision surface defect inspection in recent years. Unfortunately, most of them are highly computational. Systems built on those methods are either inapplicable or costly to achieve real-time inspection. This thesis describes an integrated low-cost intelligent system developed to automatically capture and extract regular defects of the ceramic tiles with uniformly colored specular coatings. The proposed system is implemented on a group of smart cameras using its on-board processing ability to achieve real-time inspection. The results of this study will be used to facilitate the design of a robust, low-cost, closed-loop inspection system for a class of products with smooth specular coatings. The experimental results on real test panels demonstrate the effectiveness and robustness of proposed system.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第24443号 / 理博第4942号 / 新制||理||1706(附属図書館) / 京都大学大学院理学研究科化学専攻 / (主査)教授 若宮 淳志, 教授 依光 英樹, 教授 畠山 琢次 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Optical three dimensional (3D) mapping routines are used in inspection robots to detect faults by creating 3D reconstructions of environments. To detect surface faults, sub millimeter depth resolution is required to determine minute differences caused by coating loss and pitting. Sensors that can detect these small depth differences cannot quickly create contextual maps of large environments. To solve the 3D mapping problem, a sensor fused approach is proposed that can gather contextual information about large environments with one depth sensor and a SLAM routine; while local surface defects can be measured with an actuated optical profilometer. The depth sensor uses a modified Kinect Fusion to create a contextual map of the environment. A custom actuated optical profilometer is created and then calibrated. The two systems are then registered to each other to place local surface scans from the profilometer into a scene context created by Kinect Fusion. The resulting system can create a contextual map of large scale features (0.4 m) with less than 10% error while the optical profilometer can create surface reconstructions with sub millimeter resolution. The combination of the two allows for the detection and quantification of surface faults with the profilometer placed in a contextual reconstruction. / Master of Science

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In traditional industrial manufacturing, due to the limitations of science and technology, manual inspection methods are still used to detect product surface defects. This method is slow and inefficient due to manual limitations and backward technology. The aim of this thesis is to research whether it is possible to automate this using modern computer hardware and image classification of defects using different deep learning methods. The report concludes, based on results from controlled experiments, that it is possible to achieve a dice coefficient of more than 81%.

Il été prouvée dans plusieurs études de la littérature que la taille d'un composant affecte sa tenue en fatigue et cette tendance est plus prononcée dans le régime de fatigue à grand nombre de cycles. Plus précisément, une baisse de la limite de fatigue est observée et est souvent expliquée par l’augmentation, avec l’augmentation du volume sollicité, de la probabilité de trouver un défaut critique ou une zone plus faible dans le matériau. Le présent mémoire fait partie d'un projet de recherche français (QUAUSI) regroupant plusieurs partenaires industriels et académiques qui vise à contrôler la qualité d'usinage des composants structuraux d'avions. Un des défis consiste à définir un critère approprié d'acceptabilité de défauts pour la conception en FGNC. Le critère doit être capable de prendre en compte une large gamme de défauts de surface et de composants de tailles et de géométries différentes. L'objectif principal étant de mieux comprendre l'impact des états de surface périodiques (caractéristique du type d'usinage utilisé) sur la limite de fatigue, Il a fallu d'abord vérifier si un effet de taille peut être observé quand un nombre croissant de défauts de surface simples sont introduits à la surface d'échantillons polis. Le matériau d’étude est l’alliage d'aluminium 7050 (Al Zn6CuMgZr). Une grande campagne d'essais de fatigue sous charge de flexion plane à R=-1 est effectuée sur des éprouvettes présentant des défauts hémisphériques, de différents tailles et nombres, et des états de surface usinés. Les résultats des essais ont permis de caractériser à la fois l'effet Kitagawa et l'effet d'échelle sur la tenue fatigue. Une approche probabiliste basée sur le concept du maillon le plus faible associé à un critère d'amorçage de fissure de fatigue approprié est utilisée pour prendre en compte la répartition des contraintes et la taille du volume fortement sollicité. Les prédictions utilisant des simulations EF montrent un bon accord avec les résultats expérimentaux et illustrent l'importance de prendre en compte l'effet d'échelle lors de la conception de composants contenant différents types de défauts de surface ou de motifs de rugosité.Mots-clés : Défaut de surface, fatigue à grand nombre de cycles, diagramme de Kitagawa-Takahashi, Le plus faible concept de lien, alliage AA7050 / The size of a component has been proved in several studies of the literature to affect the fatigue strength and this trend is known to be more pronounced in the High Cycle Fatigue regime. More exactly a drop of the fatigue limit is observed and this evolution is very often explained by the probability to find a critical defect or a weakest zone in the material as the stressed volume rises. The present manuscript is part of a French research project gathering several industrial and academic partners that aims to control the machining quality of aircraft structural components. For one part of the project the challenge is to define a proper defect acceptability criterion for HCF design purpose. It must be able to account for a large range of surface defects and of component sizes and geometries. Even though the primary objective was to better understand the impact of periodic surface micro-geometry patterns (characteristic of the type of machining used) on the fatigue limit, we thought that it was first necessary to check if a size effect can be observed when an increasing number of artificial simplified surface defects are introduced at the surface of smooth specimens. The aeronautical material under investigation is a 7050 Aluminum alloy (Al Zn6CuMgZr). A large fatigue testing campaign under fully reversed plane bending loading is undertaken on specimens with artificial surface hemispherical defects. Defect number varies from 1 to 44 per specimen whereas their size ranges from 60 µm to 800 µm. Testing results allow the characterization of both Kitagawa effect and scale effect on the fatigue response. A probabilistic approach based on the weakest link concept together with a proper fatigue crack initiation criterion is used to account for the stress distribution and the size of the highly stressed volume. Predictions using FE simulations show a good agreement with experimental results and illustrate the importance of taking the scale effect into account while designing components containing different types of surface defects or roughness patterns.Keywords : Surface defect, HCF, Kitagawa-Takahashi diagram, Weakest link concept, AA7050 alloy.

<p>The development and improvement of the functionality of metal oxides in heterogeneous catalysis and other surface chemical processes can greatly benefit from an atomic-level understanding of the surface chemistry. Atomistic calculations such as quantum mechanical (QM) calculations and molecular dynamics (MD) simulations can provide highly detailed information about the atomic and electronic structure, and constitute valuable complements to experimental surface science techniques. </p><p>In this thesis, an embedded-cluster approach for quantum mechanical calculations has been developed to model the surface chemistry of metal oxides. In particular, CO adsorption on the MgO(001) and CeO₂(110) surfaces as well as O vacancy formation at the CeO₂(110) surface have been investigated. The cluster model has been thoroughly tested by comparison with electronic structure calculations for the periodic slab model.</p><p>The chemical implications of distorted surface structures arising from the surface dynamics have been investigated by combining the QM embedded-cluster calculations with force-field based MD simulations. Here QM embedded-cluster calculations were performed using surface structures sampled from the MD simulations.</p><p>This combined MD+QM embedded-cluster procedure was applied to the CO adsorption on MgO(001) at 50 K and the O vacancy formation on CeO₂(110) at 300 K. Significant thermal variations of the CO adsorption energy and the O vacancy formation energy were observed. It was found that these variations could be estimated using the force field of the MD simulation as an interaction model. With this approach, the QM results were extrapolated to higher temperature and doped systems.</p>