Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 106-107). / The Department of Defense (DoD) presented a need to transform its Military Psychological Health Enterprise (MPHE) at multiple levels. It had been established that Enterprise Architecting would be used as an approach to perform the transformation but the way in which the multiple levels of the enterprise would be transformed had yet to be determined. The study began with an investigation into the current state of a low-level component of the MPHE. This investigation invoked Enterprise Architecting techniques to determine the as-is state of this low-level enterprise. Then, the results of the Enterprise Architecting analysis were combined with multilevel analysis techniques to create a framework that supported transformation of a complex, multilevel enterprise. It was determined that upon using Enterprise Architecting techniques to identify the dominant views of a low-level component of a multilevel Enterprise, the structure of the levels the enterprise as well as the interactions between the levels can be used to understand the impacts of decisions made at higher levels of the enterprise. In the specific case of the DoD MPHE, the dominant views were found to be Organization, Process, and Information. By investigating these dominant views in more depth, the ways in which its resources interacted while performing relevant tasks in this micro-level enterprise (Camp Lejeune MPHE) were determined. This information was transformed into objective data, which was then combined with the information about how the levels of the DoD MPHE interact to suggest a framework for modeling potential future states of the enterprise. This will support both the design and selection of a transformation plan for the enterprise. The descriptive application of the suggested framework provided in this thesis supports both the design and selection of a transformation plan for the enterprise. / by Elizabeth Cilley Southerlan. / S.M.in Engineering and Management

Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, February 2013. / Cataloged from PDF version of thesis. "September 2012." / Includes bibliographical references (pages 80-82). / Enterprises, companies and organizations around the world strive to achieve competitive advantage by designing and implementing more advanced business and organizational architectures, streamlined and robust processes and structures, and effective and scalable management systems and practices. Industry, academia and management consulting companies have developed a variety of organizational models, change frameworks and transformation roadmaps to facilitate and to support business improvement activities and initiatives. The overall change management landscape, however, remains rather vague, overlapping and fragmented at the same time. To reduce this ambiguity and to be able to make a better-educated choice of models and frameworks to use, a close examination, classification, mapping and analysis of leading models and frameworks is conducted here. Common themes and distinct features are identified. An alternative high level organizational model is proposed. The coupled nature and duality of organizational models and change frameworks are identified and explored. Macro and meso levels of change management are considered and bridged via the classification of change management actions and interventions and the decomposition of change management planning and transformation design phases. To complement high level change management frameworks with applied tools, a change management projects scoring approach called "BLUE-over-RED" is proposed. In addition, an attempt to formulate a formal problem of organization transition trajectory optimization using the apparatus of operations research and graph theory is made. / by Dmitry Uspenskiy. / S.M.in Engineering and Management

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2003. / Includes bibliographical references (leaves 84-88). / Supply chain flexibility is introduced and its importance is discussed. This is followed by a review of the flexibility literature in manufacturing, supply chain, economics, strategy, organizational design, and industrial networks. Next, tools for evaluating flexibility are discussed: Decision analysis, decision trees, and real options. Lastly, an analysis of the literature and tools is incorporated into a set of guidelines for dealing with flexibility decisions. / by James B. Taylor. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. / Includes bibliographical references (leaves 164-169). / On August 3, 2007, President George Bush signed into law HR1 the "Implementing Recommendations of the 9/11 Commission Act of 2007." The 9/11 Act requires 100% scanning of US-bound containers at foreign seaports by 2012 through the use of non-intrusive (NII) and radiation detection equipment. Maritime stakeholders and the government community have actively debated the feasibility of this plan, citing economic impacts, barriers to global trade and insufficient technology and physical space. This thesis focuses on importer concerns relating to potential shipment delays, financial burdens, sourcing issues and contingency planning concerns in global supply chain operations. Using port statistics, field study data as well as industry insights, frameworks are developed to identify major stakeholder issues and quantify the financial costs and delay risks bourn across the entire supply chain. Cost and delay analyses are based on 2 prototypical ports - a small/low-volume export port and a large/high-volume export port. Cost analysis is performed for a consolidated (port authority) level installation and a segmented (terminal operator) level installation to calculate a per-box scanning fee. Queuing models and Monte-Carlo simulations are also developed to quantify truck congestion due to primary scanning and the risk of containers missing vessels due to secondary inspections. Results of the cost analysis indicate that scanning configurations, particularly related to NII, greatly affect the-per box scanning cost. It is not economically feasible to scan only US-bound containers at half of the 600 ports with direct connections to the US. Analysis of truck congestion suggests that the ramp metering effect of the entry gate can help to abate congestion at the scanning area. / (cont.) Analysis on secondary inspection delays revealed that under a set of assumptions that reflect current operations, the risk of containers missing sailings could potentially increase to 1.5%, which may in turn require a 0.5% to 5% increase in safety stock. Our study shows that cost and delay implications of 100% export US-bound container scanning may be less severe than industry anticipated. Supply chain disruptions due to scanning is best mitigated through earlier container dispatch, increased safety stock or increased scanning infrastructure and personnel at ports. / by Allison C. Bennett and Yi Zhuan Chin. / M.Eng.in Logistics

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 115-119). / Concerns over climate change and a reliance on CO₂-emitting fossil fuels for a majority of the world's energy supply have motivated the development of carbon dioxide capture and storage (CCS). However, CCS is not yet commercially available, and key technical roadblocks remain. However, the external circumstances for developing the technology, such as weak climate policy and tight public finances, have changed dramatically over the past four years and current RD&D roadmaps are poorly adapted to the new realities. In order to rethink U.S. CCS policy, and to provide a realistic roadmap for technology development, this thesis provides an overview of the key technical roadblocks, an analysis of the impact of the new realities on CCS investments, and a novel method for finding the optimal way of allocating scarce public resources to CCS RD&D. The U.S. has responded to the changing political context in two notable ways. First, Enhanced Oil Recovery (EOR) has received increased attention due to the positive value that EOR storage puts on CO₂. Second, the EPA has proposed a 1000 lbs CO₂/MWh emission standard that would require new coal plants to install CCS. Using a stochastic generation expansion model, this thesis concludes that low natural gas prices make fuel switching rather than CCS investment the most likely compliance method. Moreover, should these standards be gradually tightened, CCS will likely be deployed on natural gas plants before coal plants. More generally, the model highlights the importance of considering uncertainty when analyzing CCS investments, and results differ notably depending on whether probability distributions over parameters are considered or not. With limited funds available for technology development there is a striking need to ensure that limited resources are allocated strategically. Whereas designing optimal technology RD&D portfolios has traditionally been dealt with qualitatively, this thesis develops a quantitative model for choosing optimal portfolios of demonstration projects. The strength of new model is how it incorporates the different uncertainties associated with CCS, allowing decision makers to observe how different underlying assumptions affect project choices. Based on my analyses, I make six recommendations for CCS technology development in times of uncertainty, many of which are major departures from current U.S. CCS policy. First, the U.S. should focus more on pilot-scale development of novel capture concepts promising to significantly reduce cost. Second, if gradually tightening emission standards is to be the primary mechanism to reduce power sector CO2 emissions, then the U.S. should also demonstrate CCS on natural gas plants. Third, granting a limited number of coal plants a higher CO₂ emission standard could help bring CCS plants online in challenging times. Fourth, relying almost exclusively on projects with EOR storage is unlikely to be a sound long-term policy. Because of the significant variability across geologic storage reservoirs, at least some demonstration projects must focus on CO₂ storage in saline formations. Finally, with tightening public finances it becomes increasingly important to coordinate demonstration efforts globally to avoid unproductive overlap. / by Jan Eide. / S.M.in Technology and Policy

Thesis: Ph. D. in Human Systems Engineering, Massachusetts Institute of Technology, Engineering Systems Division, 2014. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 217-230). / Recent advances in autonomous system capabilities have improved their performance sufficiently to make the integration of unmanned and autonomous vehicles systems into human-centered civilian environments a realistic near-term goal. In these systems, such as the national highway system, mining operations, and manufacturing operations, unmanned and autonomous systems will be required to interact with large numbers of other unmanned vehicle systems as well as with manned vehicles and other human collaborators. While prior research provides information on the different methods of controlling unmanned vehicles and the effects of these methods on individual vehicle behavior, it has typically focused on only a small number of unmanned systems acting in isolation. The qualities that provide the desired behavior of an autonomous system behavior in isolation may not be the same as the characteristics that lead to desirable performance while interacting with multiple heterogeneous actors. Additionally, the integration of autonomous systems may include constraints on operations that limit interactions between manned and unmanned agents. It is not clear which constraints might be most effective in promoting safe operations and how these constraints may interact with unmanned system control architectures. Examining the effects of unmanned systems in these large, complex systems in reality would require significant capital investment and the physical construction and implementation of the un- manned vehicles of interest. Both of these aspects make empirical testing either difficult or impossible to perform and may also limit the ability of testing to fully examine all the parameters of interest in a safe and efficient manner. The objective of this thesis is the creation of a simulation environment that can replicate the behavior of the unmanned vehicle systems, manned vehicles, and human collaborators in the environment in order to enable an exploration of how parameters related to individual actor behavior and actor interactions affect performance. The aircraft carrier flight deck is chosen as an example domain, given that current operations require significant interactions between human collaborators and manned vehicles and current research addresses the development of unmanned vehicle systems for flight deck operations. Because the complexity of interactions be- tween actors makes the creation of closed-form solutions of system behavior difficult, an agent-based modeling approach is taken. First, a list of actors and their characteristic tasks, decision-making processes, states, and parameters for current aircraft carrier flight deck operations was generated. Next, these models were implemented in an object-oriented programming language, enabling the definition of independent tasks, actors, parameters, and states. These models were later extended to incorporate features of unmanned vehicle control architectures by making minor modifications to the state, logic functions, or parameters of current agents (or tasks). This same tactic can be applied by future researchers to further pursue examinations of other in influential aspects of system performance or to adapt the model to other domains. This model, the Multi-Agent Safety and Control Simulation (MASCS), was then compared to data for current flight deck operations to calibrate and partially validate simulation outputs, first addressing an individual vehicle task before proceeding to mission tasks utilizing many vehicles at once. The MASCS model was extended to incorporate models of different unmanned vehicle control architectures and different safety protocols that affect vehicle integration. These features were then tested at different densities of mission operations on the flight deck and compositions (unmanned vs. manned) of missions in order to fully explore the interactions between variables. These results suggest hat productivity on the flight deck is more heavily influenced by the safety protocols that in influence vehicle integration as opposed to the types of unmanned vehicle control architecture employed. Vehicle safety is improved by increasing the number of high-level constraints on operations (e.g. separating unmanned and manned aircraft spatially or temporally), but these high-level constraints may conflict with implicit constraints that are part of crew-vehicle interactions. Additional testing explored the use of MASCS in understanding the effects of changes to the operating environment, independent of changes to unmanned vehicle control architectures and safety protocols, as well as how the simulation can be used to explore the vehicle design space. These results indicate that, at faster operational tempos, latencies in vehicle operations drive significant differences in productivity that are exacerbated by the safety protocols applied to operations. In terms of safety, a tradeoff between slightly increased vehicle safety and significant increases in the risk rate of crew activity is created at faster tempos in this environment. Lastly, the limitations and generalizability of the MASCS model for use in other Heterogeneous Manned-Unmanned Environments (HMUEs) was discussed, along with potential future work to expand the models. / by Jason C. Ryan. / Ph. D. in Human Systems Engineering

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 163-178). / A health care delivery chain is a series of treatment steps through which patients flow. The Emergency Department (ED)/Inpatient Unit (IU) chain is an example chain, common to many hospitals. Recent literature has suggested that predictions of IU admission, when patients enter the ED, could be used to initiate IU bed preparations before the patient has completed emergency treatment and improve flow through the chain. This dissertation explores the merit and implications of this suggestion. Using retrospective data collected at the ED of the Veterans Health Administration Boston Health Care System (VHA BHS), three methods are selected for making admission predictions: expert opinion, naive Bayes conditional probability and linear regression with a logit link function (logit-linear regression). The logit-linear regression is found to perform best. Databases of historic data are collected from four hospitals including VHA BHS. Logit-linear regression prediction models generated for each individual hospital perform well based on multiple measures. The prediction model generated for the VHA BHS hospital continues to perform well when predictive data are collected and coded prospectively by nurses. For two weeks, predictions are made on each patient that enters the VHA BHS ED. This data is then summarized and displayed on the VHA BHS internet homepage. No change was observed in key ED flow measures; however, interviews with hospital staff exposed ways in which the prediction information was valuable: planning individual patient admissions, personal scheduling, resource scheduling, resource alignment, and hospital network coordination. A discrete event simulation of the system shows that if IU staff emphasizes discharge before noon, flow measures improve as compared to a baseline scenario where discharge priority begins at 1pm. Sharing ED crowding or prediction information leads to best patient flow performance when using specific schedules dictating IU response to the information. This dissertation targets the practical and theoretical implications of using prediction to improve flow through the ED/IU health care delivery chain. It is suggested that the results will have impact on many other levels of health care delivery that share the delivery chain structure. / by Jordan Shefer Peck. / Ph.D.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2005. / Includes bibliographical references (leaves 57-60). / The global village in which we live enables increased trade and commerce across regions but also brings a complicated new set of challenges such as terrorist activity, human and drug smuggling and theft in foreign or domestic locations. Containers travel the globe, across all seven continents. In the wake of intensified security concerns since the September 11, 2001 attacks, tracking containers and their contents presents an increasing concern for those institutions and personnel charged with ensuring their security. This thesis analyzes the risks associated with global container transport. The concept of an e-container is set forth as a risk mitigation technology that uses real-time monitoring of a container's physical status acquired from an array of embedded RFID-enabled sensors. A framework is suggested that relates sensor-identified signatures and phenomena to behaviors representing breaches in container security. A theoretical model suggests which sensors are required to identify the individual breaches in order to mitigate container security risk. / y Adam Ian Schlesinger. / M.Eng.in Logistics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2010. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student submitted PDF version of thesis. Page 247 blank. / Includes bibliographical references (p. 239-246). / This research analyzes how a telecommunications regulator can balance regulation with innovation, at a reasonable cost. This question has gained critical importance for telecom regulators as the unregulated Internet technologies such as voice and video over Internet disrupt the regulated traditional technologies such as telephony and television and the historical paradigm of the regulator. The existing U.S. telecommunications regulations were created in the integral age. In that paradigm, functional components that constitute a service compliant with regulation resided inside the network core; each operator was vertically integrated and controlled the total functionality necessary to deliver a service; a few such operators controlled the industry; they faced low competition and were under limited pressure to adopt innovation; and consumers had limited choice. The Internet has introduced a polar opposite paradigm-the modular age. In this paradigm, functional components that constitute a service are dispersed across the network core and edges; each firm controls only a subset of the total functionality necessary to constitute a service; many modular firms interoperate to deliver a service; firms compete fiercely and are under great pressure to innovate; and consumers enjoy far greater choice due to the multi-modal competition among multiple technologies. Although transitioning from an integral to a modular age dramatically flips the environment, the current regulatory response to this dramatic shift has been hesitant to shift its intellectual roots. Consequently, this thesis describes and analyzes the new telecommunications paradigm and explores its implications for an appropriate regulatory paradigm. The research uses the regulation of voice communications in the United States as a representative case. We analyze the new telecommunications paradigm as a dynamic complex system. Our research approach rests upon four principles of systems: two organizational principles (hierarchy and feedback) and two behavioral principles (emergent behavior and strategic and statistical behavior).The telecommunications system is viewed as one of the many subsystems that together fulfill the objectives of a society. The dynamics of the telecommunications system itself are conceptualized as those resulting from the interactions of four subsystems: regulatory dynamics, corporate strategy dynamics, consumer dynamics, and technology dynamics. The regulatory objectives to be fulfilled are conceived as an emergent property of such a system of systems. To carry out this research, we have developed a system-level dynamic feedback model and two case studies. As modular entrants of Internet-based technology disrupt integrated incumbents of traditional technology, bewildering dynamic complexity complicates decision-making by policymakers, managers, consumers, and technologists alike. Our model makes understandable the emergent behavior amidst the uncertainty that surrounds such a disruption phenomenon. The model formulations are behavioral. They are derived from the existing theories of technology and industry disruption, where possible. Alternatively, where theories have a gap, the decision processes of stakeholders, gleaned from unstructured interviews, are mathematised as the basis for the model formulations. The resulting structure is a fully endogenous systems model of regulation, competition, and innovation in telecommunications. In the first case study we analyze the regulatory environment of pre vs. post-Internet periods, both quantitatively and qualitatively. For the analysis, public comments in response to the Telecommunications Act of 1996 Notice for Proposed Rulemaking (NPRM) are compared with those in response to the IP-Enabled Services NPRM published in 2004. The analysis demonstrates how the differences in the integral and modular age are reflected in the regulatory record. The second case study analyzes how market, technology, organizational, and regulatory uncertainties affect technology and industry disruption. For this case, we use a combination of industrial statistics and content analysis of media publications. The analysis demonstrates the limits to technology and industry disruption. The case studies complement the model in two ways: first, they facilitate further refinement of the systems model; second, they empirically validate the arguments deduced from model analysis. Through this research we answer three questions: (1) Can the regulatory structure designed in an integral age-in its objectives, obligations (requirements), and enforcement mechanisms-work for a modular age? (2) How can regulators and managers improve decision making amidst the uncertainty surrounding the disruption of an integrated technology and industry by a modular one? (3) What is the new role of the telecommunications regulator and how can it be fulfilled in the modular age of the Internet? Our analysis shows that the current regulatory structure is inadequate for responding to the challenges the modular age poses. Firstly, the current objectives are appropriate but cannot be met unless regulators discontinue the merely efficiencycentered thinking and begin to address objectives at the societal level. Secondly, the current obligations may attain short-term goals, but have undesirable long-term consequences. Devising obligations that are appropriate in the long-term requires regulators to discontinue myopic measures such as incremental regulation of new technologies. Finally, the current enforcement mechanisms are blunted by the dynamic complexity of the modular age. Enforcing regulations effectively in the modular age necessitates adding to the regulatory quiver new mechanisms that are more versatile than the merely adversarial command-and-control mechanisms. Through model analysis, we demonstrate how a lack of understanding of the various uncertainties, and misperceptions of feedback in a complex system where regulators, firms, consumers, and technologists constantly interact, could lead to decisions that are costly for regulators as well as managers. Yet, as we demonstrate, with better grasp of the dynamic complexity involved, they can significantly improve decision-making to meet the challenges of the modular age. We argue that the most critical role for the telecommunications regulator in the new telecommunications paradigm is to sustain a balance between regulation and innovation, at a reasonable cost. Achieving such a balance in a modular structure is not trivial because of several natural tendencies. First, achieving high compliance at low cost is difficult because in highly modular architectures and industries, coordination costs, such as the time to build consensus, can be inordinately large. Second, keeping the innovationlevel high is difficult because it requires fighting the natural tendency of modular firms to gain and abuse market power. We propose a combination of two policy levers-Limiting Significant Market Power (SMP) Accumulation and Building Broad-based Consensus around Regulatory Issues-that most effectively achieve the desired balance and remain inadequately explored in the United States. We contend that implementing these policy levers will require, first, a more broadly construed antitrust regulation in the United States that will ensure higher modularity, and, second, a telecommunications regulatory agency that is empowered and organized to pursue objectives at the societal level and to build broad-based consensus among divergent interests in a highly modular structure. / by Chintan Vaishnav. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student submitted PDF version of thesis. / Includes bibliographical references (p. 303-311). / Climate change impacts, including sea-level rise and changes in tropical storm frequency and intensity, will pose signicant challenges to city planners and coastal zone managers trying to make wise investment and protection decisions. Meanwhile, policymakers are working to mitigate impacts by regulating greenhouse gas emissions. To design effective policies, policymakers need more accurate information than is currently available to understand how coastal communities will be affected by climate change. My research aims to improve coastal impact and adaptation assessments, which inform climate and adaptation policies. I relax previous assumptions of probabilistic annual storm damage and rational economic expectations-variables in previous studies that are suspect, given the stochastic nature of storm events and the real-world behavior of people. I develop a dynamic stochastic adaptation model that includes explicit storm events and boundedly rational storm perception. I also include endogenous economic growth, population growth, public adaptation measures, and relative sea-level rise. The frequency and intensity of stochastic storm events can change a region's long- term economic growth pattern and introduce the possibility of community decline. Previous studies using likely annual storm damage are unable to show this result. Additionally, I consider three decision makers (coastal managers, infrastructure investors, and residents) who differ regarding their perception of storm risk. The decision makers' perception of risk varies depending on their rationality assumptions. / (cont.) Boundedly rational investors and residents perceive storm risk to be higher immediately after a storm event, which can drive down investment, decrease economic 3 growth, and increase economic recovery time, proving that previous studies provide overly optimistic economic predictions. Rationality assumptions are shown to change economic growth and recovery time estimates. Including stochastic storms and variable rationality assumptions will improve adaptation research and, therefore, coastal adaptation and climate change policies. / by Travis Read Franck. / Ph.D.