Current organizational design changes such as restructuring, production advancements, and information technology improvements have caused many organizations to move to flatter management structures. Changes in the organizational structure along with the demand for improved performance have broadened the scope of responsibilities for first-level managers in manufacturing organizations. First-level managers are required to balance their time to meet greater demands. The sociotechnical systems principle of joint optimization states that organizations function optimally when design changes are made to meet the needs of both the social and technical subsystems in the context of the organization's environment. This study uses time allotment at the supervisory level to operationalize the sociotechnical systems principle of joint optimization. Ninety-one first-level managers from both the production and distribution areas of thirteen North American facilities participated in this study. Four survey instruments were used to measure the following dimensions: joint optimization, department performance, time allotment to the social and technical subsystems, and organizational values of appropriate time use. Five time allotment constructs emerged from the data collected on time use in the social and technical subsystems. These were time spent on Participation and Information Sharing, Customer Needs and Strategic Planning, Skill Development and Compensation, Quality, and Department Operational Needs. The results indicated time allotment constructs along with the organization's values on appropriate time use can be used to predict both joint optimization and performance at the department level. The results also indicated a strong relationship (r = .607, p < .05) between level of joint optimization and department performance. / Master of Science

Master of Science

Product line planning aims at optimal planning of product variety. In addition, the traditional product line planning problem develops new product lines based on product attributes without considering existing product lines. However, in reality, almost all new product lines evolve from existing product lines, which leads to the product line evolution problem. Product line evolution involves trade-offs between the marketing perspective and engineering perspective. The marketing concern focuses on maximizing utility for customers; the engineering concern focuses on minimizing engineering cost. Utility represents satisfaction experienced by the customers of a product. Engineering cost is the total cost involved in the process of the development of a product line. These two goals are in conflict since the high utility requires high-end product attributes which could increase the engineering cost and vice versa. Rather than aggregating both problems as one single level optimization problem, the marketing and engineering concerns entail a non-collaborative game per se. This research investigates a game-theoretic approach to the product line evolution problem. A leader-follower joint optimization model is developed to leverage conflicting goals of marketing and engineering concerns within a coherent framework of game theoretic optimization. To solve the joint optimization model efficiently, a bi-level nested genetic algorithm is developed. A case study of smart watch product line evolution is reported to illustrate the feasibility and potential of the proposed approach.

The traditional approach to imaging system design places the sole burden of image formation on optical components. In contrast, a computational imaging system relies on a combination of optics and post-processing to produce the final image and/or output measurement. Therefore, the joint-optimization (JO) of the optical and the post-processing degrees of freedom plays a critical role in the design of computational imaging systems. The JO framework also allows us to incorporate task-specific performance measures to optimize an imaging system for a specific task. In this dissertation, we consider the design of computational imaging systems within a JO framework for two separate tasks: object reconstruction and iris-recognition. The goal of these design studies is to optimize the imaging system to overcome the performance degradations introduced by under-sampled image measurements. Within the JO framework, we engineer the optical point spread function (PSF) of the imager, representing the optical degrees of freedom, in conjunction with the post-processing algorithm parameters to maximize the task performance. For the object reconstruction task, the optimized imaging system achieves a 50% improvement in resolution and nearly 20% lower reconstruction root-mean-square-error (RMSE ) as compared to the un-optimized imaging system. For the iris-recognition task, the optimized imaging system achieves a 33% improvement in false rejection ratio (FRR) for a fixed alarm ratio (FAR) relative to the conventional imaging system. The effect of the performance measures like resolution, RMSE, FRR, and FAR on the optimal design highlights the crucial role of task-specific design metrics in the JO framework. We introduce a fundamental measure of task-specific performance known as task-specific information (TSI), an information-theoretic measure that quantifies the information content of an image measurement relevant to a specific task. A variety of source-models are derived to illustrate the application of a TSI-based analysis to conventional and compressive imaging (CI) systems for various tasks such as target detection and classification. A TSI-based design and optimization framework is also developed and applied to the design of CI systems for the task of target detection, it yields a six-fold performance improvement over the conventional imaging system at low signal-to-noise ratios.

Volvo Construction Equipment (VCE) has invested in an advanced lasermachine that can cut sheet metal parts with angled edges. As a result, thedevice provides expanded possibilities in the design and production of sheetmetal products.The material cost component is significant in the production of sheet metalproducts. This cost can be reduced by reducing the plate's thickness andchanging its dimensions.This study examines the effects of a thinner plate thickness combined withchanged height and width dimensions and a more robust weld joint inmanufacturing a so-called A stay, a part of the articulated hauler from VCE.The study was conducted with the Design for Six Sigma (DFSS) process,product research, development, and R&amp;D methodology, which falls under theoverall scientific, technical research methodology "Systems Engineering."The study's conclusion shows that material saving with a thinner sheet is at theexpense of reduced quality and product cycle life. In addition,recommendations for in-depth analyses have also been proposed in the study'sdiscussion section.

Aujourd'hui, les systèmes d'imagerie sont des instruments complexes qui font interagir optique, détecteur et traitement numérique. Afin de dépasser les performances d'imagerie conventionnelles, il devient nécessaire de tenir compte de cette interaction dès la phase de conception et d'optimiser simultanément les paramètres optiques et numériques. L'objectif de ma thèse est de développer des méthodes d'optimisation conjointe pour obtenir de nouveaux systèmes à performances d'imagerie augmentées et de complexité réduite. J'ai tout d'abord étudié le cas de l'augmentation de la profondeur de champ d'une combinaison optique existante. Un masque de phase binaire a été inséré au voisinage du diaphragme d'ouverture d'un objectif ouvert à f/1.2 et a été optimisé de façon conjointe avec un traitement de déconvolution en utilisant le critère basé sur la qualité de l'image restaurée. L'augmentation de profondeur de champ a été quantifiée et des mesures précises de la fonction de transfert de modulation ont permis de valider expérimentalement l'efficacité de ce type d'imageur non-conventionnel. Dans ces premiers travaux, seul le masque de phase a été modifié lors de l'optimisation. Pour accroître encore l'efficacité du système d'imagerie, il est nécessaire d'optimiser l'ensemble de tous les paramètres optiques. Or l'optimisation d'une combinaison optique est un problème complexe qui doit tenir compte de contraintes spécifiques et nécessite l'utilisation d'un logiciel de calcul optique dédié, comme le logiciel Code V qui a été utilisé dans cette thèse. Comme le critère d'optimisation conjointe basé sur la qualité image n'est plus adapté à ce type d'optimisation, j'ai proposé un nouveau critère. Il se base sur les critères d'optimisation classiques de Code V, qui ont été modifiés de façon à prendre en compte de manière implicite le traitement de déconvolution. Cette méthode de conception a tout d'abord été validée dans le cas de l'optimisation d'un masque de phase pour l'extension de profondeur de champ d'une combinaison optique existante. Les résultats obtenus sont équivalents à ceux donnés par l'optimisation suivant le critère de qualité d'image. La technique a ensuite été utilisée pour améliorer une combinaison conventionnelle existante à très forte ouverture (f/0.75) : en modifiant ses paramètres optiques, la combinaison a été allégée et la qualité d'image a été homogénéisée sur l'ensemble du champ. Enfin, j'ai appliqué cette méthode de conception conjointe pour résoudre le problème important de la sensibilité thermique d'un système infrarouge dans la bande 8-12 µm. Cette méthode a permis de concevoir, à partir de zéro, plusieurs types de combinaisons optiques à courte et longue focale, rendues insensibles à la température. Elles présentent un schéma optique plus simple que les solutions athermalisées de façon classique, tout en ayant des performances d'imagerie similaires voire supérieures. / Imaging systems are now complex instruments where lens, sensor and digital processing interact strongly together. In order to obtain better imaging performance than conventional imaging, it has become necessary to take into account this interaction in the design stage and therefore to optimize jointly optical and digital parameters. The objective of my thesis is to develop joint optical-digital optimization methods in order to obtain imaging systems with higher performance and lower complexity. I first considered extending the depth of field of an already existing lens. A binary phase mask has been inserted in the vicinity of the aperture stop of a f/1.2 lens, and it has been optimized jointly with a deconvolution filter using the restored image quality criterion. The increase in depth of field has been quantified, and modulation transfer function measurements have proved experimentally the efficiency of this unconventional imaging system. During this first study only the phase mask was optimized. To further increase the imaging system efficiency, all the optical parameters need to be optimized. However, optical design is a complex problem in which specific constraints have to be taken into account and for which one needs to use a dedicated software. In this thesis I used the Code V optical design software. Since the image quality-based optimization cannot be easily implemented in this type of software, I proposed a new criterion. It is based on classical optical optimization criteria used in Code V that have been modified in order to take into account deconvolution in a implicit manner. This design method has been first validated on the optimization of a phase mask for depth of field extension of an already existing lens. Results were similar to those given by the image quality-based optimization. Then this method has been used to enhance a very fast f/0.75 lens: by modifying its optical parameters, the lens has been simplified, and the image quality has been homogenized over the field. Eventually I applied this joint design method to solve the important problem of thermal sensitivity of an 8-12 µm infrared system. By using this method I designed from scratch several types of short and long focal length athermalized lenses. The obtained lenses are simpler than conventionally athermalized ones while having similar or even higher imaging performance.

Bundle adjustment is the process of simultaneously optimizing camera poses and 3D structure given image point tracks. In structure-from-motion, it is typically used as the final refinement step due to the nonlinearity of the problem, meaning that it requires sufficiently good initialization. Contrary to this belief, recent literature showed that useful solutions can be obtained even from arbitrary initialization for fixed-rank matrix factorization problems, including bundle adjustment with affine cameras. This property of wide convergence basin of high quality optima is desirable for any nonlinear optimization algorithm since obtaining good initial values can often be non-trivial. The aim of this thesis is to find the key factor behind the success of these recent matrix factorization algorithms and explore the potential applicability of the findings to bundle adjustment, which is closely related to matrix factorization. The thesis begins by unifying a handful of matrix factorization algorithms and comparing similarities and differences between them. The theoretical analysis shows that the set of successful algorithms actually stems from the same root of the optimization method called variable projection (VarPro). The investigation then extends to address why VarPro outperforms the joint optimization technique, which is widely used in computer vision. This algorithmic comparison of these methods yields a larger unification, leading to a conclusion that VarPro benefits from an unequal trust region assumption between two matrix factors. The thesis then explores ways to incorporate VarPro to bundle adjustment problems using projective and perspective cameras. Unfortunately, the added nonlinearity causes a substantial decrease in the convergence basin of VarPro, and therefore a bootstrapping strategy is proposed to bypass this issue. Experimental results show that it is possible to yield feasible metric reconstructions and pose estimations from arbitrary initialization given relatively clean point tracks, taking one step towards initialization-free structure-from-motion.

Neue Organisationsformen, wie evolutionäre Organisationen, bilden in vielen Kooperationsszenarien sozio-technische Konstrukte mit modernen CSCW Anwendungen aus. Daher erfordern Veränderungen dieser sozialen Systeme eine kontinuierliche Anpassung der technischen Tools an die neuen sozialen Konfigurationen. Diese Dissertation ist als Design Science Research (DSR) Projekt konzipiert und addressiert die folgende Forschungsfrage (RQ): “Wie können soziotechnische, evolutionäre Organisationen die Herausforderungen der joint optimization und des organizational choice während ihrer autopoietischen Veränderungsprozesse addressieren?” Die Fallstudie Viva con Agua de St. Pauli e.V. wurde mittels qualitativer und ethnographischer Methoden im Rahmen der entsprechenden DSR Zyklen untersucht. Das Forschungsprojekt fokussiert die Entwicklung von Artefakten indem sowohl eine technische, als auch eine soziale Perspektive eingenommen wird. Aus der technische Perspektive wird die RQ durch eine Microservice-Plattform adressiert. Die Architektur dient der Verteilung von Verantwortlichkeit für die Software in einem heterogenen Netzwerk von Entwickler:innen. Dabei müssen diverse neue Herausforderungen beachtet werden, wie etwa die Verteilung des User Interface. Durch die Betrachtung der RQ aus der sozialen Perspektive wird der USMU Workshop entwickelt. Dieses Artefakt dient der Verbindung der Charakteristika evolutionärer Organisationen mit agiler Software Entwicklung und mit Methoden des partizipativen Designs. Die Studien zeigen, dass beide Artefakte die RQ adressieren. Zudem konnte ich für beide Artefakte wertvolle Verbesserungsmöglichkeiten aufzeigen. Somit motivieren die Ergebnisse den nächsten Schritt des Projekts und die vorliegende Thesis wird Bestandteil des zyklischen Ablaufs eines DSR Projekts. / The emergence of new types of organizational structures, such as evolutionary-teal organizations, almost always leads to the development of socio-technical constructs when it comes to working in collaboration with modern CSCW applications. A consequence of this is that the social system’s autopoietic change processes create challenges that compel one to adjust the implementation of the technical tool to the social system’s new configuration. This thesis is structured according to the design science research (DSR) approach and focuses on the research question (RQ): “How can socio-technical evolutionary-teal organizations address the challenges of joint optimization and organizational choice during their autopoietic processes?” For this purpose, the case study Viva con Agua de St. Pauli e.V. is investigated using a qualitative ethnographical approach during the DSR cycles. Addressing the RQ, two artifacts are designed from a technical as well as a social perspective. While the technical perspective primarily investigates the adjustments of technology, the social perspective focuses on the management of change in socio-technical evolutionary-teal organizations. I propose a microservice platform as an artifact that addresses the RQ from a technical perspective. The microservice architecture aims at spreading the responsibility for the software through a heterogeneous ecosystem of developers. The newly designed USMU workshop is addressing the RQ from the social perspective. It strives to intertwine the characteristics of evolutionary-teal organizations with agile software development and participatory design methods. In my studies, I examine the fact that both artifacts can be used to address the RQ. Additionally, I was able to identify valuable improvements for both of my artifacts. Hence, the project follows the lifecycle of a DSR project by reasoning through the results presented here for its next iteration.

Ces dernières années, un nouveau type de système de production nommé système de production géographiquement dispersé (GDPS) est prôné par de nombreuses entreprises manufacturières internationales. Par cette vision « dispersée », il présente un certain nombre d'avantages tels que l'économie des coûts du produit livré (puisque proche des clients), l'amélioration de la qualité des services (délais de livraison courts, services après-vente de haute qualité) favorisant la pérennité et la compétitivité des entreprises dans un contexte de compétition mondiale. Cependant l’exploitation multi-sites d’un GPDS est confronté à de nombreux défis concernant les normes, les réglementations, la maîtrise des flux de production, et en particulier la planification et l'optimisation de la maintenance en raison de la dispersion géographique des sites de production. Sur ce dernier point et plus globalement la définition d’une stratégie de maintenance adaptée au GDPS, peu d'études ont été menées compte tenu de la jeunesse du sujet et de la complexité des GDPSs (ex. multi-sites, multi-composants). Cette thèse se positionne donc sur ce sujet émergeant avec comme objectif de développer une stratégie de maintenance de regroupement dynamique pour un GDPS en tenant compte de dépendances à la fois aux niveaux composants et sites de production (dépendances économique et géographique) et des impacts des contextes dynamiques (à savoir, taux de détérioration variable des composants, modification des itinéraires de maintenance, possibilités de maintenance, etc.) auxquels il est soumis. Dans cette stratégie, les itinéraires de maintenance et l'ordonnancement sont considérés conjointement dans un modèle global. Le modèle vise à trouver un plan optimal de maintenance et de routage des ressources de maintenance. A cette fin, une structure de coûts et un modèle de dépendance qui prend en compte conjointement la dépendance économique et géographique sont formulés. Ils servent de base à l'élaboration du modèle global de planification et d'ordonnancement de la maintenance et du routage. De plus, pour la recherche de la solution optimale, des algorithmes d’optimisation basés sur l'algorithme génétique et l'algorithme Branch and Bound sont proposés. Enfin, une étude numérique est investiguée pour évaluer la performance, les avantages et aussi les limites de la stratégie proposée. / In the recent years, the Geographically Dispersed Production System (GDPS) with a number of advantages such as saving the product delivered costs (closed to the clients), improving quality of services (short delivery time, high quality after-sales services) has been extensively developed by many manufacturing companies to ensure their competitiveness. In operation, the GPDS faces many challenges concerning standards, regulation, production management, and especially maintenance planning and optimization due to the geographical dispersion of production sites. However, few studies have been developed for maintenance strategies of GDPSs. To face this challenge, the main objective of this thesis is to develop a dynamic grouping maintenance strategy for a GDPS with consideration of dependencies between at both component and site level (economic, geographical dependencies) and impacts of dynamic contexts (i.e. varying deterioration rate of components, change of maintenance routes, maintenance opportunities, etc.). In this strategy, maintenance routing and scheduling are jointly considered in a global model. The model aims at finding an optimal maintenance and routing plan. For this purpose, a cost structure and a dependence model jointly considering economic and geographical dependence are formulated. They are used as a basis for the development of the global model of maintenance routing and scheduling. In addition, to find a joint optimal maintenance and routing plan, advanced algorithms using jointly Genetic Algorithm and Branch and Bound are proposed. Finally, a numerical study is investigated to evaluate the performance and the advantage as well as limits of the proposed maintenance strategy.

<div>Smart warehouses have become more popular in these days, with Automated Guided Vehicles (AGVs) being used for order pickups. They also allow efficient cost management with optimized storage and retrieval. Moreover, optimization of resources in these warehouses is essential to ensure maximum efficiency. In this thesis, we consider a three dimensional smart warehouse system equipped with heterogeneous AGVs (i.e., having different speeds). We propose scheduling and placement policies that jointly consider all the different design parameters including the scheduling decision probabilities and storage assignment locations. In order to provide differentiated service levels, we propose a prioritized probabilistic scheduling and placement policy to minimize a weighted sum of mean latency and latency tail probability (LTP). Towards this goal, we first derive closed-form expressions for the mean latency and LTP. Then, we formulate an optimization problem to jointly optimize a weighted sum of both the mean latency and LTP. The optimization problem is solved efficiently over the scheduling and decision variables. For a given placement of the products, scheduling decisions of customers’ orders are solved optimally and derived in closed forms. Evaluation results demonstrate a significant improvement of our policy (up to 32%) as compared to the state of other algorithms, such as the Least Work Left policy and Join the Shortest Queue policy, and other competitive baselines.</div>