Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 98-100). / The U.S. Coast Guard has been part of several major organizational transformations. A little over a decade ago, the Naval Engineering enterprise underwent a significant organizational transformation. Due to the nature of the Coast Guard's organizational size, expansive geographical laydown of its cutters and boats, and inherent responsibilities, the Coast Guard must maximize the use of each finite resource. The purpose of this thesis is to examine and analyze the current transformed Surface Forces Logistics Center Industrial Operations Division (SFLC-IOD) organization. Additionally, it evaluates how can systems-thinking inform future enterprise transformation opportunities for improved efficiencies in the delivery of depot-maintenance to the surface fleet. Moreover, the objective is to propose alternative enterprise architectures that deliver value to all stakeholders. The primary methodology for this research utilizes the Architecting Innovative Enterprise Strategy (ARIES) framework, supported by literature reviews, and internal and external stakeholder interviews. This research identifies four alternative architectures that provide value to the SFLC customer ecosystem; the selected architecture supports a gap identified in the stakeholder analysis by providing a dedicated industrial depot-maintenance service to major cutters clustered at dense centers of gravity. Additionally, it focuses on providing dependable and repeatable specialized services to its waterfront customers; this affords the surface fleet requisite flexibility in operational planning and execution of its mission. The qualitative analysis suggests that the U.S. Coast Guard should explore a self-sustaining depot-maintenance posture due to the U.S. Navy's increased dependency on private commercial, industrial base activities in support of their non-nuclear surface naval fleet. / by Eric J. Jones. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 208-217). / Considering the large capital outlay and the long duration for recouping investments on Oil and Gas projects, it is concerning that a number of projects in the Industry continue to exceed their approved cost and schedules by significant margins. Engineering is often named as a culprit for Project execution issues manifesting in engineering and construction rework, start-up delays, startup performance and early facility life issues. Worthy of note is the increasing complexities of Oil and Gas production facilities and systems stemming from more remote operational locations, newer production technologies and a drive for autonomous facilities. Hence, the need for an Engineering approach to address current system development issues and poised to take on the complexity challenges of the systems of the future. Despite the benefits of Model Based System Engineering (MBSE), and System Engineering broadly, in addressing system complexities in industries like Aerospace, there are sparse references that address benefits of such as approach in the Oil and Gas industry. In addition, there is a gap in literature on the Oil and Gas Industry that analyze the underlying design approach, used over decades in the industry, relative to project outcomes. This research attempts to address the gaps using a case-study approach to analyze MBSE implementation in Aerospace for insights towards an implementation in the Oil and Gas Industry. This research evaluates the underlying discipline-based design approach in the industry against a System Engineering benchmark; analyzes key design issues categories in the industry identifying candidates for MBSE Application; and presents an MBSE Implementation scorecard for the Oil and Gas Industry. The main contribution of this research is the development of a framework for System design in the Oil and Gas Industry as part of the System/Product Development cycle. The framework addresses the underlying design approach as a contributor to Engineering process outcomes; and provides a method that facilitates a systemic approach to design enabled by appropriate modeling to ensure systemic emergence is understood; and adequately characterized with direct impacts to the Engineering process and downstream System development activities. It proffers a new way of thinking design on Oil and Gas projects. / by Funmilola Adeoti Asa. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 189-191). / Chevron, one of the world's leading integrated energy companies, faces new challenges as it aggressively pursues digital innovation and acceleration. Oil and gas well construction, in particular, will continue to incorporate automation to enhance capabilities and gain a competitive advantage. These changes to the technology landscape will fundamentally alter the nature of well construction and the interactions pertaining to well design, operation, and maintenance. WellSafe, Chevron's well control assurance program, was created to ensure process safety hazards are controlled and to prevent large-scale incidents. Since its inception in 2015, WellSafe has brought incremental improvements. To continuously adapt and keep pace with the ongoing digital transformation, WellSafe must use systems engineering principles, methods, and tools to improve in the face of a changing environment. System-Theoretic Accident Models and Processes (STAMP) and System-Theoretic Process Analysis (STPA) developed by MIT's Nancy Leveson help assess WellSafe and uncover opportunities to improve. This thesis analyzes the WellSafe assurance program and generates system requirements based on causal factors that impact the efficacy of the program. This, in turn, helps identify safe system boundaries and constraints that must be enforced to achieve system safety. This thesis demonstrates the value of STPA as an integrated analysis method and offers specific recommendations to improve the WellSafe program. / by Brandon S. Baylor. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 69-70). / Tanker markets are one of the many markets to experience extreme volatility, historically realizing drastic swings in earnings of up to 260% week over week. This volatility has placed pressure on tanker market participants to forecast future returns, create guidance for their investment decisions, and develop an analytical advantage. In this thesis, we develop analytics models to predict average earnings in the VLCC and Suezmax tanker market segments. Through the use of principal components regression, we forecast market returns with endogenous and exogenous market factors. A challenge lies in the fact that key variables--supply, demand, and utilization--are not necessarily available at the time of prediction. Accordingly, we develop an original two-step framework that first predicts vessel supply using classification models, and then embeds the imputed variables into the downstream principal components regression model. Methodologically, this procedure provides a novel approach to integrate classification outputs into a downstream predictive model. Based on our findings, we apply the forecast to two investment decisions; how to hedge the tanker market using time charter contracts and how to determine the optimal economic approach to lightering considering uncertainty in demand and in market returns. In both instances, we demonstrate how the use of an accurate tanker market forecast can be leveraged to make better managerial decisions, historically amounting up to 35 million dollars per year in the lightering decision and 10 million dollars per contract in the time charter investment. / by Kayhan Babakan. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, May, 2020 / Cataloged from the official version of thesis. "May 2020." / Includes bibliographical references (pages 79-83). / As medical devices become more complex, the need for methodical and structured design processes has never been greater. Due to the great complexity of the aerospace industry, both qualitative and quantitative methods of technology planning and design assessment have been implemented with great success in that industry. These methods, such as technology roadmapping and multi-disciplinary design optimization, show great promise in the medical device field that has traditionally lacked such rigor. This research accomplishes four objectives: Benchmarking of the current development methods used in the medical device industry; Evaluating the current state of the art of adhesive biomaterials; Application of technology roadmapping methods as they relate to the medical device industry, specifically bone adhesives; and, Development of a multidisciplinary design optimization model used for the development of a novel mineral-organic adhesive used in lumbar spine fusion procedures. A Multi-objective optimization found that an optimal design of the mineral-organic adhesive resulted in a slight (1 minute) increase in surgical time, it resulted in a significant reduction of approximately $1,020 in product cost, and more importantly, a reduction in the estimated healing time from 72 to 24 weeks as compared to the baseline design for utilization in the lumbar spine fusion surgical procedure. By accomplishing these four objectives, this thesis outlines the methods and models necessary to bring to market paradigm shifting technologies that will be the catalyst for significant change in the healthcare industry. / by Michael C. Brown. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, May, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 65-68). / Due to increasing internet access and mobile phone usage, the collection of data has exploded globally in the past decade. At the same time, the processing power and storage capabilities have become cheap and prevalent, and sophistication and complexity of AI and machine learning algorithms have advanced and are widespread. Data is a new type of capital. Public governance has not yet caught up, and because of the specialized technical expertise required, the public sector has permitted and sometimes even invited private companies to make the rules. Caught up in these trends is a tension between cities wanting to be at the forefront of technology while needing to act in the public interest and protect the marginalized and underrepresented. This thesis utilizes a comparative analysis of two case studies, Toronto and New York, to examine the existing urban data governance models and identify some learnings from the comparison. Within each case study, the thesis employs systems architectural concepts such as stakeholder mapping and architectural decisions to illustrate differences and highlight shortcomings and potential recommendations to address in future policy proposals. / by Shelley Chan. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, May, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 89-91). / While moving to the cloud increases flexibility for many organisations around the world, it also presents its own set of operational risks and complexities when it comes to keeping data and workflows secure. As data becomes digitized, it is becoming more fruitful for bad actors to try to engage in data theft or disrupt online services for their financial gain, corporate espionage, or general intent to disrupt a service. Computers are also becoming more powerful and sophisticated than ever, allowing them to brute force what were once considered top of the line cryptographic ciphers and algorithms in no time. The cost of protecting an infrastructure is increasing both financially and in terms of human resources needed to support a system's security. Companies are relying on the cloud to provide that protection, and one of the ways the cloud provides it is through Edge nodes that sit in front of their infrastruture. Edge nodes are the first line of defense against threats to a web application. This thesis explores a new heuristic for approaching threat generation and detection in a network. It aims to demonstrate that with a proper grammar definition along with a strategy, and a reward system, a genetic algorithm can perform better than the existing rulebased system used to generate and defend against a wide breadth of attacks. This proposes solution focuses on three types of attacks: Data Exfiltration, Server Hijack, and Denial of Service. The goal is to demonstrate that computationally searching for vulnerabilities does not scale well with a rule based system while a genetic algorithm can handle an increase of breadth in attacks with more elegance and better results. / by Sofiane Djeffal. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 171-173). / The United States (US) Navy struggles to sustain its ranks of aviators; it therefore seeks to produce more pilots, more quickly, without additional resources. This thesis employs the Architecting Innovative Enterprise Strategy (ARIES) framework, Factory Physics methodologies, and experimental models to investigate new policies, organizational structures, processes, and knowledge that support this imperative in the Navy's Primary Flight Training commands. It addresses promising changes to Primary and how to facilitate them. The ARIES framework, and associated stakeholder interviews, logically investigate the qualitative intricacies of Primary to illustrate its operation. Quantitative internal baseline methods suggest policies for student inventory management, student prioritization, and aircraft allocation. Each technique is tested by a joint discrete process and agent-based student model. This investigation suggests that Primary is challenged by an excessive student inventory and unclear operations policies. It asserts that these two factors create excessive wait time and resource-wasting rework that drastically reduce production performance. Experimentation results qualify the trends of these detriments and quantify their impacts on throughput and training time. The work concludes that a tightly governed start rate can be paired with three concurrent policies to raise average throughput by 62% and reduce average time to train by 52%. 1. Prioritize students by their total time in training to reduce the impacts of rework. 2. Allocate resources to the largest queues to increase peak performance and capacity. 3. Manage student inventory via a constant work in process (CONWIP) policy to reduce the impacts of rework and dampen sensitivity to resource variations. It also suggests minimally disruptive changes to Primary's architecture that aim to reduce organizational, knowledge, and process complexities while promoting sustainability, scalability, and evolvability in the enterprise. Four core concepts summarize the rearchitecting effort: 1. Employ data analytics in the current infrastructure to aid in decision making. 2. Balance organizational centralization to support flexible but consistent performance. 3. Consolidate and reinforce institutional knowledge in stable employees. 4. Promote knowledge sharing and coordination to improve organizational learning. This thesis asserts that application of these new policies and re-architecting concepts will promote production performance, organizational knowledge, and proactive management. / by Nicholas R. Hanley. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 75-79). / When searching for jobs, job applicants are not only motivated by monetary compensation alone, the meaning and social effects of the work also matter. Pro-social motivation, the desire to have a positive impact on other people or social collectives also play an important role in job searching. On the other hand, organizations also have many incentives to promote pro-social jobs during the recruiting processes and accordingly design pro-social characteristics in job postings. Using latest machine learning techniques, we could possibly quantify pro-social characteristics in massive amount of job postings and potentially predict pro-social messages advertised in online job postings. In this thesis, we take up the challenge of developing novel measures of pro-social that satisfactorily address the problems identified with existing measures of pro-social. We proposed implementations of two different machine learning approaches to quantitatively measure pro-social messages from over five million online job postings documentation and effectively predict pro-social jobs, with 79% and 94% prediction accuracy yield from methodology I and methodology II respectively. Based on those approaches, we evaluate the model performance and measure correlation of industries' use of pro-social messages in job postings to compare the effectiveness of two models on several metrics. / by Zhuoqiao Hong. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 177-184). / Autonomous underwater vehicles hold great potential in the realms of industry, military, scientific, and personal usage. The applications of intelligently applied autonomous functionality could improve work performed on subsea infrastructure, commercial shipping lane maintenance, canal and channel observation, search and rescue, military applications, as well as general scientific research. Given such potential, and supposing that existing technological barriers to progress could be overcome, what could a potential system architecture of future autonomous underwater vehicles look like? Fundamentally this thesis asks: "could novel architectures of AUV systems - specifically pairing AUVs to remote service platforms - lead to significant performance increases?" In approaching this subject, a specific case study is leveraged where autonomous underwater vehicles were extensively used: the search for Malaysian Air flight 370. This specific mission profile has been extensively documented by others laying a comprehensive framework. It represents the single largest search and rescue operation ever performed. Within this thesis, whole-system performance metrics of this search and rescue operation are compared against calculated performance metrics of systematically generated possible architectures. In decomposing the system into its functional elements, a deterministic evaluation is executed followed by a probabilistic examination of the system as modeled. The results of the probabilistic model are also interpreted via a Pareto ranking methodology where Pareto surfaces are identified in multidimensional tradespaces. These component cases which comprise the Pareto surface are subsequently removed from the dataset, and the process is run again. This iterative approach demonstrated that the top ten performing architectures were comprised entirely out of architectures with either one or four AUVs. The outputs of these models are subsequently compared against the baseline system used in the search for MH370. Following the analysis, a major fault was identified in the foundations of all of the models surrounding a figure of merit wherein the time to the seafloor was calculated for all architectures. All of the top ten performing design vectors - systems which contained one or four AUVs - were unchanged due to this error. Architectures which were affected by this error -- systems with more than four AUVs -- were impacted negatively. Several methods of re-imagining the error are presented herein as complexities that are inherent in the system, which are not handled by these models. These new emergent complexities were present in the system prior to the model construction, but unaccounted for. Discovery of this faulty assumption laid bare several architectural decisions which are unexplored in this thesis, but could provide the foundation for future work in this space. The outcome of these modeling efforts suggests that pairing an autonomous underwater vehicle with an autonomous service platform can result in increases in all performance metrics. Specific metrics which are improved include daily search area rate, calendar mission completion time, and total project cost. This improvement is specifically calibrated to the case study of MH370, but the performance metrics themselves are not exclusively applicable to search and rescue operations. This model indicates that such a system could accomplish the same mission in less time for half the cost. This thesis presents a vision of future autonomous underwater vehicle systems in which daily operational time, search area rates, calendar mission completion times, and total system costs can all be improved relative to the existing standards. Such improvements are equally applicable to commercial, industrial, military, civilian, and scientific endeavors in which autonomous underwater vehicles could be a potential tool. / by Brendan K. Horton. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program