This work deals with the metal surface wetting problems of molten lead-free solder and monitoring of ongoing processes at the inter-phase interface using the method of evaluation of the height of the molten solder deducted from the video sequences. The work is aimed at evaluating the metal surface wettability, wetting angle determined. Wettability of the metal surface is compared for different types of surface treatments and for different ages of the measured samples. Measurement is performed at the improved workplace, is used to evaluate the newly derived formula for calculating the wetting angle and created program for automatic evaluation of Picture is used to.

The master thesis analyses electrical conductivity of lead-free solder joints. The test method design for monitoring the electrical conductivity of the soldered joint is described in the practical part. Simulated BGA package with four pin (BGA4) is used for experiments. Tested PCBs are subjected to isothermal aging and current load. During isothermal aging is measured electrical conductivity and optical microscope is used for intermetallic layer (IMC) growth observation. Two types of surface finish (OSP and ENIG) are used for tests and three diameters of solder terminal balls (solder alloy SAC405). The influence of the ratio area connection / solder volume (ratio S / V) on lead-free solder joints conductivity was evaluated.

This thesis is focused on BGA packages and fault detection after rework using X – Ray. There is a description of BGA packages by carrier substrate, techniques of connecting on chip, from mounting packages to repair printed circuit boards (hereafter PCB). Thesis summarizes description of defects, which are created after rework process. There is also description of X – Ray as method for analyzing defects. X – PLANE method used to detect internal structure of BGA packages and it was confirmed by microsection and by software for reconstruction. Description of automatic and manual measurement is follow.

Convolutional Neural Network (CNN) has been established as a powerful toolto automate various computer vision tasks without requiring any aprioriknowledge. Printed Circuit Board (PCB) manufacturers want to improve theirproduct quality by employing vision based automatic optical inspection (AOI)systems at PCB assembly manufacturing. An AOI system employs classiccomputer vision and image processing techniques to detect variousmanufacturing faults in a PCB assembly. Recently, CNN has been usedsuccessfully at various stages of automatic optical inspection. However, nonehas used 2D image of PCB assembly directly as input to a CNN. Currently, allavailable systems are specific to a PCB assembly and require a lot ofpreprocessing steps or a complex illumination system to improve theaccuracy. This master thesis attempts to design an effective soldering faultdetection system using CNN applied on image of a PCB assembly, withRaspberry Pi PCB assembly as the case in point.Soldering faults detection is considered as equivalent of object detectionprocess. YOLO (short for: “You Only Look Once”) is state-of-the-art fast objectdetection CNN. Although, it is designed for object detection in images frompublicly available datasets, we are using YOLO as a benchmark to define theperformance metrics for the proposed CNN. Besides accuracy, theeffectiveness of a trained CNN also depends on memory requirements andinference time. Accuracy of a CNN increases by adding a convolutional layer atthe expense of increased memory requirement and inference time. Theprediction layer of proposed CNN is inspired by the YOLO algorithm while thefeature extraction layer is customized to our application and is a combinationof classical CNN components with residual connection, inception module andbottleneck layer.Experimental results show that state-of-the-art object detection algorithmsare not efficient when used on a new and different dataset for object detection.Our proposed CNN detection algorithm predicts more accurately than YOLOalgorithm with an increase in average precision of 3.0%, is less complexrequiring 50% lesser number of parameters, and infers in half the time takenby YOLO. The experimental results also show that CNN can be an effectivemean of performing AOI (given there is plenty of dataset available for trainingthe CNN). / Convolutional Neural Network (CNN) har etablerats som ett kraftfullt verktygför att automatisera olika datorvisionsuppgifter utan att kräva någon apriorikunskap. Printed Circuit Board (PCB) tillverkare vill förbättra sinproduktkvalitet genom att använda visionbaserade automatiska optiskainspektionssystem (AOI) vid PCB-monteringstillverkning. Ett AOI-systemanvänder klassiska datorvisions- och bildbehandlingstekniker för att upptäckaolika tillverkningsfel i en PCB-enhet. Nyligen har CNN använts framgångsrikti olika stadier av automatisk optisk inspektion. Ingen har dock använt 2D-bildav PCB-enheten direkt som inmatning till ett CNN. För närvarande är allatillgängliga system specifika för en PCB-enhet och kräver mångaförbehandlingssteg eller ett komplext belysningssystem för att förbättranoggrannheten. Detta examensarbete försöker konstruera ett effektivtlödningsfelsdetekteringssystem med hjälp av CNN applicerat på bild av enPCB-enhet, med Raspberry Pi PCB-enhet som fallet.Detektering av lödningsfel anses vara ekvivalent medobjektdetekteringsprocessen. YOLO (förkortning: “Du ser bara en gång”) ärdet senaste snabba objektdetekteringen CNN. Även om det är utformat förobjektdetektering i bilder från offentligt tillgängliga datasätt, använder viYOLO som ett riktmärke för att definiera prestandametriken för detföreslagna CNN. Förutom noggrannhet beror effektiviteten hos en tränadCNN också på minneskrav och slutningstid. En CNNs noggrannhet ökargenom att lägga till ett invändigt lager på bekostnad av ökat minnesbehov ochinferingstid. Förutsägelseskiktet för föreslaget CNN är inspirerat av YOLOalgoritmenmedan funktionsekstraktionsskiktet anpassas efter vår applikationoch är en kombination av klassiska CNN-komponenter med restanslutning,startmodul och flaskhalsskikt.Experimentella resultat visar att modernaste objektdetekteringsalgoritmerinte är effektiva när de används i ett nytt och annorlunda datasätt förobjektdetektering. Vår föreslagna CNN-detekteringsalgoritm förutsäger merexakt än YOLO-algoritmen med en ökning av den genomsnittliga precisionenpå 3,0%, är mindre komplicerad som kräver 50% mindre antal parametraroch lägger ut under halva tiden som YOLO tar. De experimentella resultatenvisar också att CNN kan vara ett effektivt medel för att utföra AOI (med tankepå att det finns gott om datamängder tillgängliga för utbildning av CNN)

Eine kompakte Integration der Leistungselektronik in einem Fahrzeuggetriebe des Hybridfahrzeugs stellt hohe Anforderungen an die Lastwechselfestigkeit der Halbleiter-Leistungsmodule. Gefordert wird die Auslegung für die Kühlmitteltemperatur von 125°C und für die Sperrschichttemperatur von 200°C. Für die Untersuchung der Lastwechselfestigkeit bei geforderten hohen Temperaturen werden neue Prüfstandskonzepte und Messmethoden vorgestellt. Mit realisierten Testständen wird die Lastwechselfestigkeit der neuen Aufbau- und Verbindungstechnologien „gehärtete Aluminiumbonddrähte”, „Diffusionslöten”, „Lötung mit vertikalen Strukturen” und „Niedertemperatur-Verbindungstechnik” untersucht. / High power density of the power electronics in a hybrid electric vehicle demands a high power cycling capability of the semiconductor power module. Requirements are: 125°C coolant and 200°C junction temperature. For the investigation of the power cycling capability at high temperatures new test benches and measurement methods are introduces. With realized methods the reliability of following new interconnection technologies is investigated: doped aluminium bond wires, diffusion soldering, solder layer with vertical microstructures, low temperature sinter technology.

FA; UTFPR; RENAULT / Linhas robóticas de solda são comuns na indústria automobilística. Durante a produção de um veículo, sua estrutura metálica precisa ser soldada em um único corpo resistente. Isso é feito por meio de centenas de soldas a ponto por resistência, cada uma liga localmente duas ou mais placas metálicas. Distribuir eficientemente esses pontos entre robôs é particularmente desafiador, levando em conta que: cada robôs podem fazer acessar uma parte dos pontos de solda, há tempo de movimentação entre pontos e robôs podem colidir entre si se ocuparem o mesmo espaço físico ao mesmo tempo. Há muitas maneiras factíveis de distribuir pontos de solda. No entanto, cada uma gera um resultado econômico diferente: Se um robô soldar muitos pontos se tornará um gargalo e reduzirá a taxa média de produção.Obter o conjunto de decisões operacionais que gera o melhor desempenho é o objetivo de técnicas de otimização. Há uma ampla variedade de técnicas descritas na literatura de pesquisa operacional e ciência da computação: modelos matemáticos, algoritmos, heurísticas, meta-heurísticas, etc. No contexto industrial, tais técnicas foram adaptadas para diversas variantes de problemas práticos. No entanto, estas adaptações só podem resolver as variantes para as quais foram idealizadas. Se por um lado podem se traçar paralelos entre vários aspectos de linhas robóticas de solda e tais variantes, por outro o conjunto completo de características das linhas estudadas não é tratável por (ou convertível em) nenhuma delas. A presente dissertação desenvolve uma abordagem para otimizar tais linhas, baseada em um modelo de programação linear inteira mista desenvolvido para descrever o problema. Ela também apresenta um estudo de caso para discutir e ilustrar possíveis dificuldades de aplicação e como superá-las. O modelo apresentado foi aplicado a dados de uma linha robótica de solda da fábrica, composta por quarenta e dois robôs, quatro modelos de veículos e mais de setecentos pontos de solda por veículo. A média ponderada da redução em tempo de ciclo obtida pelo modelo foi de 17.5%. Variantes do modelo, concebidas para auxiliar trabalhos futuros, são apresentadas e discutidas. / Robotic welding manufacturing lines are production lines common in automobile industries. During a vehicle's production, the vehicle's metal structure must be welded in a single resistant body. This is made by hundreds of spot-welding points, each of which tie locally two or more metal plates. Efficiently distributing these welding points amongst robots is particularly challenging, taking in account that: not all robots can perform all weld points, robots must move their welding tools between weld points, and robots might interfere with one another if they use the same geometrical space. There are multiple feasible manners to distribute the welding points. However, each of these forms generates different economical results: If a robot performs too many points, it will become a line bottleneck and reduce average throughput. To find the set of operational decisions that yields the best output is the goal of optimization techniques. There are a wide variety of such techniques described in operations research and computer sciences literature: mathematical models, algorithms, heuristics, meta-heuristics, etc. In the industrial context, these techniques were adapted to related line balancing problems. However, these adaptations can only solve the specific variants they were designed to address. While parallels can be drawn between aspects of robotic welding lines and many of such variants, the full combined set of characteristics of the studied lines is not treatable by (or convertible to) any of them. This dissertation develops a framework to optimize such lines, based on mixed-integer linear programing model developed to describe the problem. It also presents a case study to discuss and illustrate possible difficulties and how to overcome them. The presented model was applied to data from the factory's robotic welding lines composed of forty-two robots (divided in thirteen stations), four vehicle models and over seven hundred welding points for each vehicle. The weighted average reduction percentage in cycle time obtained by the model was 17.5%. Model variants, designed to aid further works are presented and discussed.

This thesis contains a complete description of the design and implementation of a 500W transformer soldering station. This soldering station includes a half-bridge DC/DC converter with a pulse transformer. The device works with a very low voltage and extremely high output current. Therefore some parts have a special design to ensure the proper equipment function. Coaxial transformer with very low leakage inductance (nH units) is unusual. A synchronous rectifier is another special feature working with low voltage and high output current of the transformer. The finished functional prototype consists of a soldering station and a soldering adapter.

The aim of this project is using the CAE system to analyze the distribution of the temperature profile brazing furnace DIMA 0180. To create the model is used SolidWorks Premium 2012. The simulation is performed using the Flow Simulation. This work builds on the knowledge diploma thesis by Martin Procházka titled The effect of different heat capacities and components on the longitudinal temperature profile for reflow soldering. We start from the knowledge of heat transfer, especially of heat conduction and radiation, which appear in the furnace.

Eine kompakte Integration der Leistungselektronik in einem Fahrzeuggetriebe des Hybridfahrzeugs stellt hohe Anforderungen an die Lastwechselfestigkeit der Halbleiter-Leistungsmodule. Gefordert wird die Auslegung für die Kühlmitteltemperatur von 125°C und für die Sperrschichttemperatur von 200°C. Für die Untersuchung der Lastwechselfestigkeit bei geforderten hohen Temperaturen werden neue Prüfstandskonzepte und Messmethoden vorgestellt. Mit realisierten Testständen wird die Lastwechselfestigkeit der neuen Aufbau- und Verbindungstechnologien „gehärtete Aluminiumbonddrähte”, „Diffusionslöten”, „Lötung mit vertikalen Strukturen” und „Niedertemperatur-Verbindungstechnik” untersucht. / High power density of the power electronics in a hybrid electric vehicle demands a high power cycling capability of the semiconductor power module. Requirements are: 125°C coolant and 200°C junction temperature. For the investigation of the power cycling capability at high temperatures new test benches and measurement methods are introduces. With realized methods the reliability of following new interconnection technologies is investigated: doped aluminium bond wires, diffusion soldering, solder layer with vertical microstructures, low temperature sinter technology.

Quenching and partitioning (Q&P) steels show a good balance between strength and ductility due to a special heat treatment that allows to adjust a microstructure of martensite with a fraction of stabilized retained austenite. The final heat treatment step is performed at low temperatures. Therefore, joining of Q&P steels is a big challenge. On the one hand, a low joining temperature is necessary in order not to influence the adjusted microstructure; on the other hand, high joint strengths are required. In this study, joining of Q&P steels with Ag nanoparticles is investigated. Due to the nano-effect, high-strength and temperature-resistant joints can be produced at low temperatures with nanoparticles, which meets the contradictory requirements for joining of Q&P steels. In addition to the Ag nanoparticles, activating materials (SnAg and Sn) are used at the interface to achieve an improved bonding to the steel substrate. The results show that the activating materials play an important role in the successful formation of joints. Only with the activating materials, can joints be produced. Due to the low joining temperature (max. 237 °C), the microstructure of the Q&P steel is hardly influenced.