Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 52-53). / With increasing cost of labor, additional regulatory pressures, and changing consumer habits, consumer goods manufacturers in low-cost sourcing countries in Asia are increasingly looking at manufacturing technologies to help. These manufacturing technologies in the apparel industry range from electronic sewing machines that have been around for decades to the precision control robotics that are still in the development phase. We aim to demonstrate the benefit of technology adoption and catalog the barriers faced in implementation. To achieve this, the project first explores the extent of technology adoption within the Li & Fung supplier network through the use of the technical audit; a questionnaire which includes 5 technology related questions that are filled out on-site by a third party auditor. This analysis is then expanded through a vendor survey launched to hundreds of factories that asks additional questions around technology adoption. Finally, this analytical review of technology adoption is complemented by an in-depth design and implementation of a technology system, specifically an Industrial Internet of Things (IIoT) system, at a bottling factory. This study further demonstrates the potential impact of technology in factories and the challenges to implementation. In demonstrating the benefit of specific technologies, we are able to show a statistically significant correlation of higher performance with two technologies from the technical audit. Through our IIoT project, we also simulate how an inventory buffer optimized with the data gathered by the IIoT can increase productivity by as much as 34%. Finally, we catalog financial, strategic, and organizational barriers that factories face. / by Zachary Jason Stauber. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 63). / In November 2013, Boeing launched a derivative of the 777 airplane, known as the 777X, which will be the largest and most efficient twin-engine jet in the world when it enters service in 2020. In parallel with new airplane development, Boeing is transforming its existing 777 production system through an initiative known as FPS, or Future Production System (FPS), in order to create a more safe, flexible and productive manufacturing environment that accommodates the 777 and 777X. This will require upgrades to be made to the existing 777 manufacturing process. FPS requirements include the need for a system to better support the mechanic by implementing "final stage tool kitting." My project scope was to plan, design, and implement a tool kitting process for the Service Ready Wing (SRW) area of 777 Manufacturing. The first part of this thesis evaluates the prescribed solution of tool kitting and attempts to evaluate its potential cost and benefit to 777 SRW Manufacturing. The thesis then systematically approaches the problems for which tool kitting is trying to solve, rather than the solution itself. The result is a set of solutions discussed in Chapter 7 that focuses on reducing tool inventory, floor space, and non-value added time of the mechanic. This thesis is intended to serve as a model for all areas of 777 and 777X Manufacturing as teams continue to work towards understanding how to improve tool management. By providing a systematic approach to evaluating the current-state tool usage in a specific manufacturing area, and focusing proposed solutions on actions that solve a defined problem set agreed to by key stakeholders, this work will help guide other groups towards creating successful, sustainable tool conveyance solutions. / by Erin E. Golden. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 73). / This thesis provides a deep mathematical analysis of the diverse alternatives for routing models considering an Omni-channel supply chain. The natural evolution of supply chains from traditional brick-and-mortar stores to an omni-channel supply chain, encompassing and merging e-commerce together with a multi-channel concept, allows businesses to reach new levels of operational efficiency by leveraging inventory closer to the customer and making decisions on the fly on how to better and more cheaply provide a service/product to the final consumer. The flexibility and benefits, unfortunately, do not come without a certain dose of complexity and further development of the supply chain tactical implementation and systems. New alternatives to fulfill customer orders are available, which require greater screening among the different alternatives. An effective routing model becomes essential to make sure these alternatives are properly considered in order to satisfy both the consumer and retailer objectives, such as on-time delivery of orders, retail stores' service levels, and fulfillment costs. / by Federico Markowicz. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 55). / One challenge that many manufacturing companies face is the transition from lab-scale product development to full-scale production. Techniques and processes that are used by research and development (R&D) personnel or within a lab may not be suitable for a production environment, and directly applying an R&D process to production may overlook certain capabilities and requirements. This challenge can be made more difficult if there is a development "wall" between R&D and production. R&D personnel are familiar with new products and underlying technologies and have learned important lessons throughout the development process, while production personnel have experience with full-scale production and necessary manufacturing requirements. Getting these two groups to share knowledge and work together can be key to the successful industrialization of a new product or technology. Texstars is a Texas-based aerospace manufacturer that is currently transitioning a new transparency (optically clear structural material) product based on a polyurethane material technology branded TexeronTM, from R&D to production. TexeronTM provides a significant market opportunity to Texstars and its transition requires the development of new equipment and capabilities to reach full-scale production. This thesis examines the industrialization process of TexeronTM , including the definition of manufacturing requirements, the selection of equipment, and product-specific tooling design, and provides a working example of how a small company can balance production requirements with cost considerations. Throughout the project, we catalyzed a link between R&D and production personnel at Texstars to enable knowledge transfer. We find that this link could have been established earlier to better anticipate production challenges before production trials began. For future new product introductions, Texstars can initiate coordination between R&D and production and implement a product transition process as soon as a launch customer is identified. / by Sean M. Henson. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 65). / A hazard analysis for the test firing of NASA's Space Launch System core stage is performed using a systems-based alternative to the traditional reliability-based method. The method used, Systems-Theoretic Process Analysis (STPA), is shown to be a versatile and powerful tool in this application and by extension the development of future space launch vehicles. The Boeing Company has been selected by NASA as the prime contractor for the Space Launch System (SLS) cryogenic stages. As such, they are working with NASA to develop a comprehensive hazard analysis for core stage test firing and eventual launch operations. Developing, testing, and launching rockets is an inherently complex and high risk endeavor. Preceding the launch itself, one of the highest risk times in the operation of a rocket is the static fire testing, also called a hot fire. Hundreds of parameters need to be monitored in real time in order to ensure the system is operating nominally and equipment damage (and possible injury or death) will not occur. Depending on the point of the testing and the resultant speed at which events are occurring, different levels of automatic safing conditions and operator actions are required to protect the vehicle. Traditionally, the way these safing conditions are derived is through the evaluation of hazard reports, which are themselves based on a "reliability" model: hazards are seen to arise from the failure of individual components and are thus primarily mitigated through increasing component reliability or adding in redundancy. With the level of complexity and required safety of today's launch systems, it is beneficial to evaluate a new approach to identifying the underlying hazards in a system, including ones that arise from unsafe component interactions and not simply failures / by Barret William Schlegelmilch. / M.B.A. / S.M.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 63). / The Vaccines & Diagnostics (V&D) division of Novartis recently developed a global automation strategy that highlights the need to implement a manufacturing execution system (MES). Benefits of an MES (electronic production records) include enhancing the compliance position of the organization, reducing production delays, and improving process flexibility; however, implementing an MES at global manufacturing sites presents unique logistical challenges that need to be overcome. The goal of this thesis is to investigate cold chain management as an expanded functionality for an MES. The thesis attempts to identify best practices for the strategic implementation of an MES in the management of cold chain vaccine products. While the concepts presented in this thesis are in the context of managing the cold chain for vaccine products, the best practices can be applied to a variety of cold chain management scenarios. In order to generate best practice recommendations for the strategic implementation of a cold chain management MES, a thorough understanding of the manufacturing process will need to be acquired. The first tool used to gain this understanding was value-stream mapping (VSM). VSM provided some insight into the current paper-based cold chain management system; however, the tool was not applicable for understanding the flow of information generated within the cold chain management system. Another tool was used to enable the organization to focus on the data generated by a process, the information product map (IP-Map). Current-state IP-Maps of the cold chain at the Rosia, Italy, site were generated and numerous areas for improving the data quality were identified. Future-state IP-Maps of the cold chain at the Rosia, Italy, site were generated to demonstrate how the implementation of a cold chain MES could improve the shortcomings of the current system. The future-state IP-Maps were based on underlying assumptions that directly lead to recommendations for the cold chain MES implementation. First, a unit of measurement smaller than lot size must be selected for tracking material data in the MES. Second, data capture technology for material entering or leaving cold storage must be integrated with the MES. / by Todd Andrew Waldron. / S.M. / M.B.A.

Engine Health Management (EHM) is a comprehensive maintenance service offered by engine manufacturer Pratt & Whitney (PW) to its airline customers. In its current form, engine performance is monitored through recorded physical metrics, such as gas temperature, pressure, and altitude, taken as single snapshots at various phases of flight. The advent of the Enhanced Flight Data Acquisition, Storage and Transmission (eFASTTM) system, which allows for near-continuous recording of engine metrics, provides Full-Flight Data Analytics (FFDA) that may proactively alert and recommend maintenance activity to airlines. Adopting eFASTTM may help avoid Adverse Operational Events (AOE) caused by unexpected engine failures and the associated cost burdens. With respect to operating cost, airlines standardly report Cost Per Available Seat Mile (CASM) and Cost Per Block Hour (CBH). EHM services that prevent operational disruptions can help airlines reduce these unit-cost metrics, whose scrutiny by industry analysts affect investment guidance, stock performance, and overall business outlook. In this study, the value of FFDA services to airlines is investigated on the International Aero Engines V2500, a mature engine with customers' operational histories well-documented. Using a Poisson distribution to model the occurrence of six operational disruption types-Inflight Shutdown, Aircraft-On-Ground, Aborted Takeoff, Air Turn-Back, Ground Turn-Back, and Delay/Cancellation-the cost savings potential is quantified as a function of events avoided by a hypothetical FFDA service. Airline Form 41 financial data from the Bureau of Transportation Statistics is then used to estimate the magnitude of savings on CASM and CBH retroactively for 2012-16. Results show that unit cost reductions of 0.5% to 1.5% are possible through engine event avoidance, representing savings up to $104M annually, but outcomes are highly dependent on assumptions about cost of operational disruptions for each individual carrier. Overall, a baseline model and procedure is developed for valuating FFDA and associated EHM services. Further collaboration between airlines and Pratt & Whitney on data availability and accuracy will help refine this model, which is the first to bridge publicly available airline costs with engine history data, helping stakeholders transition to an eFASTTM ecosystem that promises greater operational efficiency and safety. / by Henry H. T. Luu. / S.M. / M.B.A.

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2019 / Thesis: S.M., Massachusetts Institute of Technology, Operations Research Center, in conjunction with the Leaders for Global Operations Program at MIT, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references. / Company X is facing high cost to serve customers such as hospitals and clinics, due to irregular ordering pattern. Currently, the customer ordering process is not well planned and leads to multiple orders in a month, thereby excessive shipping and increased cost to serve. The supplies provided to customers are used for specimen collection, and the collected specimen are sent to diagnostic laboratories for analysis. Historical data on order quantities of specimen collection items (SCIs) and specimen containers returned to lab are available. This project takes advantage of the closed loop nature of the system to predict order quantities of SCIs. This project explores two replenishment strategies and compares it with the current method, through simulation. / The simulation models the daily consumption of SCIs at a chosen Patient Service Center (PSC), and estimates average inventory levels and the number of occurrences of stockouts for each SCI at the PSC, for varying values of parameters such as review period and safety stock levels. The two replenishment strategies are (a) constant order quantity, in which fixed replenishment quantities of SCIs are supplied every review period, and (b) predictive modelling replenishment strategy, in which the order quantities of SCIs are predicted using the data on specimen containers returned to diagnostic lab for analysis. For the latter strategy, multiple models for prediction, such as penalized regression, Classification and Regression Trees (CART) and Random Forest are used. Two parameters, the total replenishment costs and the number of occurrences of stockouts, are measured to evaluate the performance of the replenishment strategies. / The total cost of replenishment for constant quantity strategy is comparable to that of baseline case, whereas predictive modelling strategies have much higher cost. The constant quantity strategy with increased levels of safety stock gives best results of reducing the total cost of replenishment and minimizing the number of occurrences of stockouts. / by Merin Thomas. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Operations Research Center

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 54-55). / For top wholesale retail companies, the demand for products from US-based customers (wholesale, digital, and direct to consumer) is extremely high. However, the available supply of a product is contingent upon the success of long-term forecasting, manufacturers across the globe, and intercontinental transportation. Therefore, there is not always enough supply to meet demand. In these situations, wholesale retailers must decide which orders to prioritize in the allocation of available supply. This thesis presents a method for improving order prioritization by utilizing readily available data to wholesale retail companies and a method for predicting the effectiveness of the new prioritization methodology utilizing historical data. By prioritizing orders that meet certain characteristics deemed to be in-line with company strategy and simulating multiple conditions, it is possible to deliver improved service on a specific set of orders. The impact of this work has been verified through a simulation model. The model was used to simulate three months of supply and demand and indicated a possible increase of 10-90% in the number of units made available to ship to specific marketplace segments. / by Ashton David Imlay. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 81-82). / To reach its long term revenue targets, EDSCO Fasteners must expand its smooth bar anchor bolt product line to increase revenue generation. In order to maximize profit during this expansion, an operational strategy must be developed to minimize total landed cost. This project will assess the current manufacturing processes and develop a realistic and practical model of the supply chain. Using data collected through pilot project implementation the model's parameters are calibrated and the model accuracy is validated. By developing this model as a linear optimization program it can be used as a decision support tool to inform the operational strategy. Likely expansion scenarios and decision points (consolidation, acquisition, capital expenditures, etc.) are considered as decision variables in the supply chain optimization model to minimize total landed cost. These results are used to inform a recommended scenario based strategy for product line expansion. / by Brian C. Martin. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering