Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2010. / Cataloged from student submitted PDF version of thesis. / Includes bibliographical references (p. 78-86). / Liquid fuels such as gasoline and diesel are traditionally derived from petroleum. Since petroleum has the potential to be exhausted, there is interest in large scale production of fuels from renewable sources. Currently, ethanol and bio diesel are liquid fuels that are mainly derived from field crops. This paper examines the supply chain challenges and issues that exist for bringing biofuel production up to scale. One major challenge that exists is how to transport the feedstock from a farm to a refinery in the most cost efficient manner. One way to improve transportation efficiency of feedstock is to increase the energy density of the feedstock. However, increasing the density of a feedstock comes with a cost. We use switchgrass as a case study and examine the tradeoff between higher transportation costs in transporting a less energy dense feedstock to processing a feedstock to increase its energy density. We show that creating ethanol from switchgrass in the United States is not competitive in price to gasoline without government subsidies, but as the supply chain matures, efficiencies gained will narrow the gap. / by Sooduck Chung [and] Michael Farrey. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009. / Includes bibliographical references (leaves 62-64). / LargeCo, a large multinational consumer goods manufacturing and distribution company, has been pursuing initiatives to improve the responsiveness of its supply network. The impact of these initiatives on the supply network is measured through a few Key Performance Indicators (KPIs). LargeCo has invested in a responsive supply chain so that it can respond swiftly to unpredictable market demand and minimize lost sales. Reduction in lost sales leads to growth in sales. LargeCo is interested in finding out if its responsive supply chain is contributing to sales growth. In particular, LargeCo would like to determine whether improvement in KPIs, driven by improvement in the responsiveness of the supply chain, has a relationship with improvement in sales. LargeCo uses a measure of sales known as Sales Net of Effects (SNE) which measures sales net of the effects of discounts, marketing and promotions. Establishing a relationship between KPIs and sales will help LargeCo measure the value of responsiveness in its supply network. This research project develops an analytical framework using an econometric model to determine if relationships exist between the KPIs and sales and a causal model to explain the relationships. The econometric model shows that relationships exist between two of the KPIs - Days of Inventory and Supply Chain Cycle Time, and sales. The causal model explains how these KPIs and sales are linked. / by Jaime Garza Ramírez and Subramanian Mambakkam Suryanarayanan. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006. / Includes bibliographical references (leaves 86-87). / Non-profit humanitarian relief organizations have typically been unable to measure the performance of their supply chains due to an inability to centrally capture data from operations. With the recent development and implementation of information technology systems that can support the logistics function of these organizations, the data is now available to measure performance, but what is still lacking is a central framework of metrics that measures performance according to the organization's strategic goals. First, this thesis reviews the best practices noted in performance measurement systems of the logistics functions in military and commercial organizations and applies them to the humanitarian sector. Second, the thesis suggests a framework of key performance indicators to be implemented in an international non-profit humanitarian organization based on the unique strategic goals of the sector. The thesis then applies this proposed framework to two actual operations performed by this organization. / (cont.) The analysis performed herein proves that a measurement system would help strengthen the organization's ability to deliver goods to beneficiaries more efficiently and effectively. Finally, the thesis addresses feasibility issues of implementing a measurement system in the non-profit sector and also describes the next steps of opportunities related to measurement systems within humanitarian logistics. / by Anne Leslie Davidson. / M.Eng.in Logistics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 220-224). / Commonality, or the sharing of components, processes, technologies, interfaces and/or infrastructure across a product family, represents one of many potential tools for increasing corporate profitability. Industrial interest in commonality is strong, but results appear to be mixed. A rich stream of academic research has examined commonality (typically under terms such as "product platforms" and "platform-based development") but has not emphasized the benefits and penalties of commonality, a topic that is critical to effective product family planning and lifecycle management, and ultimately, to improving corporate profitability. This dissertation leverages field research and a simple cost model to examine commonality in the context of complex product families. The core research effort was focused on conducting seven case studies of complex product families (aircraft, automobiles, satellites, and capital equipment). While the case studies provided a wealth of general insights, the studies were focused on examining divergence and lifecycle offsets, two critical topics that influence the benefits and penalties of commonality, yet appear to be inadequately addressed by the literature. Divergence refers to the tendency for commonality to reduce with time, for both beneficial and non-beneficial reasons. Lifecycle offsets refer to temporal differences between the lifecycle phases of product family members. Lifecycle offsets alter the potential benefits and penalties of commonality and their apportionment to individual products. / (cont.) Additionally, key factors identified during the literature review and case studies were translated into a simple two-product cost model of development and production in order to demonstrate key research insights in a more analytical manner. The case studies provide a refined view of commonality that reflects the realities of industrial practice. The cases indicate that complex product families are developed in a mostly sequential manner; that commonality is highest during the product family planning phase and then declines significantly throughout the lifecycle; and that development focuses more on reusing prior product baselines than on enabling future, potential commonality. The case studies also identified challenges in the evaluation of commonality and its lifecycle management. The case findings and simple cost model contribute to an improved understanding of commonality, while the recommendations offer potential paths to improved corporate profitability. / by Ryan C. Boas. / Ph.D.

Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2012. / Cataloged from PDF version of thesis. "June 2012." / Includes bibliographical references. / Venture Capital (VC) has been an important driver of innovation, entrepreneurship and economic growth in the U.S. and around the world for the past few decades. The astounding success of Venture Capital prompted various countries' attempts to emulate the U.S. model and create an indigenous venture capital industry. Several attempts are being pursued to emulate this success and create an indigenous Venture Capital industry in India. This thesis examines efforts to create a Venture Capital and Private Equity industry in India and the various factors that influence this process. / by Shravan K. Surineni. / S.M.in Engineering and Management

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009. / Includes bibliographical references (leaves 78-79). / This thesis examines a distribution multi-echelon production-inventory system subject to stochastic demand in the steel industry. The sponsor company, Ternium (a South American steel producer), needs to provide short service times under low inventory costs. The goal of this thesis is to generate a model and conclusions to determine where and how much inventory to hold to satisfy a required service level. Risk pooling is an important consideration for this problem; once a steel product advances in the production process, it has less possibilities of use for different customers. Since distribution stochastic multi-echelon inventory systems have no known optimal formulated solution, algorithms and simulation will be used determine a strategy. The analysis uses simulation as the main method to solve the problem. A distribution multi-echelon model is developed. Different cost scenarios are defined and run. Next, the best set of solutions, defined as the service level-holding cost efficient frontier, is found. To increase the understanding of the problems and provide a better interpretation of the results, we test the sensitivity of the solution and the impact of the input parameters. Later, we explore different ways of solving the problem using alternative modeling methods to determine the base-stock levels. Finally, these solutions are tested with simulation and compared with the best results. Through the analysis, we find that simulation is a powerful tool for finding the best inventory strategy, but the results are very sensitive to cost parameters. / (cont.) Modeling allows important saving costs if we compare the best solutions found with the simplest policy used by the company (allocating all safety stock to the echelon closest to the customer). Finally, we demonstrate that some of the alternative modeling methods used to allocate inventory perform well, but simulation is an important complement to test and fine-tune these models. / by Juan D. Iocco. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008. / Includes bibliographical references (leaf 74). / Many firms worldwide have adopted the process of Sales & Operations Planning (S&OP) process where internal departments within a firm collaborate with each other to generate a demand forecast. In a collaborative demand planning process buyers and sellers collaborate with each other to generate a mutually agreed upon forecast which takes into account the needs and limitations of both buyers and sellers. In this research we concentrate on finding out the value from both statistical and qualitative forecasts. We apply standard forecasting algorithms to generate a statistical forecast. We also generate a hybrid model that is a weighted technique using both a statistical and qualitative forecast. Then we evaluate the statistical, hybrid, and qualitative collaborative forecasts using an error analysis methodology. Finally we recommend an approach for forecasting a family of items based on our analysis and results. We also recommend changes to the existing process so that our recommendations on the forecasting approach can get seamlessly integrated into the overall process. / by Ratan Jha. / M.Eng.in Logistics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 379-385). / Processes in manufacturing, services, and healthcare are complex socio-technical systems composed of intricately sequenced activities supported by elements drawn from multiple domains. While many of these processes offer high performance, their complexity can make their design, improvement, troubleshooting, and change difficult due to the many possible and unforeseen interactions between elements. This thesis develops a design methodology and multi-domain network model for complex process design, change management, process improvement, and troubleshooting. As part of the methodology a feasibility analysis method based on solving the minimum cost flow problem for a network of process alternatives is presented to identify feasible processes subject to stakeholder requirements and constraints including performance, flexibility, modularity, and other system properties. A model based on Multi-Domain Matrix (MDM) concepts is developed specifically for process analysis called the Multi-Domain Process Matrix model (MDPM) to enumerate and analyze the interactions between process elements such that process performance under change and troubleshooting scenarios can be improved. The graph theory basis of the MDPM model enables its analysis using a proposed set of metrics derived from communications, social, and process network literature. As a demonstration of the use of the methodology, a complex DNA sequencing based surveillance process for Methicillin resistant Staphylococcus aureus (MRSA) in the US healthcare system is designed and a prototype implemented. Rapid advances in DNA-based technologies have greatly expanded the range of processes available to the clinical microbiology laboratory, however, integrating these new processes into a comprehensive surveillance system presents significant challenges. Many of these new technologies are still in early stages of development, require multidisciplinary teams to support them, and must undergo significant optimization presenting significant barriers to their rapid adoption despite the pressing need to understand and control antibiotic resistance. Data from the prototype MRSA surveillance process show significant variation at the DNA level between patient cases, providing evidence for the urgent need for a DNA sequencing based microbial surveillance process as part of clinical microbiology efforts in the US healthcare system. However, results of applying the process design methodology and MDPM model analysis indicate significant work remains to reduce complexity, further improve key technology elements, gain acceptance, develop key organizational infrastructure, and Page 3 of 385 redesign the process to efficiently absorb the rapid technology change expected in DNA sequencing. The MDPM model is used to develop a roadmap of specific multi-domain projects addressing these issues to accelerate the deployment of a national DNA sequencing based surveillance system. / by Robert Nicol. / Ph.D.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2007. / "June 2007." / Includes bibliographical references (leaves 69-71). / Production planning in premium fresh produce supply chains is challenging due to the uncertainty of both supply and demand. A two-stage planning algorithm using mixed integer linear programming and Monte Carlo simulation is developed for production planning in the case of a premium branded tomato. Output from the optimization model is sequentially input into the simulation to provide management with information on expected profit and customer service levels at the grocery retail distribution center. The models are formulated to incorporate uncertainty in demand, yield, and harvest failure. The outcome of the algorithm is an annual production plan that meets minimum customer service requirements, while optimizing profit. The resulting timing, location, and quantity of acres suggested by the algorithm are evaluated against the current industry heuristic of performing deterministic calculations, based on average yield and demand, and then planting double the required acreage. The suggested two-stage planning algorithm achieves 90 percent customer service with 20 percent less planted acres and almost three times as much profit than the industry heuristic of doubling the acreage. / by Joshua Matthew Merrill. / M.Eng.in Logistics

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006. / Includes bibliographical references (leaves 97-98). / This research examines the impact of inventory pre-positioning on humanitarian operations. The study identifies optimal locations for warehousing non-consumable inventories required for initial deployment of aid. These facility location problems are geometric optimizations using mean annual homeless resulting from hazards (atmospheric disruptions, floods, waves, landslides, seismic disruptions, volcanoes and wildfires) as an indirect estimation of demand for infrastructure inventory. Minimization of per capita distance, or the average global distance from the nearest warehouse to a forecasted homeless person, is advanced as the objective. An array of formulations, solved using mixed-integer linear programs, predict optimal facility configurations, and corresponding per capita distances, under incremental facility constraints; thereby measuring sensitivity of mean distance to facility proliferation. The problems are devised to also gather insights into maximal covering and the effects of initial conditions. / (cont.) Moreover, demand patterns, along with correlated variables such as population and hazard frequency, offer views of regional vulnerability to natural disasters. The results also exhibit the absence of re-configuration, indicating that location decisions may not be impacted by the number of facilities planned. / by Anup Roop Akkihal. / M.Eng.in Logistics