Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2011. / Page 150 blank. Cataloged from PDF version of thesis. / Includes bibliographical references (p. 138-149). / Human supervisory control systems are characterized by the computer-mediated nature of the interactions between one or more operators and a given task. Nuclear power plants, air traffic management and unmanned vehicles operations are examples of such systems. In this context, the role of the operators is typically highly proceduralized due to the time and mission-critical nature of the tasks. Therefore, the ability to continuously monitor operator behavior so as to detect and predict anomalous situations is a critical safeguard for proper system operation. In particular, such models can help support the decision making process of a supervisor of a team of operators by providing alerts when likely anomalous behaviors are detected. By exploiting the operator behavioral patterns which are typically reinforced through standard operating procedures, this thesis proposes a methodology that uses statistical learning techniques in order to detect and predict anomalous operator conditions. More specifically, the proposed methodology relies on hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) to generate predictive models of unmanned vehicle systems operators. Through the exploration of the resulting HMMs in two distinct single operator scenarios, the methodology presented in this thesis is validated and shown to provide models capable of reliably predicting operator behavior. In addition, the use of HSMMs on the same data scenarios provides the temporal component of the predictions missing from the HMMs. The final step of this work is to examine how the proposed methodology scales to more complex scenarios involving teams of operators. Adopting a holistic team modeling approach, both HMMs and HSMMs are learned based on two team-based data sets. The results show that the HSMMs can provide valuable timing information in the single operator case, whereas HMMs tend to be more robust to increased team complexity. In addition, this thesis discusses the methodological and practical limitations of the proposed approach notably in terms of input data requirements and model complexity. This thesis thus provides theoretical and practical contributions by exploring the validity of using statistical models of operators as the basis for detecting and predicting anomalous conditions. / by Yves Boussemart. / Ph.D.

Thesis (M. Eng. in Logistics)--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. / "June 2007." / Includes bibliographical references (leaf 65). / Retailers collect information regarding consumer purchases on a transactional basis. This data is not completely being leveraged by manufacturers in the footwear and apparel industry to increase on-shelf availability. However, certain apparel and consumer products companies have developed best-in-class methods for collecting and utilizing data to enhance supply chain visibility and to drive increased sales. A description of these best-in-class practices is provided, strategies to use the data are presented, and the importance of collaboration among supply chain partners is discussed. Further, point of sale data from a footwear and apparel manufacturer is analyzed to illustrate how the data can be leveraged to predict subsequent season sales, to improve forecasting accuracy, and to allocate replenishment inventory more effectively. / by Jeffrey Edward Axline [and] Brian Joseph Lebl. / M.Eng.in Logistics

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 153-162). / Military intelligence analysts are increasingly tasked to sift through enormous volumes of data to identify the proverbial intelligence "needle in a haystack." One specific domain exemplifying this new intelligence paradigm is network analysis of terrorist organizations. This area of intelligence analysis uses mostly commercially available software applications to leverage the powers of social network theory against large terrorism data sets. An additional challenge is the fast paced development cycle for new sensors, which are capable of collecting data at unmanageable rates. As such, analysts are in dire need of new analytical techniques that give them the ability to effectively and efficiently transform the collected data into intelligible information and, subsequently, intelligence. Therefore, the primary focus of this thesis is to analyze two visualization techniques within social network analysis, with the intent to identify which mode of visualization is most effective for the intelligence tasks of: 1) identifying leaders and 2) identifying clusters. To test the effectiveness of the visualizations, an experiment was conducted in which participants exploited matrix and node-link visualizations constructed from a surrogate terror data set. The objectives of this experiment were to test the effectiveness of the node-link visualization compared to the matrix visualization, based on two criteria: 1) effectiveness at identifying leaders and clusters within a network, and 2) the time it takes to complete each task. Participants in the experiment were all Air Force intelligence analysts and the experiment utilized a 2 (Visualization) x 2 (Task) mixed design study within-subjects on the visualization task factor and between-subjects on the visualization technique factor. The node-link visualization resulted in statistically significantly better performance in all studied scenarios where the objective was identifying leaders. Although node-link also returned a better performance than the matrix for identifying clusters, there was not a statistically significant difference. The same lack of statistical significance holds true for the completion time dependent variable. In all cases, there was not enough difference between the times produced by the node-link and matrix to determine if either offers a statistically significant decrease in the time it takes to complete tasks using either visualization. At this time, the matrix should not be universally integrated into the current methodologies used by analysts to exploit terror network visualizations until more research is conducted into the respective strengths and weaknesses within the intelligence domain. However, analysts should be independently encouraged to explore and adapt new methods of visualization into their current practices and identify new or improved versions of the visualizations identified within this thesis for future testing. / by Christopher W. Berardi. / S.M.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2004. / Includes bibliographical references. / The thesis addresses the inventory planning process for NFL Replica jerseys. The analysis is conducted from the perspective of the manufacturer's North American distribution center, and how flexibility can be employed to meet customer demands. NFL replica jerseys can be stocked either completed with player name and number, called "dressed" or as "blank" jerseys that can be customized at the distribution center. Player demand can change drastically from year to year. The result is that common practice is to minimize inventory at year-end, and treat each season as a single period. The approach taken utilizes the newsvendor model to determine the optimal stocking levels of replica jerseys given an expected demand forecast. Two modeling approaches were compared, the traditional newsvendor problem and a newsvendor model with risk pooling. The traditional newsvendor problem separated selected players to order as dressed jerseys and remaining demand to order as "blank" jerseys. The second approach, the newsvendor with risk pooling, provides a more flexible inventory plan that satisfies selected player demand using a combination of dressed and blank jerseys. The newsvendor model with risk pooling resulted in the higher expected profits then the traditional newsvendor model, and comparable service levels, but at much lower inventory levels. / by John C.W. Parsons. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 92-93). / In the truckload transportation industry in the United States, a number of indexes are published that attempt to measure changes in rates, but no single index has emerged as an industry standard. Industry participants, particularly those exposed to the spot-market, have found that existing indexes do not effectively represent their experiences in the marketplace. A widely-used and valid spot-market index could allow for more effective tactical decision-making, the development of freight derivatives, stronger analysis and negotiation of contract rates, and contracts with index-tied rates. This paper examines pricing indexes from other industries and expands upon a framework of characteristics that support successful indexes. Using this framework to evaluate existing industry indexes, it finds that two commonly used indexes are not designed appropriately for use by the spot-market. It also examines rates experienced by a large North American provider of non-asset based logistics services and finds that they differ significantly from rates measured by existing indexes. The analysis suggests that indexes of the spot market would be improved by disaggregating rate information based on geography and tender lead time. / by Andrew Bignell. / M.Eng.in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, 2014. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 45-46). / PharCo (an assumed name) is a leading global healthcare company with well-recognized brands of both pharmaceutical and consumer healthcare products. As PharCo continues to expand its global presence, product stock-outs in their pharmaceutical business unit have been consistently increasing. PharCo suspected that manufacturing quality defects were a major cause of stock-outs, reducing the production yield and preventing the company from meeting customer demand. To help test this hypothesis and address the stock-out challenge, we reviewed existing research on the subject of product stock-outs within the pharmaceutical industry. To understand PharCo's manufacturing process, we conducted on-site visits and reviewed their quality control practices. Finally, we designed a mixed methods approach that combines qualitative and quantitative techniques to analyze the root causes of product stock-outs at PharCo. The analysis revealed that, instead of manufacturing quality defects, regulatory issues were the primary cause for stock-outs at PharCo. Regulatory challenges associated with developments such as new product launches, license renewals, and formulation modifications need to be addressed for PharCo to reduce their stock-out level. / by Xuewen Sun and Bangqi Yin. / M. Eng. in Logistics

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2005. / Includes bibliographical references (p. 151-152). / The concepts of value and value stream are crucial to the philosophy of Lean, and a better understanding of how these concepts relate to product development (PD) is essential for the creation of a Lean PD strategy. This thesis focuses on value by looking at PD processes through two different value perspectives: Product Development Value Stream Mapping and Earned Value Management. Product Development Value Stream Maps (PDVSMs) were created for two different PD projects, and the tasks from the maps were analyzed for how they each create value. The official value measurement for the two projects, Earned Value Management System data, was analyzed and compared to the PDVSMs. This comparison of the two value perspectives proved valuable, as it showed that despite some misalignments, they are congruent. The comparison also highlighted several flaws in EVMS. Finally, a combined EVMS/PDVSM hybrid management tool is proposed and discussed. / by Ryan Brent Whitaker. / S.M.

Thesis: Ph. D., Massachusetts Institute of Technology, Engineering Systems Division, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 186-197). / Climate and energy security concerns have prompted policy action in the United States and abroad to reduce petroleum use and greenhouse gas (GHG) emissions from passenger vehicles. Policy affects the decisions of firms and households, which inevitably react to changing constraints and incentives. Developing and applying models that capture the technological and behavioral richness of the policy response, and combining model insights with analysis of political feasibility, are important agendas for both research and policy. This work makes four distinct contributions to these agendas, focusing on the case of climate and energy policy for passenger vehicles in the United States. First, this work contributes to econometric studies of the household response to gasoline prices by investigating whether or not U.S. households alter their reliance on higher fuel economy vehicles in response to gasoline price changes. Using micro-level household vehicle usage data collected during a period of gasoline price fluctuations in 2008 to 2009, the econometric analysis shows that this short-run vehicle switching response, while modest, is more pronounced for low income than high income households, and occurs on both a total distance and per trip basis. Second, this work makes a methodological contribution that advances the state of empirical modeling of passenger vehicle transport in economy-wide macroeconomic models. The model developments include introducing an empirically-based relationship between income growth and travel demand, turnover of the vehicle stock, and cost-driven investment both in reduction of internal combustion engine (ICE) vehicle fuel consumption as well as in adoption of alternative fuel vehicles and fuels. These developments offer a parsimonious way of capturing important physical detail and allow for analysis of technology-specific policies such as a fuel economy standard (FES) and renewable fuel standard (RFS), implemented individually or in combination with an economy-wide cap-and-trade (CAT) policy. The new developments within the model structure are essential to capturing physical system constraints, interactions among policies, and unintended effects on non-covered sectors. Third, the model was applied to identify cost-effective policy approaches in terms of both energy and climate goals. The RFS and FES policies were shown to be at least six to fourteen times as costly as a gasoline tax on a discounted basis in achieving a 20% reduction in cumulative motor gasoline use. Each of these policies was shown to have only a modest effect on economy-wide carbon dioxide emissions. Combining a fuel economy standard and a renewable fuel standard produced a gasoline reduction around 20% lower than the sum of forecasted reductions under each of the policies individually. Under an economy-wide CAT policy that targets GHG emissions reduction at least cost, obtaining additional reductions in passenger vehicle gasoline use with RFS or FES policy increases the total policy cost, and does not result in additional reductions in GHG emissions. The analysis shows the importance of integrated assessments of multiple policies that act on separate parts of a system to achieve a single goal, or on the same system to achieve distinct goals. Fourth, a political analysis shows how, in the case of climate and energy policy for passenger vehicles, sharp trade-offs exist between economic efficiency and political feasibility. These tensions are shown to exist at the level of policy justification, policy type, and design choices within policies. The pervasiveness of these tensions suggests that economically-preferred policies will face the greatest barriers to implementation. This work concludes by integrating the findings from each of the individual parts to make recommendations for policy. Recognizing the heterogeneity of household responses, the prescriptions of the economic analysis, and the tensions between these prescriptions and politics, policy options should be evaluated not only based on cost effectiveness, but also on their ability to serve as stepping stones toward desirable end states by providing incentives to revisit and increase policy cost effectiveness over time. / by Valerie Jean Karplus. / Ph. D.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2003. / Includes bibliographical references (leaves 32-33). / by Bradley Richard Yim. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2004. / "June 2004." / Includes bibliographical references (leaves 71-72). / Process integration has become more and more important in today's world where companies' supply chains have become more complex. Companies around the world are beginning to realize the importance of integrating their supply chain business processes to achieve fulfillment excellence. Unfortunately, process integration is still somewhat a novel concept and relatively little research has been conducted in examining how companies can effectively implement successful process integration across their supply chains. To complicate matters further, many companies still confuse the concept of business process integration with that of mere data integration. The primary motivation for this research study is to provide a framework on how best to implement process integration to achieve fulfillment excellence. The methodology employed in this particular study comprises the use of two case studies with real-life companies, which provide real-world examples of how companies try to "integrate" their complex supply chain processes. A deep and thorough analysis is then conducted to identify the challenges presented by the firm's current practices from a business process integration perspective. Further analysis then provides an overall view of what is done right and what could have been improved. Last but not least, a generalized framework of best practices and a prescription of how best to implement successful process integration to achieve fulfillment excellence are presented. / co-authored by Marcos Buelvas [and] Sonita Lontoh. / M.Eng.in Logistics