This study aims to research variation at a startup company and to understand what methods are necessary to root out and eliminate quality issues. The study is conducted at Biotech AB which is a producer of Bio-instruments as well as bio-ingredients that are produced on site for customers. The company has been concerned with the amount of variation in internal quality coming from the production and the purpose of this study is to find what is causing the variations and what preventative actions need to be taken. This study has been a mix between a quantitative and a qualitative study with its base being around the records of errors given through quality logs. Several interviews were made as well as observations in working procedures and working instructions. The results showed that five major issues were causing the most concern and unnecessary cycles in production, namely featured parts and human error also cause these variations. The interviews indicated that processes need to be managed better and faster due to the rapid pace of the company growth. They also indicate that the communication doesn't always work and needs to flow freely in both directions. The level of waste is quite high in forms of physical waste and time wasted due to cycles in production. Lean thinking needs to be implemented and 5s needs to be made aware of to give everyone a quality and waste-free working ethic from the ground up. Many of these issues could be solved by implementing a quality perspective by giving constant feedback according to TQM.

In connection with the Russian invasion of Ukraine in 2014, the building of the Swedish total defence was brought to the fore. In its focus, the Swedish government has emphasized total defence should be resilient to external threats, but without defining the concept of resilience. This study takes its starting point in trying to identify key actors' interpretation of the concept of resilience by studying key policy documents related to the development of the Swedish total defence through a qualitative text analysis. Through a theory-consuming approach, a theoretical framework has been constructed that broadens the concept of resilience in a security policy context to identify both explicit and implicit statements and representations from each actor's policy document. To identify possible differences, scientific definitions of resilience are adopted as an indicator to visualize each actor's presentation of the concept of resilience. These indicators are engineering resilience, ecological resilience, and evolutionary resilience. The results of the study show that there are differences between the central actors, the politicians, the Authority for civil protection and emergency preparedness (MSB), and the Swedish Armed Forces, in the presentation and interpretation of the concept of resilience, which may have a negative impact in implementing resilience throughout the Swedish total defence system.

The classic nonparametric confidence intervals for a difference or ratio of medians assume that the distributions of the response variable or the log-transformed response variable have identical shapes in each population. Asymptotic distribution-free confidence intervals for a difference and ratio of medians are proposed which do not require identically shaped distributions. The new asymptotic methods are easy to compute and simulation results show that they perform well in small samples.

Space-Time Adaptive Processing is a signal processing technique that uses an adaptive array to help remove nonhomogeneous data points from a dataset. Since the early 1970s, STAP has been used in radar systems for their ability to "filter clutter, interference and jamming signals. One major flaw with early STAP radar systems is the reliance on non-robust estimators to estimate the noise condition. When even a single outlier is present, the earliest STAP radar systems would break down, causing the target to be missed. Many algorithms have been developed to successfully estimate the noise condition of the dataset when outliers are present. As recently as 2007, a STAP radar processing system based on Adaptive Complex Projection Statistics has been proposed and successfully"filters out the noise condition even when outliers are present. However, this algorithm requires the data to be entirely real. Radar data, which consists of amplitude and phase, is complex valued. Therefore, it must be converted into its rectangular components before processing can commence. This introduces many additional processing steps which significantly increase the computing time. The STAP radar algorithm of this thesis overcomes the problems with early radar systems. It is based on the Complex GM Wiener Filter (CGMWF) with the Minimum Covariance Determinant (MCD) for outlier detection. The robustness of the conventional Wiener "lter is enhanced by robust Huber Estimator, and using the MCD enables processing entirely in the complex domain. This results in a STAP radar algorithm with a breakdown point of nearly 35% and that enables processing entirely in the complex domain for fewer computing steps. / Master of Science

A mathematical model of a small fixed-wing aircraft was developed through application of parameter estimation techniques to simulated flight test data. Multiple controllers were devised based on this model for path following, including a self-scheduled linear parameter-varying (LPV) controller with path curvature as a scheduling parameter. The robustness and performance of these controllers were tested in a rigorous MATLAB simulation environment that included steady winds and gusts, measurement noise, delays, and model uncertainties. The linear controllers designed within were found to be robust to the disturbances and uncertainties in the simulation environment, and had similar or better performance in comparison to a nonlinear control law operating in an inner-outer loop structure. Steps are being taken to implement the resulting controllers on the unmanned aerial vehicle (UAV) testbed in the Nonlinear Systems Laboratory at Virginia Tech. / Master of Science

A novel hierarchical flexing and stretching strategy for rigid semiconducting substrates was devised. Architectures for comprehensively compliant semiconductors were created as a result. Si and GaN-on-Si have been segmented into both highly flexible and rigid segments. An advanced controlled cleavage technique has been integrated into the manufacturing process. The bending radius of the substrate has been decoupled from the substrate thickness thus allowing for higher mechanical stability, while achieving bending radii below 250 .m. Novel fabrication workflows have been created, one of which is completely compatible with CMOS fabrication techniques, while still being cost effective. Each of the rigid segments have been designed to carry in excess of its own weight. The reliability of the interconnecting springs was examined by rugged cyclic bending and twisting tests. Finite element simulations in COMSOL exhibited no stress for the rigid segments. For the first time a flexible and/or stretchable Si substrate has been integrated with pick and place tool technology. Additionally the platform serves as a More-than-Moore technology, by folding the monocrystalline substrate on top of itself, while routing power through the flexible segments. This More-than-Moore (MtM) technology has the advantages of System-in-Package (SiP) but does not have the additional costs. From this compliant approach a qubic 4D electronic platform was created. An aerially deployable electronic system was achieved by incorporating thermal paste into the qubic platform. Energy storage, sensing, and actuating were successfully tested on the system. Buried cavities for microfluidics were developed for on-chip chemical and biological processes. A platform was developed for µTF-SOFCs deposition. Cavities were interconnected subterraneously and columnar anodes were developed to enhance the fuel flow in the fuel cell electrode. The triple phase boundary (TPB) was enhanced by over an order of magnitude in comparison to standard processing techniques. A subsequent, microfluidic platform was developed for biological applications. The wettability of the platform gave good results for water, as well as for neurobasal media buffer. Tests indicate that neurons can grow directly on the platform.

Modeling extreme events is one of the central tasks in risk management and planning, as catastrophes and crises put human lives and financial assets at stake. A common approach to estimate the likelihood of extreme events, using extreme value theory (EVT), studies the asymptotic behavior of the ``tail" portion of data, and suggests suitable parametric distributions to fit the data backed up by their limiting behaviors as the data size or the excess threshold grows. We explore an alternate approach to estimate extreme events that is inspired from recent advances in robust optimization. Our approach represents information about tail behaviors as constraints and attempts to estimate a target extremal quantity of interest (e.g, tail probability above a given high level) by imposing an optimization problem to find a conservative estimate subject to the constraints that encode the tail information capturing belief on the tail distributional shape. We first study programs where the feasible region is restricted to distribution functions with convex tail densities, a feature shared by all common parametric tail distributions. We then extend our work by generalizing the feasible region to distribution functions with monotone derivatives and bounded or infinite moments. In both cases, we study the statistical implications of the resulting optimization problems. Through investigating their optimality structures, we also present how the worst-case tail in general behaves as a linear combination of polynomial decay tails. Numerically, we develop results to reduce these optimization problems into tractable forms that allow solution schemes via linear-programming-based techniques.

Dans cette thèse, nous nous intéressons à l’optimisation robuste. Plus précisément,nous nous intéresserons aux problèmes linéaires mixtes bi-niveaux, c’est à dire aux problèmes dans lesquels le processus de décision est divisé en deux parties : dans un premier temps, les valeurs optimales des variables dites "de décisions" seront calculées ; puis, une fois que l’incertitude sur les données est levée, nous calculerons les valeurs des variables dites "de recours". Dans cette thèse, nousnous limiterons au cas où les variables de deuxième étape, dites "de recours", sontcontinues.Dans la première partie de cette thèse, nous nous concentrerons sur l’étudethéorique de tels problèmes. Nous commencerons par résoudre un problème linéairesimplifié dans lequel l’incertitude porte seulement sur le membre droit descontraintes, et est modélisée par un polytope bien particulier. Nous supposerons enoutre que le problème vérifie une propriété dite "de recours complet", qui assureque, quelles que soient les valeurs prises par les variables de dcisions, si ces dernières sont admissibles, alors le problème admet toujours une solution réalisable, et ce, quelles que soient les valeurs prises par les paramètres incertains. Nous verrons alors une méthode permettant, à partir d’un programme robuste quelconque, de se ramener à un programme robuste équivalent dont le problème déterministe associévérifie la propriété de recours complet. Avant de traiter le cas général, nous nouslimiterons d’abord au cas o les variables de décisions sont entières. Nous testeronsalors notre approche sur un problème de production. Ensuite, après avoir remarquéque l’approche développée dans les chapitres précédents ne se généralisait pasnaturellement aux polytopes qui n’ont pas des points extrmes 0-1, nous montreronscomment, en utilisant des propriétés de convexité du problème, résoudre le problème robuste dans le cas général. Nous en déduirons alors des résultats de complexité sur le problème de deuxième étape, et sur le problème robuste. Dans la suite de cette partie nous tenterons d’utiliser au mieux les informations probabilistes que l’on a sur les données aléatoires pour estimer la pertinence de notre ensemble d’incertitude.Dans la deuxième partie de cette thèse, nous étudierons un problème de conceptionde parc hybride de production d’électricité. Plus précisément, nous chercheronsà optimiser un parc de production électrique constitué d’éoliennes, de panneauxsolaires, de batteries et d’un générateur à diesel, destiné à répondre à unedemande locale d’énergie électrique. Il s’agit de déterminer le nombre d’éoliennes,de panneaux solaires et de batteries à installer afin de répondre à la demande pourun cot minimum. Cependant, les données du problème sont très aléatoires. En effet,l’énergie produite par une éolienne dépend de la force et de la direction du vent ; celle produite par un panneau solaire, de l’ensoleillement et la demande en électricité peut tre liée à la température ou à d’autres paramètres extérieurs. Pour résoudre ce problème, nous commencerons par modéliser le problème déterministeen un programme linéaire mixte. Puis nous appliquerons directement l’approche de la première partie pour résoudre le problème robuste associé. Nous montrerons ensuite que le problème de deuxième étape associé, peut se résoudre en temps polynomial en utilisant un algorithme de programmation dynamique. Enfin, nous donnerons quelques généralisations et améliorations pour notre problème. / Robust optimization is a recent approach to study problems with uncertain datathat does not rely on a prerequisite precise probability model but on mild assumptionson the uncertainties involved in the problem.We studied a linear two-stage robustproblem with mixed-integer first-stage variables and continuous second stagevariables. We considered column wise uncertainty and focused on the case whenthe problem doesn’t satisfy a "full recourse property" which cannot be always satisfied for real problems. We also studied the complexity of the robust problemwhich is NP-hard and proved that it is actually polynomial solvable when a parameterof the problem is fixed.We then applied this approach to study a stand-alonehybrid system composed of wind turbines, solar photovoltaic panels and batteries.The aim was to determine the optimal number of photovoltaic panels, wind turbinesand batteries in order to serve a given demand while minimizing the total cost of investment and use. We also studied some properties of the second stage problem, in particular that the second stage problem can be solvable in polynomial time using dynamic programming.

The unmanned aerial vehicles (UAVs) are also known as drones. Recently, UAVs have attracted the next generation researchers due to their flexible, dynamic, and cost-effective deployment, etc. Moreover, the UAVs have a wide range of application domains, such as rescue operation in the remote area, military surveillance, emergency application, etc. Given the UAVs are appropriately deployed, the UAVs provide continuous and reliable connectivity, on-demand, and cost-effective features to the desired destination in the wireless communication system. Thus, the UAVs can be a great choice to deploy as a mobile relay in co-existence with the base stations (BSs) on the ground to serve the 5G wireless users. In this thesis, the UAV-assisted mobile relay (UAV-MR) in the next generation wireless networks has been studied, which also considers the UAV-MR physical layer security. The proposed system also considers one ground user, one BS on the ground, and active presence of multiple eavesdroppers, situated nearby the ground user. The locations of these nodes (i.e., the ground user, the BS, and the eavesdroppers) are considered fixed on the ground. Moreover, the locations of the eavesdroppers are not precisely known to the UAV-MR. Thus, this thesis aims to maximize the achievable secrecy rate, while the BS sends the secure information to the ground user via the UAV-MR. However, the UAV-MR has some challenges to deploy in wireless networks, such as 3D deployment, robust resource allocation, secure UAV-MR to ground communication, the channel modeling, the UAV-MR flight duration, and the UAV-MR robust trajectory design, etc. Thus, this project investigates the UAV-MR assisted wireless networks, which addresses those technical challenges to guarantee efficient UAV-MR communication. Moreover, the mathematical frameworks are formulated to support the proposed model. An efficient algorithm is proposed to maximize the UAV-MR achievable secrecy rate. Finally, the simulation results show the improved performance for the UAV-MR assisted next-generation networks.

La thèse se compose de quatre chapitres, qui discutent les différents aspects d'élaboration de politique macroéconomique dans le contexte d'incertitude. Le premier chapitre est consacré à la politique monétaire robuste dans une union monétaire. Un grand nombre de recherches révèle l'importance de chocs spécifiques du pays pour la politique optimale dans une union monétaire. Cependant, ces chocs n'ont pas été étudiés par la littérature sur la politique optimale dans le contexte d'incertitude. Ainsi, le but principal de ce chapitre est de remplir cet espace et montrer que les asymétries entre les régions doivent être tenues en compte en élaborant la politique monétaire robuste. Dans notre recherche, nous utilisons un modèle New-Keynesian d'une union de deux pays qui est frappée par les chocs asymétriques. Pour ce modèle, nous tirons la politique monétaire robuste qui est raisonnablement bonne même pour le worst-case modèle. Nous trouvons l'effet d'atténuation d'incertitude en cas des chocs dans une région avec la plus forte stickiness des prix. Cela signifie que la banque centrale réagit à ces chocs moins agressivement quand l'incertitude est plus haute. Pour les chocs dans une région avec les prix plus flexibles, nous constatons une anti-atténuation effet de l'incertitude. Le deuxième chapitre explore le rôle de préférences gouvernementales incertaines dans un modèle d'interactions de politique monétaire et fiscale. Nous montrons que les effets d'incertitude de préférences sont liés à l'incertitude multiplicative de l'efficacité de politique. Si les effets de politiques monétaires et fiscales sont connus, l'incertitude de préférences n'alterne pas le résultat de symbiose d'interaction. Dans ce cas-là, l'inflation et la production sont égales à leurs cibles. L'incertitude multiplicative des effets de politique fiscale crée l'excès d'inflation. L'incertitude des effets de politique monétaire crée soit l'excès d'inflation soit l'excès d'inflation négatif avec la production plus haut que la cible et l'inflation plus bas que la cible. Dans ce cas-là, l'incertitude de préférences élargit la valeur absolue des excès. Après avoir étudié l'impact d'incertitude des excès de production et d'inflation, nous poursuivons les caractéristiques de bien-être dans l'équilibre et discutons le design optimale d'autorités pour les types différents d'incertitude. Le troisième chapitre étudie le rôle de l'information publique et privée dans les sociétés hétérogènes. La littérature qui étudie les impacts d'information sur le bien-être social est étendue. Néanmoins, la plupart de cette littérature est basée dans l'idée que l'économie est homogène, en signifiant que tous les agents sont frappés par les mêmes chocs fondamentaux. Dans ce chapitre nous développons une économie de deux régions avec les chocs idiosyncratiques. Pour ce modèle, nous élaborons l'équilibre, l'optimum social et régional et discutons les valeurs sociales, régionales et inter-régionales d'information. Après cela, nous appliquons cette méthodologie à un exemple de concours de beauté. Le dernier chapitre étudie des jeux de communication non-coopératifs étant joués par les autorités politiques dans une économie internationale. Chaque agent politique reçoit des signaux sur les chocs réels qui affectent les économies de pays. Cet agent peut révéler ou pas ces signaux reçus. Le modèle est caractérisé par un argument de concours de beauté dans l'utilité et des effets externes inter-régionales. L'équilibre non-coopératif n'est jamais caractérisé par opacité. La plaine transparence peut être le résultat d'équilibre et dans ce cas-là est Pareto-optimum. D'un point de vue normatif, opacité peut être Pareto-optimale: la valeur sociale d'information publique peut être négative dans les économies ouvertes aussi bien que dans les économies fermées. La révélation partielle est un résultat possible, mais jamais Pareto-optimu / The thesis consists of four chapters, which discuss the different aspects of macroeconomic policy elaboration under uncertainty.The first chapter is devoted to the robust monetary policy in a currency union. A great number of recent researches reveal the importance of country-specific shocks for the optimal policy in a currency union. However, these shocks have been completely overlooked by the literature on optimal policy under model uncertainty. Thus, the main purpose of this chapter is to fill this gap and to show that the asymmetries between regions have to be taken into account when elaborating robust monetary policy. In our research, we use a New-Keynesian model of a two-country currency union which is hit by asymmetric shocks. For this model, we derive the robust monetary policy which works reasonably well even for the worst-case model perturbations. We find the attenuation effect of uncertainty in case of shocks in a region with stronger price stickiness. This means that the central bank reacts to these shocks less aggressively when the extent of model uncertainty is higher. For the shocks in a region with more flexible prices, we find a anti-attenuation affect of model uncertainty.The second chapter discusses the optimal policy design in a game-theoretical framework. More precisely, this chapter explores the role of uncertain government preferences in a linear-quadratic model of fiscal and monetary policy interaction. We show that the effects of preference uncertainty are fastened on multiplicative uncertainty about the policy effectiveness. If the effects of fiscal and monetary policies on the economy are known, preference uncertainty does not alternate the symbiosis result of interaction. In this case, inflation and output are equal to their targets irrespective of the central bank and the government preferences. Multiplicative uncertainty about the fiscal policy effects creates the inflation bias. Multiplicative uncertainty about the monetary policy effects creates either standard inflation bias or negative inflation bias with output higher than the target and inflation lower than the target. In this case, preference uncertainty enlarges the absolute value of the output gap, while the effect on the inflation gap depends on the extent of monetary multiplicative uncertainty. After studying the impact of uncertainty on inflation and output gaps, we proceed with the welfare properties of the equilibrium and discuss the optimal conservativeness of authorities for different types of uncertainty.The third chapter explores the role of public and private information in heterogeneous societies. The literature which studies the impacts of information on social welfare, is extensive. Nevertheless, most of this literature is based on the assumption of homogeneous economy, meaning that all the agents are hit by the same fundamentals shocks. In this chapter we develop a two-region economy with idiosyncratic shocks. For this model, we derive the equilibrium, social and regional optimum and discuss the social, regional and inter-regional values of information. After that, we apply this methodology to a beauty contest example.The last chapter studies non-cooperative communication games being played by policymakers in an international economy. Each policymaker receives signals on the real idiosyncratic shocks which affect the country economies. It has the choice of revealing or not the received signals. The model is characterized by a beauty contest argument in the utility function and cross-border real spillovers. The non-cooperative equilibrium is never characterized by no revelation. A full transparency outcome may be the equilibrium outcome and is then Pareto-optimal. From a normative point of view, no revelation may be Pareto-optimal: the social value of public information may be negative in international economies as well as in closed economies. Partial revelation schemes are possible outcomes but never Pareto-optimal.