Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, May, 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (pages 73-77). / The world is facing a grave plastic waste problem. It is not new that we hear about oceanic death and morbid landfills. Only 8% of all the plastic produced is recycled in the US. This grotesque situation has been worsened by the Chinese ban of plastic waste imports from the developed western nations as of 2018. In this research we assess the feasibility of a novel approach to using existing e-commerce reverse logistics channels to take back post-consumer plastic. We use product sales data to estimate the post-consumer plastic volume. We then, design a mixed integer linear programming (MILP) based optimization model to assess different take-back routes and calculate various operational costs. In addition to the optimization model we determine the feasibility of this process by considering cost offsets such as price of virgin plastics. After that, we conduct a scenario-based sensitivity analysis to understand systemic cost and overall profit. We used the results of these analyses to formulate the strategic recommendations for companies interested in promoting or implementing e-commerce-based recycling programs. Finally, we assess the greenhouse gas emissions and corresponding externality costs through this process and perform a qualitative assessment of the stakeholder networks vital to making such a system operational. In conclusion, our results suggest that in certain scenarios it is economically feasible to facilitate a take-back process for post-consumer plastic using existing e-commerce-based reverse logistics channels while maintaining minimal additional emissions in the process. / by Saikat Banerjee. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 56-67). / In previous decades the postal sector experienced drastic changes. Liberalization and digitization resulted in a continuous mail market decline. Simultaneously the rise of Internet resulted in a booming e-commerce parcel delivery market. To cope with these ongoing market developments Postal Operators (POs) need to rigorously restructure their delivery networks frequently in order to reduce distribution cost. Moreover, POs are searching for synergy opportunities between the mail and parcel delivery network. A recent development in the postal sector is the use of light electric freight vehicles (LEFV) in urban and suburban areas as a sustainable and cheaper solution for last-mile delivery. Limited research has been performed regarding the impact of LEFV on distribution cost and network design. This thesis introduces a two echelon location routing model for POs to determine the optimal network configuration for mail and parcel delivery in order to minimize total distribution costs using LEFV in their vehicle portfolio. A mixed integer linear programming model (MILP) is proposed including a multi-depot VRP for the first tier and continuous approximation techniques (CA) for the second tier. Using a real-world application at the Dutch PO - PostNL - the impact of merging the mail and parcel network as well as the impact of introducing LEFV was established. Results suggest that adding LEFV to the vehicle fleet leads to a distribution cost saving of 3% in the separate mail and parcel network. LEFV are a worthy alternative to vans in dense city areas, due to their high speed on short distances and their maneuverability in city areas. While merging the parcel and mail network with the current vehicle fleet leads to a distribution cost reduction of 1%, the inclusion of LEFV in a merger scenario leads to a saving of 5%. Therefore, adding LEFV to the vehicle fleet enables POs to seize synergy opportunities between the distribution networks. / by Ronald Veldman. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 48-49). / During the past few years, blockchain technology has shown great potential to disrupt existing supply chain finance solutions, as it could increase the efficiency of invoice processing and provide a more transparent and secure transactions. However, the costs and benefits of implementing blockchain technology in supply chain finance for involved parties are still unclear, since research on the topic is scarce. This thesis explores the net value of implementing blockchain technology in supply chain finance arrangement by using cost-benefit analysis. A cost-benefit model and the operating processes of traditional and blockchain-based supply chain finance solutions are proposed and applied to a real-world case study. We prove that blockchain technology increases the total net benefit among involved parties participating in the supply chain finance arrangement as a result of improved efficiency of invoice processing. We also find that suppliers would benefit from blockchain-based supply chain finance if the benefit from the unlocked working capital outweighs the cost of the platform fee. Another finding is that the buyer does not benefit from the technology in terms of unlocked working capital. / by Patara Panuparb. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 86-95). / The U.S. energy portfolio is set to undergo drastic change in the coming decades. Policies to reduce emissions combined with growing demand for energy will test existing infrastructure. Large reserves of shale gas provide an attractive near-term solution to help states transition from coal-powered plants to cleaner fuel. Most commercial production growth in shale gas occurred in the early 2000's. Yet most of the natural gas pipeline system was constructed long before the "shale gas revolution". Almost half of all interstate transmission pipeline mileage is over 50 years old. In order to best utilize the country's natural gas reserves, the pipeline transportation network must respond to accommodate changing flow patterns. Consumption of natural gas often occurs far from production sites. This research seeks to identify states where the required inflow and outflow of natural gas may be constrained by pipeline capacity limitations. / A literature review of the natural gas production and consumption outlook reveals an expected steady growth in the industry until 2050. The current state of the system is then evaluated. A simple analysis is performed to determine the inflow and outflow transmission pipeline capacity utilization rates for each state. It is found that some states, namely Florida, California, and New England, are indeed at risk for natural gas shortages. It is further discovered that some states with access to reserves, namely Pennsylvania, may be limiting production due to insufficient outflow pipeline capacity. The pipeline approval process, managed by FERC is reviewed. The process is found to be inefficient at allocating new capacity where it is needed. Alternative solutions to address the supply risk were also considered. A literature review confirms that pipeline transportation has a much lower incidence of accidents per volume of natural gas moved than either rail or truck transportation. / The dangers of underground storage are also explained. A major risk in the current pipeline system, age, is investigated using a simple analysis of PHMSA data. It is found that three of the top four causes of accidents are related to pipeline age, with older lines having higher rates of accidents. Lastly, the risks of over-reliance on natural-gas for electricity generation are discussed and it is recommended that states take a more balanced long-term approach to energy development and incorporate locally accessible renewable energy. / by Lauren E. Sittler / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 72-75). / The rapid growth in e-commerce volumes, coupled with customer expectations of faster, flexible and cheaper parcel deliveries is increasing the pressure on retailers to design the most efficient delivery network. Collection-and-delivery points (CDPs) allow for the aggregation of demand and enable reductions in travel time and costs. CDPs also help minimize additional tours arising due to failed deliveries or failed pickups for returns. We formulate an optimization model that integrates CDPs in the design of the overall distribution network, including the location of upstream transshipment facilities. The model accounts for changes in demand density due to the placement of CDPs. It considers demand aggregation at the CDP for both forward and return flows, and the impact of failed deliveries and failed return pickups on the routing cost. The model considers multiple different route options and solves them using extended routing cost approximation formulae thus allowing the implementation of the model on large-scale problems. We then apply the model to solve a real-world case study on the last-mile distribution network of a major Brazilian e-commerce retailer. The results demonstrate that failed deliveries and failed return pickups increase both the last-mile cost and the overall cost of distribution, and CDPs effectively reduce these costs by aggregating the demand and minimizing travel time. / by Himanshu Rautela. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, May, 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (pages 74-80). / Information sharing is one of the established approaches to improve demand forecasting and reduce the bullwhip effect, but it is infeasible to do so effectively in a long supply chain. Using the polystyrene industry as a case study, this thesis explores the usage of modern natural language processing (NLP) techniques in a deep learning model, known as NEMO, to forecast the demand of a commodity -- without requiring downstream companies to share information. In addition, this thesis compares the effectiveness of such an approach with other non-deep learning approaches, specifically an ARIMA model and a gradient boosting model, XGBoost, to demand forecasting. All three models returned large forecast errors. However, NEMO tracked the volatility of actual data better than the ARIMA model. NEMO also had better success in predicting demand than the XGBoost model, returning approximately 20% better Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) scores. This result suggests that NEMO can be improved with better data, but other issues, such as legality of text mining, need to be considered and addressed before NEMO can be used in day-to-day operations. In its current form, NEMO can be used alongside other forecasting models and provide invaluable information about upcoming demand volatility. / by William W.J. Teo. / M. Eng. in Supply Chain Management / M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 51). / On-time delivery is a key metric in the trucking segment of the transportation industry. If on-time delivery can be predicted, more effective resource allocation can be achieved. This research focuses on building a predictive analytics model, specifically logistic regression, given a historical dataset. The model, developed using six explanatory variables with statistical significance, results in a 76.4% resource reduction while incurring an impactful error of 2.4%. Interpretability and application of the logistic regression model can deliver value in predictive power across many industries. Resulting cost reductions lead to strategic competitive positioning among firms employing predictive analytics techniques. / by Rafael Duarte Alcoba and Kenneth W. Ohlund. / M. Eng. in Supply Chain Management

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 52-53). / To be competitive, businesses must make supply network design decisions, but often with only limited information and under uncertain conditions. How can an organization understand trade-offs between supply network decisions, without relying on complex, black-box models that require extensive data collection and hidden assumptions? We apply approximation methods to estimate and compare total logistics cost of supply network designs under various business conditions, such as variations in demand, changing costs, and shifting production policies. The method is applied to the real-world example of XYZ Co, evaluating network design choices for a new, rapidly growing product category: fresh foods. The method is used to evaluate tradeoffs between five distinct network designs for supply of these highly perishable foods to XYZ Co stores from a sole regional supplier. The model provides insights to help understand tradeoffs and key cost drivers, thereby channeling subsequent, more intensive and time- consuming analysis. / by Cyril Khamsi and Veronica Stolear. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 42-43). / This thesis analyzes the impact on prices and capacity of trucking industry due to the introduction of ELD mandate. This mandate requires truck drivers to record their working hours in a specified electronic device instead of a pen and paper method. This thesis utilizes the change in average truck driver working hours, cost of ELD equipment and distance from origin to destination of truck loads to determine the potential impact on trucking market. The models used provide an estimation of the impact on capacity and cost and the likelihood of impact on the economics of trucking industry. / by Chan How Law. / M. Eng. in Logistics

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 46-47). / Large pharmaceutical companies struggle to find innovative ways to reduce work-in-process inventory in their production facilities. In our research, we focus on the tradeoff between inventory and production capacity through investing in new facilities and equipment. This tradeoff will depend on the company's objectives and what it is willing to give up in return for reducing inventory. We found that increasing capacity to reduce work-in-process inventory by investing in new facilities is not always the most favorable approach in terms of net present value. However, for flexibility or lead-time improvements, it may make sense to proceed with the investment. We developed multiple scenarios considering the company's future plans to reduce inventory or grow. These scenarios provide insights into the factors that improve the attractiveness of the investments and those that do not. Our financial analysis along with the guidelines and procedures that we have developed help the sponsor company most effectively reach its goal to reduce its work in process inventory. / by Karim Kamareddine and Yihong Yao. / M. Eng. in Logistics