Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2018, In conjunction with the Leaders for Global Operations Program at MIT / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (page 63). / A key value stream for Company X is a manufacturing area dedicated to production of precision electro-mechanical systems, of which they are contracted to service during the complete lifecycle. Currently, the production system is dedicated to the refurbishment of these electro-mechanical systems; it could be characterized as a high-mix low volume production system with a-job-shop layout. The operations team is being pressured to increase both production volumes and the product mix, while maintaining a competitive cost structure in a highly constrained environment, in terms of both space and resources. This thesis proposes two distinct projects to address the challenges faced. First, develop a framework to analyze the value stream, utilizing a discrete event simulation (DES) tool to characterize the production system. / The method will validate the DES tool against the current state production system and key performance indicators (KPI's) then conduct what-if analyses and studies based upon anticipated contractual obligations. This effort will identify risks within the value stream related to the transition from current state to future state, while studying the impact of changes in shipment volumes, product mix, direct labor, and capital equipment. This model supported conclusions and recommendations drawn, based upon the results of the DES, to build confidence in the production system and enable the value stream to meet the requirements of the increased volumes and complexity through making informed operational decisions. Second, to improve a key subassembly within the value stream identified as problematic with respect to labor content, cycle time, and ergonomics. A project has been identified to develop a new process to join two components with a tightly controlled radial bond. / Currently, the components are bonded, and the bond material must cure for several days. Upon curing, the joint contains excess bond material that must be removed for several reasons. The excess material is removed through a manual cutting process that is physically taxing on operators. After cutting, a cleanup process is initiated where an operator fills the void left from cutting with additional material; this additional bond material needs several additional days to cure. The new process utilizes an inflatable vessel that will apply pressure during the bond process to direct excess material away from the joint, eliminating the need for secondary processing in the joint, favorably impacting labor content, cycle time, and the ergonomics of operators. To speed validation and adoption, this project leveraged the 3D printing capabilities of the manufacturer. / Both the testing fixture and test articles were 3D printed in order to accelerate development and reduce risk associated with investment in the development process. Testing of the new process has indicated that the new method produces bonds of acceptable quality with markedly reduced labor content, resulting in a projected annual savings of $950k. / by Clinton Lee Proctor. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical 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 Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 73-76). / Massachusetts General Hospital (MGH) manages a large inventory of surgical equipment which must be delivered to operating rooms on-time, efficiently, and according to a set of quality standards. In recent years, flexible scope management has become a topic of interest for many hospitals, as they face pressure to both reduce costs and prevent infections that can result from mismanagement. This thesis proposes a novel method for surgical equipment management in a hospital. The proposed solution uses a real-time locating system to track flexible scopes, a semantic reasoning engine to determine the state of each scope, and a dashboard to inform staff about necessary interventions to avoid scope expirations while maximizing efficiency. This project aims to accomplish three primary goals. First, the project seeks to improve the hospital's compliance to quality standards in order to reduce risks of infection due to expired scopes. Second, the project aims to improve the cost-efficiency of scope disinfecting processes through more efficient inventory management. Finally, the project serves as an opportunity for the hospital to establish best practices for working with the newly installed real-time locating system. The system proposed in this work is piloted at MGH on a subset of the hospital's flexible scopes. The pilot results demonstrated a quality compliance increase from 88.9% to 94.5%. The implementation also resulted in an estimated $17,350 annual cost savings due to more efficient management of scopes. / by Jason Troutner. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical 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 Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 93-94). / Effective risk management is critical when manufacturing medical products to avoid any potential impact to patients due to supply disruptions or quality excursions. As Flex LTD, an end-to-end manufacturing solutions provider, continues to grow its medical device portfolio, they have a need to take a more proactive and systematic approach to managing project risks. This research applies several project risk management frameworks and interventions to one of Flex's medical device programs as a pilot study. First the current state of existing risk management practices is evaluated. The frameworks and interventions are then implemented over a period of 6 months and their effectiveness analyzed at the end of the study. The results found that the interventions and frameworks applied during the pilot study improved overall understanding of fundamental risk management concepts. / It also showed that key activities, such as training workshops and the intervention of a risk management "champion" impacted risk tracking activities and were effective for overcoming adoption barriers. In applying the Risk Driver framework to the data generated during the pilot study, it was determined that identifying commonalities and trends across risk drivers can be used to proactively inform risk management decision-making and establish new metrics. These results also show that useful insights can be derived from risk drivers without knowing the outcome of the risk event. The study concludes that while risk management has both cultural and structural components, changes to the structural aspects (tools and processes) enable cultural change. Additionally, it concludes that frameworks can be used facilitate proactive risk management if they are integrated into a robust overarching risk management process. / Recommendations for future work include improving training programs to educate team members about project risk management, as well as the development of simple frameworks that are integrated into the overall risk management process to enable more proactive risk management. Certain risk management interventions such as trainings and having an assigned "Champion" for risk management are effective in the near term, but further study is needed to evaluate their impact on long-term sustainability. / by Emily Templin Kehne. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical 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 Aeronautics and Astronautics, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 100-107). / On average, an airline starts to place orders or aircraft within 3 - 10 years before the expected delivery date. During this time, there could be changes given the natural response of the airlines to continuously refine their fleet plan. This behavior implies many possible scenarios that aircraft manufacturers would like to understand and predict in order to improve their backlog management initiatives. Furthermore, demand estimation is always a powerful lever in any production system because it allows the manufacturer to be prepared to address the customer's needs. An airline's network and fleet are dependent on each other. The network is highly dependent on the capabilities of the available fleet but also, the fleet is built considering the network strategy of an airline. Giving this relationship this project aims to develop a set of predictive models based on network-related variables that allow to forecast the RPK growth of an airline in the following 7 years. Most of the available forecast for air passenger traffic focus on economic variables such as fuel price, GDP of the countries, trade index and population among others. This project wanted to explore if network variables had any relationship with future RPKs for an airline. After the analysis of historical data of more than 400 carriers from 2010 to 2017, the results show that although mild, there is an influence of these variables and we could use the resulting forecast with a solid reliability. Furthermore, the final coefficients show more influence of these variables for short-haul (less than 2500 nautical miles) and Economy markets than long-haul and Business markets. For Boeing and its current backlog size of more than 5,800 aircraft [1], the resulting models represent another tool that will aid the company in making data driven decisions regarding aircraft production, new orders to come, evaluation of current and potential customers, and other business analysis. / by Norányeli Paola Molina Realpe. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics

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 Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (page 67). / As AstraZeneca's product portfolio becomes increasingly complex, its supply chains must evolve in parallel. These supply chains operate in an environment of ever-present external risks such as factory fires, geopolitical disruptions and natural disasters. Such risks might manifest as disruptions which could jeopardize the health of those who depend upon AstraZeneca's life-saving medicines. Accordingly, there is a need to improve proactive planning and reactive risk decisions to maintain service levels in such an environment. This thesis presents an approach which enhances both risk planning decisions and reaction to disruptive events. The approach consists of a third party software solution to provide better supply chain visibility, increased risk awareness, and faster disruptive event notification, as well as a stochastic nonlinear optimization model to support inventory reductions. Both approaches improve risk planning decisions, while the software approach also supports reactive decision-making as disruptive events unfold. For a single brand, this thesis model shows that current risk mitigation inventory sizes across its supply chain can be reduced by over 50% while maintaining the target service level. The cost savings estimated for a reduction of this magnitude are at least $20M for one brand alone. Simultaneously, the software uncovers previously unknown sub-tier suppliers and highlights tier one dependencies. Adoption of this thesis' recommendations can improve risk planning and decisionmaking within AstraZeneca's supply chains while greatly reducing mitigation inventory costs. / by Kenneth E. Hampshire. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering

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 Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 140-151). / Oral delivery of large molecules is widely considered the "holy grail" of drug delivery, but attempts to achieve this within the past century have been met with a lack of success, confounded by low bioavailability. Novel mechanisms need to be assessed in order to deliver a clinically relevant amount of drug into systemic circulation, while protecting the drug from pH denaturation and the harsh enzymatic environment of the gut. To assess the field, this thesis evaluates startup companies and academic labs focusing their efforts on the oral delivery of biologics. The holistic, phased analysis of the field includes the following items: ** Value proposition assessment as applicable to Amgen's pipeline; ** Literature review into historical barriers; ** Technology landscape of the current space; ** Down-selection to highly valued technology prospects; ** Risk assessment and mitigation planning activities. / The approach outlined above led to the identification of two promising technologies (Tech A and Tech B) that use novel methods to deliver drug through the lining of the small intestine into systemic circulation. Both early stage technologies hold a significant amount of promise for Amgen if they enable both systemic and localized GI delivery successfully, but have multiple risks to address prior to use as a platform delivery option. Risks that have been prioritized for evaluation include: health concerns over long term damage and infection, low bioavailability, limited payload capabilities, and large final device size. In Silico modeling in COMSOL Multiphysics of the mechanism of action of Technology A and the resultant spread of drug product into the lining of the small intestine was completed as a preliminary test of the risk of low bioavailability. / Results from this model indicate that Technology A can be optimized via nozzle diameter and ejection threshold pressure to deliver liquid drug product into the desired locations within the small intestinal wall for optimal drug uptake into systemic circulation. If these technologies prove to be successful, the resultant product offering could prove highly disruptive in the industry and allow Amgen to revolutionize the manner in which patients interact with their medications. / by Kaitlyn Nealon. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical 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 Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 59-60). / Verizon distributes Customer Premises Equipment (CPE) such as set top boxes, broadband routers, and WiFi extenders to Fios customers via a variety of paths; for example: direct ship to customer (either for self-install or for later installation by a field technician), delivery via field technicians, or retail store pickup (primarily for self-install). Each method has its own benefits and shortcomings due to impacts on metrics such as inventory levels, shipping costs, on-time delivery, and system complexity. Although the majority of shipments are successfully activated in the customer's home, a non-trivial percentage results in unused returns or inventory shrinkage. These undesirable results represent a significant amount of wasted resources. This thesis is focused on identifying and realizing cost savings in the Fios supply chain through reduction in waste associated with unsuccessful shipments. / In order to effectively analyze the closed-loop supply chain, accurate and reliable process mapping is critical. Interviews with key stakeholders, together with order and shipment data analysis yielded a complete picture of the ecosystem's processes and infrastructure. Process mining techniques augmented this understanding, using event log data to identify and map equipment and information flows across the supply chain. All together this analysis is used to identify order cancellations as a key source of waste. To limit waste, it is necessary to conduct analysis both internal to Verizon's processes and externally, to determine if there are customer trends leading to order termination. Process mining was used for the internal analysis and, while it helped identify singular cases in which process abnormalities were associated with undesirable outcomes, its current form proved unsuited for root cause analysis. / Internal analysis did, however, illuminate opportunities for improvement in radio-frequency identification (RFID) usage and protocols across the supply chain. Current systems can result in poor visibility of equipment as it moves within some segments of the supply chain. The actual monetary impact is difficult to determine but likely to increase as the importance of RFID increases. External analysis is conducted through predictive modelling. Using a variety of data sources, a model with over 80% sensitivity and a low false positive rate is achieved. Operationalizing this model through real time incorporation with sales was explored but found to be overly complex. Instead, the random forest model yielded policy changes guided by the features with the highest importance. A pilot is currently in development to test the efficacy of suggested changes, as the model implies significant savings opportunity. / by Hans P. Kobor. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical 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 Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 59-60). / Increasing competition in the defense industry risks contract margin degradation and increases the need for new avenues to margin expansion. One such area of opportunity is take-away bids for under-performing competitor sole source contracts. Post financial crisis, the government has been more willing to entertain conversation with outside firms about existing contracts in the execution phase if the contracted firm is under performing budgetary and schedule terms. The contracted firm has the opportunity to defend its performance though, so in order to maximize the likelihood of successful take-away, the bid would ideally be submitted when the contracted firm is distracted and cannot put together as strong of a defense as would be typical. Corporate restructuring is an example of such a time; employees are distracted and leadership, communication, and approval chains are disrupted. Because the government contracting process is long and detailed, often taking on the order of one year, if restructuring at competitor firms could be predicted up to a year in advance, resources could be shifted ahead of time to align bid submittal with the public restructuring announcement and therefore increase the likelihood of take-away success. The subject of this thesis is the development of the necessary dataset and application of various machine learning methods to predict future restructuring. Literature review emphasizes understanding of current methods benefits and shortcomings in relation to forecasting, and proposed methods seeks to fill in gaps. Depending on the competitor, the resulting models predict future restructuring on blind historical test set data with an accuracy of 80-90%. While blind historical test set data are not necessarily indicative of future data, one of the firm's under assessment recently announced a future restructuring in the same quarter that the model predicted. / by Matt Casavant. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical 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 Aeronautics and Astronautics, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 65-67). / Ascent Aerospace is a global tooling and factory automation supplier for the Aerospace industry. Ascent's customers are typically introducing automation for the first time, or have already introduced automation to their production systems and are wary of its challenges. Choosing the appropriate technology is essential in ensuring successful implementation for both Ascent's customers and Ascent itself. Ascent has two different business units that produce equipment to automate the drilling and fastening of aerospace structures. These two units each come with vast product portfolios, and distinct approaches to address customer needs. This thesis focuses on an efficient method of evaluating how Ascent's current products align with customer's requirements, as well as identifying any technology gaps needing further exploration. / This thesis argues that Ascent's multiple business units are not currently equipped to advise their customers on investing in the appropriate technology for their production systems. To investigate such a vast solution space, a framework developed by the Systems Engineering Advancement Research Initiative (SEARI) at the Massachusetts Institute of Technology (MIT) is utilized called Multi-Attribute Tradespace Exploration (MATE). Using this framework, a software package called the Product Selection Tool, was developed to analyze how Ascent's product portfolio satisfies the customer's requirements for specific applications. The Product Selection Tool visualizes Ascent's 71 different product offerings on a single graph of utility versus cost per fastener. / The interface that displays the graph is dynamic, allowing Ascent's customers to adjust their requirements and preferences in real time, and visualize the sensitivity, or risk, of the recommended solution based on their specific requirements. This new approach allows Ascent to closely work with their customer in selecting a solution, identify areas of concern early on in the product selection process, and introduce cost-effective technology. This model can be applied to a variety of applications that have a vast solution space, reducing the complexity of understanding and communicating one's product line and/or capabilities. / by Zachary David Talus. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: S.M., Massachusetts Institute of Technology, Department of Chemical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from student-submitted PDF version of thesis. "June 2019." / Includes bibliographical references (pages 87-89). / Flexible, modular, continuous manufacturing small-scale plants (MCSPs) for small-molecule drugs have been recognized as potential safe and economical solutions for pharmaceutical manufacturing. However, among the variety of equipment technologies required for an MCSP platform, there are only a few technologies that have publicly available methodologies for equipment selection. In this study, a new method and tool for computer-assisted equipment selection was developed, which use key engineering correlations and design criteria to match off-the-shelf equipment with the synthesis processes of interest. Furthermore, the tool allows simultaneous equipment selection for multiple synthesis processes to allow the identification of the most flexible MCSP assets. The long-term goal of this tool is to encompass the entire span of technologies that could be used in an MCSP skid and to serve as a communal storage location for vendor-available equipment information to facilitate collaboration and design of a mainstream continuous manufacturing (CM) system. This methodology was applied to equipment selection for the continuous manufacturing of an actual Amgen small-molecule drug substance (API) as a case study. The results from this study showed that the new tool can improve the speed at which equipment is selected and can aid the process developer in decision-making for choosing the most suitable CM asset. / by Kevin Peng. / S.M. / M.B.A. / S.M. Massachusetts Institute of Technology, Department of Chemical Engineering / M.B.A. Massachusetts Institute of Technology, Sloan School of Management