Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2005. / Includes bibliographical references (leaf 69). / This thesis assesses the value to vendors of using point of sale data to predict what retailers will order from them. In particular, we look at how The Gillette Company can use point of sale data generated by two of their customers, (Wal-Mart and Target), to predict the orders of all of Gillette's customers combined. The thesis also examines the impact on forecasts of shortening and simplifying the demand planning process. By improving the forecast of orders from their customers, vendors like Gillette can reduce safety stock inventory which is held as protection against unpredictable demand. / by Atul Agarwal [and] Gregory Douglas Barton Holt. / M.Eng.in Logistics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. / Includes bibliographical references. / This research used a combination of a grounded theory approach and system dynamics to study the electric power system in Kenya and to model the feedback at work in the development of the system. The ethnographic study revealed the challenges faced by consumers in choosing between grid and off-grid power options. Examination of this challenge leads to the hypothesis that competition between the grid and off-grid markets is contributing to the low growth in power consumption and that there is the potential for off-grid to become the dominant option in the future. This theory guided the construction of a system dynamics model focusing on consumers' decision-making and their interaction with the operation of the system. I then used the model to explore the dynamics of the system through scenario testing. There were two key outcomes from the model. The first showed that given the parameters chosen in most cases there is a clearly dominant option, although it changes over time. This finding points to the second key outcome the model, which is that there are realistic scenarios under which off-grid generation will become the dominant supply source. This shift could be induced by either reduced overhead on photovoltaic panels or high fuel prices. The outcomes from this research have implications for future electricity planning in Kenya and elsewhere in Africa. In particular, there is a need to decouple the system from external prices or account for the extreme uncertainty in fuel prices. Given the potential shift to large-scale off grid power generation, energy planners also need to look at options for managing a decentralized power system architecture and consider how to build in options for future reintegration if a large-scale centralized generation source comes online. / (cont.) This research has both academic and applied contributions. On the academic side, it extends the range of engineering systems modeling to include qualitative factors found in an African environment. These factors include the addition of reliability and availability of the electric power grid and the biases in decision-making, which differ from those in industrialized countries. While the model clearly has direct application in Kenya, it was designed with flexibility to be expanded to include other countries and regions and could be a useful tool for understanding policy trade-offs in African electrification planning. / by Katherine Deaton Steel. / Ph.D.

Thesis: Ph. D., 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. / Most modern era software-enabled, electro-mechanical systems are becoming more complex as we demand more performance and better lifecycle properties (e.g. robustness) from them. As a consequence system development projects are becoming increasingly challenging and are falling behind in terms of schedule and cost performance. The complexity of technical systems depends on the quantity of different elements and their connectivity, i.e., complexity means a measurable system characteristic. There are three main dimensions of complexity that emerged in the context of system design and development: (1) Structural Complexity; (2) Dynamic Complexity and (3) Organizational Complexity. Structural complexity pertains to the underlying system architecture or more generally, the enabling infrastructure. Dynamic complexity refers to the complexity of the system behavior or process running on the underlying infrastructure. Organizational Complexity relates to the system development process and the organizational structure of the development team. This dissertation primarily focuses on developing a theoretical framework for structural complexity quantification of engineered systems and subsequently a complexity-based design paradigm of interconnected, complex engineered system. There are four distinct thematic parts in this dissertation: (i) theoretical development of the proposed structural complexity metric, including the metric's qualification as a valid complexity measure based on its mathematical properties; (ii) empirical validation of the proposed complexity metric based on simple experiments and application of the methodology to compute structural complexity of complex engineered systems like jet engines and advanced printing systems; (iii) systemic implications from a complexity management standpoint, including introduction of complexity budgeting for system development and linking actual complexity to human perception of complexity through the notion of complicatedness, and (iv) extension of the proposed metric to system-of-systems and a computational framework for measuring dynamic complexity. The topological complexity metric, C₃ is shown to clearly distinguish between system architectural regimes (e.g., centralized, hierarchical, transitional and distributed). The ball and stick experiment empirically establishes the super-linear relationship between structural complexity (X) and development effort (Y) with exponent, b=1.48. / by Kaushik Sinha. / Ph. D.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 101-102). / The analysis is based on one year of transactional data from a major beverage company and interviews with asset based and non-asset based truckload carriers. Throughout our research we investigate the use of asset based carriers and brokers as unique sources of capacity on low volume and medium haul lanes. We examine price escalation issues in the context of load tender rejections and daily shipment volumes on a given lane. Our study revealed that as the shipment volume goes up on a lane, prices could escalate as much as 30-40% over rates originally contracted with primary carriers. In the case of rejections though, as prices go up, the probability of not covering a load comes down. Additionally, we propose a lane aggregation methodology, which decreases variability and simplifies freight procurement for long and short haul shipments. Finally, through a carrier proximity study we demonstrate that distance from carrier domicile to pick up location has an impact on pricing for short haul shipments. Based on our findings, we identified building network robustness and creating available carrier capacity as critical factors to sustainable pricing, while still being able to maintain a high service level. / by Lukasz Kafarski and David Allen Caruso, Jr. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2003. / Includes bibliographical references (p. 121-123). / The strong bargaining power of major retailers and the higher requirements for speed, service excellence and customization have significantly contributed to transform the Supply Chain Management. These increasing challenges call for an integrated and dynamic Supply Chain Management and for a better integration and alignment with key customers, in order to reduce the firm's time-to-market and build competitive advantage. The thesis aims at providing the partner company, a major player in the consumer goods industry, with a more robust and efficient vendor managed inventory practice, so that the partner can determine the optimum inventory level to satisfy turnover, service level and lead time requirements, whereas minimizing lost sales and total costs in the system. The team developed a Supply Chain Dynamics framework to help the partner to establish new service level strategies, strongly oriented to the strategic importance of its products and customers, and to map the key system-wide drivers that impact the overall number of inventory turns, service level and total costs. Additionally, in order to run simulations and estimate the outcomes of the proposed recommendations, the team developed a "Multi-Echelon" simulator and used a commercial "Supply Chain Dynamics" simulator. / by Ricardo Wagner Lopes Barbosa [and] Edward Fan. / M.Eng.in Logistics

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2007. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Includes bibliographical references (p. 129-132). / Classical risk-based or game-theoretic security models rely on assumptions from reliability theory and rational expectations economics that are not applicable to security threats. Additionally, these models suffer from serious deficiencies when they are applied to software-intensive, socio-technical systems. Recent work by Leveson in the area of system safety engineering has led to the development of a new accident model for system safety that acknowledges the dynamic complexity of accidents. Systems-Theoretic Accident Models and Processes (STAMP) applies principles from control theory to enforce constraints on hazards and thereby prevent accidents. Appreciating the similarities between safety and security while still acknowledging the differences, this thesis extends STAMP to security problems. In particular, it is applied to identify and mitigate the threats that could emerge in critical infrastructures such as the Air Transportation System. Furthermore, recommendations are provided to assist systems engineers and policy makers in securely transitioning to the Next Generation Air Transportation System (NGATS). / by Joseph R. Laracy. / S.M.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, June 2008. / "May 26, 2008." / Includes bibliographical references (p. 152-156). / All ES evolve as the result of stakeholder decisions and decision processes that affect their design and operation. These decision making problems often involve many stakeholders, each of whom have a say in the outcome. This has been termed a lateral alignment problem, as opposed to a unitary decision making problem. Lateral alignment focuses on group decision making where stakeholders are nominally organizationally independent, interact to maximize their own goals and simultaneously a common goal, and who are able to influence decision outcomes to varying degrees through power and influence. Previous work in the relevant literatures has focused on two variants used to assess and model group decision making. Type 0 Group Decision problems involve anonymous voting, where stakeholders do not interact. Type 1 Group Decision problems involve non-cooperative interaction where stakeholders try to maximize their self-interest through negotiation. We define the lateral alignment problem as a Type 2 Group Decision problem, which involve elements of both non-cooperative and cooperative behavior. Type 2 Group Decisions have not been fully treated in the existing literatures. In this thesis, we evaluate a prototype Type 2 Group Decisions: the Federal Open Market Committee (FOMC) from 1970-1994 as a test case. One major advantage of studying the FOMC is the availability of data and relevant analytical published work. Our original empirical findings include: 1. Information ambiguity is the major factor that impacts coalition dynamics, via the number of starting bids, in FOMC decision making. 2. Deliberation time is directly determined by information ambiguity and the relationship is the same across chairmen eras. 3. Decision efficacy falls off gradually as information ambiguity increases. / (cont.) 4. Members whose past views are best reflected as correct in hindsight appear to build up reputation and have greater influence on decision outcomes. We also develop an agent based model (ABM) to study the FOMC. As we show, the ABM is very effective at predicting observables of the FOMC decision making process. These observables are: 1. Membership in the Winning Coalition. 2. Number of Bargaining Rounds. 3. Decision Outcomes. 4. The Number of Starting Bids. In chapter 6 we discuss issues of generalizing the findings of this to other ES. Our sample includes the Food and Drug Administration (FDA), SEMATECH, and the Next Generation Air Transportation System (NGATS). / by Christopher M. Lawson. / Ph.D.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 56). / In the oilfield services industry, healthy margins and the criticality of product availability have often over shadowed the need for operational efficiency. Although those factors have not changed, the emergence of stronger industry competition and challenging economic climates have prompted ABC company to explore efficiency gains via supply chain optimization. This thesis examines and assesses opportunities for ABC Company to employ statistical inventory models, understand a variety of factors that influence inventory levels and costs, and improve its network structure. As many inventory models are not designed to accommodate SKUs that have very low rates of consumption, we also propose a methodology that will provide operational guidance and cost implications to address these types of SKUs. / by Michael Chalapong and Jake Lazarus. / 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. 109-113). / This thesis investigates broader impacts of air transportation on U.S. economic productivity, as well as market access and business location, in order to help identify how aviation supports the national economy. More traditional economic impacts are reviewed before turning to enabling impacts. Mechanisms by which air transportation might enhance economic productivity are proposed and a production model is constructed as a framework for exploring the validity of these mechanisms. Two analyses are conducted which should provide new insights to the FAA on the importance of air transportation to the U.S. economy. Focusing on the demand side of the economy, a detailed analysis of input-output (1-0) data from the Bureau of Economic Analysis (BEA) identifies where air transportation appears to be especially critical to economic production. On the supply side, U.S. Census Bureau data is used to map distributions of population, business establishments, and Fortune 500 headquarters from hub airports. Additional distribution analyses are performed for cargo airports and for select metropolitan areas. Analyses of intermediate use of air transportation provide weaker evidence than initially hypothesized as to aviation's role in supporting productivity growth. Both sets of analyses confirm that the importance of air transportation to industry is not uniform and that the government and services sectors appear to benefit from and take advantage of access to aviation more than other industry sectors. In particular, the analyses of business location relative to airports provide evidence that many service and high-value economic sectors are more concentrated near hub airports than are other industry sectors for which air transportation adds less value. / by Justin Daniel Lawrence Stilwell. / S.M.in Technology and Policy

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2007. / Includes bibliographical references (p. 111-118). / This thesis considers the problem of achieving better system performance through adaptive experiments. For the case of discrete design space, I propose an adaptive One-Factor-at-A-Time (OFAT) experimental design, study its properties and compare its performance to saturated fractional factorial designs. The rationale for adopting the adaptive OFAT design scheme become clear if it is imbedded in a Bayesian framework: it becomes clear that OFAT is an efficient response to step by step accrual of sample information. The Bayesian predictive distribution for the outcome by implementing OFAT and the corresponding principal moments when a natural conjugate prior is assigned to parameters that are not known with certainty are also derived. For the case of compact design space, I expand the treatment of OFAT by the removal of two restrictions imposed on the discrete design space. The first is that the selection of input level at each iteration depends only on observed best response and does not depend on other prior information. In most real cases, domain experts possess knowledge about the process being modeled that, ideally, should be treated as sample information in its own right-and not simply ignored. / (cont.) Treating the design problem Bayesianly provides a logical scheme for incorporation of expert information. The second removed restriction is that the model is restricted to be linear with pair-wise interactions - implying that the model considers a relatively small design space. I extend the Bayesian analysis to the case of generalized normal linear regression model within the compact design space. With the concepts of c-optimum experimental design and Bayesian estimations, I propose an algorithm for the purpose of achieving optimum through a sequence of experiments. I prove that the proposed algorithm would generate a consistent Bayesian estimator in its limiting behavior. Moreover, I also derive the expected step-wise improvement achieved by this algorithm for the analysis of its intermediate behavior, a critical criterion for determining whether to continue the experiments. / by Hungjen Wang. / Ph.D.