The recent manufacturing environment is characterized as having diverse products due to mass customization, short production lead-time, and unstable customer demand. Today, the need for flexibility, quick responsiveness, and robustness to system uncertainties in production scheduling decisions has increased significantly. In traditional job shops, tooling is usually assumed as a fixed resource. However, when tooling resource is shared among different machines, a greater product variety, routing flexibility with a smaller tool inventory can be realized. Such a strategy is usually enabled by an automatic tool changing mechanism and tool delivery system to reduce the time for tooling setup, hence allows parts to be processed in small batches. In this research, a dynamic scheduling problem under flexible tooling resource constraints is studied. An integrated approach is proposed to allow two levels of hierarchical, dynamic decision making for job scheduling and tool flow control in Automated Manufacturing Systems. It decomposes the overall problem into a series of static sub-problems for each scheduling window, handles random disruptions by updating job ready time, completion time, and machine status on a rolling horizon basis, and considers the machine availability explicitly in generating schedules. Two types of manufacturing system models are used in simulation studies to test the effectiveness of the proposed dynamic scheduling approach. First, hypothetical models are generated using some generic shop flow structures (e.g. flexible flow shops, job shops, and single-stage systems) and configurations. They are tested to provide the empirical evidence about how well the proposed approach performs for the general automated manufacturing systems where parts have alternative routings. Second, a model based on a real industrial flexible manufacturing system was used to test the effectiveness of the proposed approach when machine types, part routing, tooling, and other production parameters closely mimic to the real flexible manufacturing operations. The study results show that the proposed scheduling approach significantly outperforms other dispatching heuristics, including Cost Over Time (COVERT), Apparent Tardiness Cost (ATC), and Bottleneck Dynamics (BD), on due-date related performance measures under both types of manufacturing systems models. It is also found that the performance difference between the proposed scheduling approach and other heuristics tend to become more significant when the number of machines is increased. The more operation steps a system has, the better the proposed method performs, relative to the other heuristics. This research also investigates in what conditions (e.g. the number of machines, the number of operation steps, and shop load conditions) the proposed approach works the best, and how the performance of this proposed approach changes when these conditions change. When tooling resource is shared, parts can be routed to machines that do not have all the required tools. This may result in higher routing flexibility. However, research work to date in sharing of tooling resources often places more emphasis on the real-time control and manipulation of tools, and pays less attention to the loading of machines and initial tool allocation at the planning stage. In this research, a machine-loading model with shared tools is proposed to maximize routing flexibility while maintaining minimum resident tools. The performance of the proposed loading heuristic is compared to that of a random loading method using hypothetically generated single stage system models. The study result indicates that better system performances can be obtained by taking into account the resident tooling ratio in assigning part types and allocating tools to machines at the initial planning stage. / Ph. D.

Shorter product life-cycles, unpredictable demand, and customized products have forced manufacturing firms to operate more efficiently and effectively in order to adapt to changing requirements. Traditional manufacturing systems, such as job shops and flow lines, cannot handle such environments. Cellular manufacturing, which incorporates the flexibility of job shops and the high production rate of flow lines, has been seen as a promising alternative for such cases. Although cellular manufacturing provides great benefits, the design of cellular manufacturing systems is complex for real-life problems. Existing design methods employ simplifying assumptions which often deteriorate the validity of the models used for obtaining solutions. Two simplifying assumptions used in existing design methods are as follows. First, product mix and demand do not change over the planning horizon. Second, each operation can be performed by only one machine type, i.e., routing flexibility of parts is not considered. This research aimed to develop a model and a solution approach for designing cellular manufacturing systems that addresses these shortcomings by assuming dynamic and stochastic production requirements and employing routing flexibility. A mathematical model and an optimal solution procedure were developed for the design of cellular manufacturing under dynamic and stochastic production environment employing routing flexibility. Optimization techniques for solving such problems usually require a substantial amount of time and memory space, therefore, a simulated annealing based heuristic was developed to obtain good solutions within reasonable amounts of time. The heuristic was evaluated in two ways. First, different cellular manufacturing design problems were generated and solved using the heuristic. Then, solutions obtained from the heuristic were compared with lower bounds of solutions obtained from the optimal solution procedure. The lower bounds were used instead of optimal solutions because of the computational time required to obtain optimal solutions. The results show that the heuristic performs well under various circumstances, but routing flexibility has a major impact on the performance of the heuristic. The heuristic appears to perform well regardless of problem size. Second, known solutions of two CM design problems from literature were used to compare with those from the heuristic. The heuristic slightly outperforms one design approach, but substantially outperforms the other design approach. / Ph. D.

With the integration of renewable and distributed energy resources (DER) and advances in metering infrastructure, power systems are undergoing rapid modernization that brings forward new challenges and possibilities, which call for more advanced learning, analysis, and planning tools. While there are numerous problems present in the modern power grid, in this work, this work has addressed four of the most prominent challenges and has shown that how the new advances in generation and metering can be leveraged to address the challenges that arose by them. With regards to learning in power systems, we first have tackled power distribution system topology identification, since knowing the topology of the power grid is a crucial piece in any meaningful optimization and control task. The topology identification presented in this work is based on the idea of emph{prob-to-learn}, which is perturbing the power grid with small power injections and using the metered response to learn the topology. By using maximum-likelihood estimation, we were able to formulate the topology identification problem as a mixed-integer linear program. We next have tackled the prominent challenge of finding optimal flexibility of aggregators in distribution systems, which is a crucial step in utilizing the capacity of distributed energy resources as well as flexible loads of the distribution systems and to aid transmission systems to be more efficient and reliable. We have shown that the aggregate flexibility of a group of devices with uncertainties and non-convex models can be captured with a quadratic classifier and using that classifier we can design a virtual battery model that best describes the aggregate flexibility. For power system analysis and planning, we have addressed fast probabilistic hosting capacity analysis (PHCA), which is studying how DERs and the intermittency that they bring to the power system can impact the power grid operation in the long term. We have shown that interconnection studies can be sped up by a factor of 20 without losing any accuracy. By formulating a penalized optimal power flow (OPF), we were able to pose PHCA as an instance of multiparametric programming (MPP), and then leveraged the nice properties of MPP to efficiently solve a large number of OPFs. Regarding planning in power systems, we have tackled the problem of strategic investment in energy markets, in which we have utilized the powerful toolbox of multiparametric programming to develop two algorithms for strategic investment. Our MPP-aided grid search algorithm is useful when the investor is only considering a few locations and our MPP-aided gradient descent algorithm is useful for investing in a large number of locations. We next have presented a data-driven approach in finding the flexibility of aggregators in power systems. Finding aggregate flexibility is an important step in utilizing the full potential of smart and controllable loads in the power grid and it's challenging since an aggregator controls a large group of time-coupled devices that operate with non-convex models and are subject to random externalities. We have shown that the aggregate flexibility can be accurately captured with an ellipsoid and then used Farkas' lemma to fit a maximal volume polytope inside the aforementioned ellipsoid. The numerical test showcases that we can capture 10 times the volume that conventional virtual generator models can capture. / Doctor of Philosophy / With the integration of renewable and distributed energy resources (DER) and advances in metering infrastructure, power systems are undergoing rapid modernization that brings forward new challenges and possibilities, which call for more advanced learning, analysis, and planning tools. While there are numerous problems present in the modern power grid, in this work, this work has addressed four of the most prominent challenges and has shown that how the new advances in generation and metering can be leveraged to address the challenges that arose by them. With regards to learning in power systems, we first have tackled power distribution system topology identification, since knowing the topology of the power grid is a crucial piece in any meaningful optimization and control task. We next have tackled the prominent challenge of finding optimal flexibility of aggregators in distribution systems, which is a crucial step in utilizing the capacity of distributed energy resources as well as flexible loads of the distribution systems and to aid transmission systems to be more efficient and reliable. For power system analysis and planning, we have addressed fast probabilistic hosting capacity analysis (PHCA), which is studying how DERs and the intermittency that they bring to the power system can impact the power grid operation in the long term. We have shown that interconnection studies can be sped up by a factor of 20 without losing any accuracy. Regarding planning in power systems, we have tackled the problem of strategic investment in energy markets, in which we have utilized the powerful toolbox of multiparametric programming to develop two algorithms for strategic investment. We next have presented a data-driven approach in finding the flexibility of aggregators in power systems. Finding aggregate flexibility is an important step in utilizing the full potential of smart and controllable loads in the power grid and it's challenging since an aggregator controls a large group of time-coupled devices that operate with non-convex models and are subject to random externalities.

The flexibility of welded joints is an important issue in design of car bodies. Two generic, 3-D, design-oriented models (simple and complex) are developed to represent the compliant behavior of multibranch flexible joints. The simple model consists of torsional springs restraining the relative rotation of the joint branches in the three planes, while all branches are assumed to be rigidly connected in translation. Coupling between motions in different planes is neglected. The complex model accounts for such coupling. A statistical system identification method is proposed for inferring the model parameters from the static response of the structure. The method is demonstrated by applying it to a simple cube frame structure and a car body. Finally, the two models are compared in terms of their ability to predict static response. / Ph. D.

We study the resource investment decision faced by a firm that offers two demand-classes (i.e., products, services), while incorporating the firm's pricing decision into the investment decision. For this purpose, we consider a monopolistic situation and model the demand curve of each demand-class as a downward sloping linear function of its own price. The firm can invest in dedicated resources, which can only satisfy a specific demand-class, and/or in a more expensive, flexible resource, which can satisfy both demand-classes. We consider a two-stage stochastic decision model: In the first stage, the firm determines the dedicated and flexible resource capacities to invest in under demand uncertainty. In the second stage, demand curves are realized and the firm optimizes its revenue through pricing and resource allocation decisions, constrained by its capacity investment decision in the first stage. Our analysis provides the structure of the firm's optimal resource investment strategy as a function of price elasticities and investment costs, and shows how the value of resource flexibility depends on these parameters and demand correlations. Based on our analysis, we provide principles on the firm's optimal resource investment strategy under uncertainty. We show that it can be optimal for the firm to invest in the flexible resource when demand patterns are perfectly positively correlated, while it is not always optimal to invest in the flexible resource when demand patterns are perfectly negatively correlated. / Master of Science

The stadium, in its purest form, is a structure that holds tiered seating arrangements built for mass viewing of sports, competitions, and public events. However, over the years, it has become much more than that. The stadium provides the spiritual need of community, allowing individuals to connect to others by sharing common beliefs and goals. This allows the stadium to become a source of civic pride to the people it serves. This combination of purpose and pride makes the stadium one of the most important archetypes ever created. It is the physical representation of human connectivity, a city's symbolic soul; the modern day cathedral. A symbiotic relationship is formed between the stadium and the public. In the modern era, viewing live sports has become big business. Taking advantage of the situation, team owners have designed stadiums to capitalize financially as much as possible. These newly designed stadiums, along with the rise of the automobile, have been moved from downtown to the suburbs, providing owners more space for seats, larger parking lots, and ultimately more revenue. These larger, disconnected stadiums have led to waning attendance, heavy pollution, and an overall lack of use. The once spiritual experience of the arena has now been watered down as the stadium has become a detractor of public good. Sports leagues now run as unopposed monopolies, with each major league having approximately 30 teams. With supply low and demand high, private entities essentially blackmail the public into building and funding stadiums to attract highly coveted sports teams. Desperately desiring to call a team their own, the public agrees to the deal. The end result is that the public funds a major project that provides no socioeconomic benefit to anyone other than the teams owner. The once symbiotic relationship between the stadium and the city has become perverted. Although public subsidies are now frowned upon due to the growing awareness of the damage they cause cities, the major sports leagues will always have a significant hold over the distribution of teams and demand will always remain high. Therefore, if the public continues to foot the bill, it is up to the architect to find a balance between both public and private benefits through design. We must create a stadium that functions as a revenue generating event venue, as well as a public serving entity that enriches the community around it and repair the once great harmony between the public and their stadium. My Thesis will look at designing a public soccer stadium in downtown Washington D.C. This is Public Gains: A Stadium for the People. / Master of Architecture

Insulin resistance (IR), T2DM, and obesity together form a cluster of interrelated metabolic challenges that may be linked by metabolic inflexibility. Metabolic inflexibility is characterized by the resistance to switching substrate oxidation preference based on substrate availability and can be measured in either fasted or insulin-stimulated conditions. As the largest site for glucose disposal and a primary tissue influencing regulation of blood glucose concentrations, skeletal muscle likely plays a central role in regulating substrate oxidation preference based on substrate availability. Skeletal muscle lipotoxicity caused by an impaired regulation of fat uptake and oxidation is postulated to disrupt insulin signaling and lead to skeletal muscle IR. High dietary saturated fat intake results in reduced basal fat oxidation and a resistance to switching to carbohydrate oxidation during insulin-stimulated conditions in susceptible individuals. This metabolic inflexibility may lead to an accumulation of intramyocellular species that impair insulin signaling. Endurance exercise training improves the capacity for fat oxidation in metabolically inflexible individuals. However, relatively little is known about how endurance exercise training influences substrate oxidation preference when paired with a high fat diet (HFD). Therefore, the purpose of this study was to determine the effects of a HFD on substrate metabolism in skeletal muscle of sedentary and endurance trained (ET) males. Healthy, sedentary (n=17) and ET (n=7) males first consumed a 10-day moderate carbohydrate diet (55% carbohydrate, 30% total fat, <10% saturated fat) isocaloric to their individual energy requirements and then underwent a 4- hour high fat challenge testing session. During the session, they consumed a high fat meal (820 kcals; 25% carbohydrate, 63% total fat [26% saturated fat]), and skeletal muscle biopsies were taken in the fasted and 4-hour postprandial conditions. Participants then consumed a 5-day HFD (30% carbohydrate, 55% total fat, 25% saturated fat) and repeated the high fat challenge testing session. Substrate oxidation measures were performed on the collected skeletal muscle tissue, and the meal effect, defined as the percent change from the fasting to 4- hour postprandial condition, for each measure was calculated. There was a HFD by physical activity group interaction on meal effect for metabolic flexibility (P<0.05) and a HFD effect on meal effect for glucose oxidation (P<0.05). Meal effects for metabolic flexibility and glucose oxidation were maintained in the ET (20 ± 4% to 41 ± 21% and 128 ± 92% and 41 ± 15%, respectively; both P>0.05) but decreased in the sedentary (34 ± 7% to 4 ± 5% and 78 ± 26% to -21 ± 6%, respectively; both P<0.01) group. There were trends toward HFD effects on reductions in meal effects for total (P=0.062) and incomplete (P=0.075) fat oxidation, which were driven primarily by an increase in fasting total (12.1 ± 2.6 nmol/mg protein/h to 18.5 ± 2.3 nmol/mg protein/h; P<0.01) and incomplete (11.5 ± 2.5 nmol/mg protein/h to 17.6 ± 2.3 nmol/mg protein/h; P<0.01) fat oxidation in the ET group as a result of the HFD. Fasting total and incomplete fat oxidation did not change in the sedentary group (7.3 ± 0.8 nmol/mg protein/h to 7.8 ± 0.8 nmol/mg protein/h and 6.8 ± 0.7 nmol/mg protein/h to 7.2 ± 0.8 nmol/mg protein/h, respectively; both P>0.05). Overall, these findings suggest the ET state attenuates deleterious effects of a short-term HFD on reduced metabolic flexibility and insulin-stimulated glucose oxidation. In addition, a HFD-induced reduction in fat oxidation during the fasted-to-fed transition may be caused by differing mechanisms in sedentary and ET individuals. These findings provide a basis for future work targeting the elucidation of potential mechanistic differences in substrate oxidation preference between sedentary and ET individuals. / Ph. D. / Type 2 diabetes (T2DM) is a commonly occurring disease worldwide, and treatment of the disease is considerably burdensome for individuals and societies. T2DM is closely related to insulin resistance (IR) and obesity, and in each of these conditions, the characteristic of metabolic inflexibility has been observed. Metabolic inflexibility is a reduced ability to adjust fat or carbohydrate utilization for energy based on the availability of each of these macronutrients. Skeletal muscle may be an important tissue in the regulation of macronutrient utilization since it plays a key role in blood glucose regulation. High dietary saturated fat intake may lead to metabolic inflexibility in skeletal muscle in susceptible individuals. This metabolic inflexibility may result in increased storage of fat within skeletal muscle, which is hypothesized to disrupt insulin signaling. This disruption can lead to IR. Endurance exercise training improves metabolic flexibility. However, little is known about how endurance exercise training influences macronutrient utilization when paired with a high fat diet (HFD). Therefore, the purpose of this study was to determine the effects of a HFD on macronutrient utilization in skeletal muscle of sedentary and endurance trained (ET) males. Seventeen healthy, sedentary males and seven ET males first consumed a 10-day moderate-carbohydrate diet that was provided by the study investigators and designed to keep each participant weight stable. Participants then underwent a high fat challenge testing session in which they consumed a high fat meal and had skeletal muscle biopsies taken both before and after the meal. Participants then consumed a 5-day HFD, also designed to keep them weight stable, and repeated the high fat challenge testing session. Macronutrient utilization measures were performed on the collected skeletal muscle samples. Overall, metabolic flexibility was reduced in the sedentary group but was maintained in the ET group, which suggests that ET individuals may be protected against developing a HFD-induced metabolic inflexibility in skeletal muscle and its associated downstream negative effects on insulin signaling. In addition, fat utilization during the high fat challenge meal decreased in both sedentary and ET individuals as a result of the HFD. However, fat utilization in the fasted state was higher in ET individuals after the HFD compared with baseline, but fat utilization was the same in sedentary individuals before and after the HFD. This suggests there may be differences between sedentary and ET individuals in the mechanisms involved in the adjustment of fat utilization to dietary fat intake. Further research is needed to understand these differences, as they may play important roles in understanding how IR and T2DM develop.

Yes / This article explores the implications of `networked¿ and `flexible¿ organisations for the work and skills of professionals. Drawing on material from four different case studies it reviews work that is out-sourced (IT professionals and housing benefit caseworkers), work done by teachers contracted to a temporary employment agency and work done through an inter-firm network (chemical production workers). In each of these cases work that was out-sourced was managed very differently to that which was undertaken in-house, with managerial monitoring replacing and reducing employees¿ discretion. New staff in these networks had fewer skills when hired and were given access to a narrower range of skills than their predecessors. By contrast, the production staff employed on permanent contracts in the inter-firm network were given (and took) significant amounts of responsibility, with positive results for both their skills and the work processes. Despite these results, out-sourcing and sub-contracting are a far more common means of securing flexibility than organisational collaboration and the implications of this for skills is considered.

No / This paper examines previous approaches to the identification and measurement of strategic flexibility and concludes that the use of quantitative methods alone cannot capture the essence of such a complex and intangible subject. It is reasoned that a holistic approach to research design should be adopted when carrying out particular categories of production management research. A research design used to investigate the concept of strategic flexibility in manufacturing industry is briefly outlined as an illustration. The role of the case study within this and the contribution it was able to make to the investigation is described.

No / This paper investigates the equilibrium relationship between taxation, portfolio choice (risk-taking) and capital accumulation. Specifically, it examines how taxes affect risk-taking and capital accumulation. We extend the existing literature by relaxing two crucial assumptions in modelling risk-taking behavior: (i) that the investment opportunity set is fixed and (ii) that there is no distinction between attitudes towards risk and behavior towards intertemporal substitution. We extend the investment opportunity set of individuals through optimally determined human capital; and distinguish intertemporal substitution from attitudes towards risk via a recursive utility function. In the presence of these extensions, the paper successfully derives a closed-form solution to the stochastic growth model with stochastic wage income.