Matching Items (261)
Description
The Metal Semiconductor Field Effect Transistor (MESFET) has high potential to enter analog and RF applications due to their high breakdown voltage and switching frequency characteristics. These MESFET devices could allow for high voltage analog circuits to be integrated with low voltage digital circuits on a single chip in an extremely cost effective way. Higher integration leads to electronics with increased functionality and a smaller finished product. The MESFETs are designed in-house by the research group led by Dr. Trevor Thornton. The layouts are then sent to multi-project wafer (MPW) integrated circuit foundry companies, such as the Metal Oxide Semiconductor Implementation Service (MOSIS) to be fabricated. Once returned, the electrical characteristics of the devices are measured. The MESFET has been implemented in various applications by the research group, including the low dropout linear regulator (LDO) and RF power amplifier. An advantage of the MESFET is that it can function in extreme environments such as space, allowing for complex electrical systems to continue functioning properly where traditional transistors would fail.
ContributorsKam, Jason (Author) / Thornton, Trevor (Thesis director) / Goryll, Michael (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2015-05
Description
Our thesis is a cross collaboration between international relations and industrial engineering. We used a combination of database logic, programming, and Microsoft Visual Studio to organize and analyze Middle Eastern politics. Not only does the final product show raw data entry, but it also can answer complex questions about Middle Eastern relations- queries so complex that Google can’t answer them. We organized and analyzed geopolitical data to make it more accessible and easy, hopefully you enjoy!
ContributorsGranillo-Walker, Erin (Co-author) / Gomez, Livingstone (Co-author) / Wu, Teresa (Thesis director) / Thomson, Henry (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / School of Social Transformation (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Public Affairs (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Our thesis is a cross collaboration between international relations and industrial engineering. We used a combination of database logic, programming, and Microsoft Visual Studio to organize and analyze Middle Eastern politics. Not only does the final product show raw data entry, but it also can answer complex questions about Middle Eastern relations- queries so complex that Google can’t answer them. We organized and analyzed geopolitical data to make it more accessible and easy, hopefully you enjoy!
ContributorsGomez, Livingstone Labaco (Co-author) / Granillo-Walker, Erin (Co-author) / Wu, Teresa (Thesis director) / Thomson, Henry (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
In today's global market, companies are facing unprecedented levels of uncertainties in supply, demand and in the economic environment. A critical issue for companies to survive increasing competition is to monitor the changing business environment and manage disturbances and changes in real time. In this dissertation, an integrated framework is proposed using simulation and online calibration methods to enable the adaptive management of large-scale complex supply chain systems. The design, implementation and verification of the integrated approach are studied in this dissertation. The research contributions are two-fold. First, this work enriches symbiotic simulation methodology by proposing a framework of simulation and advanced data fusion methods to improve simulation accuracy. Data fusion techniques optimally calibrate the simulation state/parameters by considering errors in both the simulation models and in measurements of the real-world system. Data fusion methods - Kalman Filtering, Extended Kalman Filtering, and Ensemble Kalman Filtering - are examined and discussed under varied conditions of system chaotic levels, data quality and data availability. Second, the proposed framework is developed, validated and demonstrated in `proof-of-concept' case studies on representative supply chain problems. In the case study of a simplified supply chain system, Kalman Filtering is applied to fuse simulation data and emulation data to effectively improve the accuracy of the detection of abnormalities. In the case study of the `beer game' supply chain model, the system's chaotic level is identified as a key factor to influence simulation performance and the choice of data fusion method. Ensemble Kalman Filtering is found more robust than Extended Kalman Filtering in a highly chaotic system. With appropriate tuning, the improvement of simulation accuracy is up to 80% in a chaotic system, and 60% in a stable system. In the last study, the integrated framework is applied to adaptive inventory control of a multi-echelon supply chain with non-stationary demand. It is worth pointing out that the framework proposed in this dissertation is not only useful in supply chain management, but also suitable to model other complex dynamic systems, such as healthcare delivery systems and energy consumption networks.
ContributorsWang, Shanshan (Author) / Wu, Teresa (Thesis advisor) / Fowler, John (Thesis advisor) / Pfund, Michele (Committee member) / Li, Jing (Committee member) / Pavlicek, William (Committee member) / Arizona State University (Publisher)
Created2010
Description
Electronic devices are gaining an increasing market share in the medical field. Medical devices are becoming more sophisticated, and encompassing more applications. Unlike consumer electronics, medical devices have far more limitations when it comes to area, power and most importantly reliability. The medical devices industry has recently seen the advantages of using Flash memory instead of Read Only Memory (ROM) for firmware storage, and in some cases to replace Electrically Programmable Read Only Memories (EEPROMs) in medical devices for frequent data storage. There are direct advantages to using Flash memory instead of Read Only Memory, most importantly the fact that firmware can be rewritten along the development cycle and in the field. However, Flash technology requires high voltage circuitry that makes it harder to integrate into low power devices. There have been a lot of advances in Non-Volatile Memory (NVM) technologies, and many Flash rivals are starting to gain attention. The purpose of this thesis is to evaluate these new technologies against Flash to determine the feasibility as well as the advantages of each technology. The focus is on embedded memory in a medical device micro-controller and application specific integrated circuits (ASIC). A behavioral model of a Programmable Metallization Cell (PMC) was used to simulate the behavior and determine the advantages of using PMC technology versus flash. When compared to flash test data, PMC based embedded memory showed a reduction in power consumption by many orders of magnitude. Analysis showed that an approximated 20% device longevity increase can be achieved by using embedded PMC technology.
ContributorsHag, Eslam E (Author) / Kozicki, Michael N (Thesis advisor) / Schroder, Dieter K. (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2010
Description
The constant scaling of supply voltages in state-of-the-art CMOS processes has led to severe limitations for many analog circuit applications. Some CMOS processes have addressed this issue by adding high voltage MOSFETs to their process. Although it can be a completely viable solution, it usually requires a changing of the process flow or adding additional steps, which in turn, leads to an increase in fabrication costs. Si-MESFETs (silicon-metal-semiconductor-field-effect-transistors) from Arizona State University (ASU) on the other hand, have an inherent high voltage capability and can be added to any silicon-on-insulator (SOI) or silicon-on-sapphire (SOS) CMOS process free of cost. This has been proved at five different commercial foundries on technologies ranging from 0.5 to 0.15 μm. Another critical issue facing CMOS processes on insulated substrates is the scaling of the thin silicon channel. Consequently, the future direction of SOI/SOS CMOS transistors may trend away from partially depleted (PD) transistors and towards fully depleted (FD) devices. FD-CMOS are already being implemented in multiple applications due to their very low power capability. Since the FD-CMOS market only figures to grow, it is appropriate that MESFETs also be developed for these processes. The beginning of this thesis will focus on the device aspects of both PD and FD-MESFETs including their layout structure, DC and RF characteristics, and breakdown voltage. The second half will then shift the focus towards implementing both types of MESFETs in an analog circuit application. Aside from their high breakdown ability, MESFETs also feature depletion mode operation, easy to adjust but well controlled threshold voltages, and fT's up to 45 GHz. Those unique characteristics can allow certain designs that were previously difficult to implement or prohibitively expensive using conventional technologies to now be achieved. One such application which benefits is low dropout regulators (LDO). By utilizing an n-channel MESFET as the pass transistor, a LDO featuring very low dropout voltage, fast transient response, and stable operation can be achieved without an external capacitance. With the focus of this thesis being MESFET based LDOs, the device discussion will be mostly tailored towards optimally designing MESFETs for this particular application.
ContributorsLepkowski, William (Author) / Thornton, Trevor (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Goryll, Michael (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2010
Description
Surgery is one of the most important functions in a hospital with respect to operational cost, patient flow, and resource utilization. Planning and scheduling the Operating Room (OR) is important for hospitals to improve efficiency and achieve high quality of service. At the same time, it is a complex task due to the conflicting objectives and the uncertain nature of surgeries. In this dissertation, three different methodologies are developed to address OR planning and scheduling problem. First, a simulation-based framework is constructed to analyze the factors that affect the utilization of a catheterization lab and provide decision support for improving the efficiency of operations in a hospital with different priorities of patients. Both operational costs and patient satisfaction metrics are considered. Detailed parametric analysis is performed to provide generic recommendations. Overall it is found the 75th percentile of process duration is always on the efficient frontier and is a good compromise of both objectives. Next, the general OR planning and scheduling problem is formulated with a mixed integer program. The objectives include reducing staff overtime, OR idle time and patient waiting time, as well as satisfying surgeon preferences and regulating patient flow from OR to the Post Anesthesia Care Unit (PACU). Exact solutions are obtained using real data. Heuristics and a random keys genetic algorithm (RKGA) are used in the scheduling phase and compared with the optimal solutions. Interacting effects between planning and scheduling are also investigated. Lastly, a multi-objective simulation optimization approach is developed, which relaxes the deterministic assumption in the second study by integrating an optimization module of a RKGA implementation of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to search for Pareto optimal solutions, and a simulation module to evaluate the performance of a given schedule. It is experimentally shown to be an effective technique for finding Pareto optimal solutions.
ContributorsLi, Qing (Author) / Fowler, John W (Thesis advisor) / Mohan, Srimathy (Thesis advisor) / Gopalakrishnan, Mohan (Committee member) / Askin, Ronald G. (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2010
Description
Current trends in the Computer Aided Engineering (CAE) involve the integration of legacy mesh-based finite element software with newer solid-modeling kernels or full CAD systems in order to simplify laborious or highly specialized tasks in engineering analysis. In particular, mesh generation is becoming increasingly automated. In addition, emphasis is increasingly placed on full assembly (multi-part) models, which in turn necessitates an automated approach to contact analysis. This task is challenging due to increases in algebraic system size, as well as increases in the number of distorted elements - both of which necessitate manual intervention to maintain accuracy and conserve computer resources. In this investigation, it is demonstrated that the use of a mesh-free B-Spline finite element basis for structural contact problems results in significantly smaller algebraic systems than mesh-based approaches for similar grid spacings. The relative error in calculated contact pressure is evaluated for simple two dimensional smooth domains at discrete points within the contact zone and compared to the analytical Hertz solution, as well as traditional mesh-based finite element solutions for similar grid spacings. For smooth curved domains, the relative error in contact pressure is shown to be less than for bi-quadratic Serendipity elements. The finite element formulation draws on some recent innovations, in which the domain to be analyzed is integrated with the use of transformed Gauss points within the domain, and boundary conditions are applied via distance functions (R-functions). However, the basis is stabilized through a novel selective normalization procedure. In addition, a novel contact algorithm is presented in which the B-Spline support grid is re-used for contact detection. The algorithm is demonstrated for two simple 2-dimensional assemblies. Finally, a modified Penalty Method is demonstrated for connecting elements with incompatible bases.
ContributorsGrishin, Alexander (Author) / Shah, Jami J. (Thesis advisor) / Davidson, Joe (Committee member) / Hjelmstad, Keith (Committee member) / Huebner, Ken (Committee member) / Farin, Gerald (Committee member) / Peralta, Pedro (Committee member) / Arizona State University (Publisher)
Created2010
Description
The essence of this research is the reconciliation and standardization of feature fitting algorithms used in Coordinate Measuring Machine (CMM) software and the development of Inspection Maps (i-Maps) for representing geometric tolerances in the inspection stage based on these standardized algorithms. The i-Map is a hypothetical point-space that represents the substitute feature evaluated for an actual part in the inspection stage. The first step in this research is to investigate the algorithms used for evaluating substitute features in current CMM software. For this, a survey of feature fitting algorithms available in the literature was performed and then a case study was done to reverse engineer the feature fitting algorithms used in commercial CMM software. The experiments proved that algorithms based on least squares technique are mostly used for GD&T; inspection and this wrong choice of fitting algorithm results in errors and deficiency in the inspection process. Based on the results, a standardization of fitting algorithms is proposed in light of the definition provided in the ASME Y14.5 standard and an interpretation of manual inspection practices. Standardized algorithms for evaluating substitute features from CMM data, consistent with the ASME Y14.5 standard and manual inspection practices for each tolerance type applicable to planar features are developed. Second, these standardized algorithms developed for substitute feature fitting are then used to develop i-Maps for size, orientation and flatness tolerances that apply to their respective feature types. Third, a methodology for Statistical Process Control (SPC) using the I-Maps is proposed by direct fitting of i-Maps into the parent T-Maps. Different methods of computing i-Maps, namely, finding mean, computing the convex hull and principal component analysis are explored. The control limits for the process are derived from inspection samples and a framework for statistical control of the process is developed. This also includes computation of basic SPC and process capability metrics.
ContributorsMani, Neelakantan (Author) / Shah, Jami J. (Thesis advisor) / Davidson, Joseph K. (Committee member) / Farin, Gerald (Committee member) / Arizona State University (Publisher)
Created2011
Description
Optimization of surgical operations is a challenging managerial problem for surgical suite directors. This dissertation presents modeling and solution techniques for operating room (OR) planning and scheduling problems. First, several sequencing and patient appointment time setting heuristics are proposed for scheduling an Outpatient Procedure Center. A discrete event simulation model is used to evaluate how scheduling heuristics perform with respect to the competing criteria of expected patient waiting time and expected surgical suite overtime for a single day compared to current practice. Next, a bi-criteria Genetic Algorithm is used to determine if better solutions can be obtained for this single day scheduling problem. The efficacy of the bi-criteria Genetic Algorithm, when surgeries are allowed to be moved to other days, is investigated. Numerical experiments based on real data from a large health care provider are presented. The analysis provides insight into the best scheduling heuristics, and the tradeoff between patient and health care provider based criteria. Second, a multi-stage stochastic mixed integer programming formulation for the allocation of surgeries to ORs over a finite planning horizon is studied. The demand for surgery and surgical duration are random variables. The objective is to minimize two competing criteria: expected surgery cancellations and OR overtime. A decomposition method, Progressive Hedging, is implemented to find near optimal surgery plans. Finally, properties of the model are discussed and methods are proposed to improve the performance of the algorithm based on the special structure of the model. It is found simple rules can improve schedules used in practice. Sequencing surgeries from the longest to shortest mean duration causes high expected overtime, and should be avoided, while sequencing from the shortest to longest mean duration performed quite well in our experiments. Expending greater computational effort with more sophisticated optimization methods does not lead to substantial improvements. However, controlling daily procedure mix may achieve substantial improvements in performance. A novel stochastic programming model for a dynamic surgery planning problem is proposed in the dissertation. The efficacy of the progressive hedging algorithm is investigated. It is found there is a significant correlation between the performance of the algorithm and type and number of scenario bundles in a problem instance. The computational time spent to solve scenario subproblems is among the most significant factors that impact the performance of the algorithm. The quality of the solutions can be improved by detecting and preventing cyclical behaviors.
ContributorsGul, Serhat (Author) / Fowler, John W. (Thesis advisor) / Denton, Brian T. (Thesis advisor) / Wu, Teresa (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2010