Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 83-84). / As multinational industrial goods companies (MNCs) selling low-volume high-complexity products move into markets across the globe, they develop an operations strategy to provide a product tailored to local markets, often also engineered and manufactured in that local market. As MNCs seek to provide more customization to their customers, they face issues with the resulting complexity of operations, leading them to pursue mass customization, i.e. providing variety at low cost through configurable products. An important step in this product strategy is the introduction of product configurators, i.e. software tools that permit the automatic or semiautomatic configuration and pricing of product variants. Through streamlining the specification and bidding process, product configurators lower process time and therefore also lower costs in both sales and engineering functions. However, difficulties arise in developing a product configurator for a global company operating in many different localized markets. This study develops a framework for multinational companies to first evaluate the needs of their overseas divisions for a product configurator and second identify the gaps between the global and local product configuration and pricing. The objective of the framework is to provide a unified, centrally managed product configurator that provides the ability to tailor product options to specific local needs. A case study of a power electronics multinational with 9 overseas locations is performed. Interviews of key stakeholders in the head office and in the overseas division provide preliminary indication of differing product configurator design requirements from country to country. A deep dive is performed using the framework into two of its oversea divisions, Canada and Brazil. The study reveals key differences in the product feature requirements, in costing products due to local labor costs, part costs and import taxes, in the pricing process due to margin structures and sales incentives and in usage patterns due to language, local technical terminology and collaboration modes between sales and engineering. Using survey techniques, prioritization of the configurator functionality requirements is determined. Combined with an organizational analysis of the company, an integrated implementation plan is developed to permit identification of solutions in conjunction with roll-out to the international organization. / by Alicia Lenis. / S.M. / M.B.A.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / 32 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 101-103). / There are several models for change available to modern organizations based on decades of research. This research tends to focus on broad changes, such as enterprise transformations. This thesis presents a model developed for changes of smaller scope. These smaller changes are typically localized to a specific process or department. The Tactical Change Model is derived from existing change management literature to address these localized change efforts. The phases of the model include: Name a Goal, Investigate the Current State, Develop and "Sell" a Future State, Plan to Get From Here to There, Enact the Plan, and Spread the Knowledge. A final phase, Reflection, is used throughout the change effort. This thesis presents two cases of change at the Aerospace Systems division of United Technologies Corporation. The first case is a change in how escalation in supply costs, or headwind, is forecasted. The goal in this case is a quick, top-down method for forecasting headwind to replace a time-intensive, bottom-up method. The second case is a change in the evaluation method of obsolescence risk mitigation options. This effort is intended to improve the evaluation of these options to develop a more holistic perspective. The Tactical Change Model is used in both of these cases and evaluated using a Three Lens Analysis. The analysis generates improvements to the Tactical Change Model, including explicitly accounting for the Three Lenses throughout the model; removing the Name a Goal phase; emphasizing frequency and structure in the Reflection phase; and allowing for feedback loops. / by Robert J. Harris, Jr. / M.B.A. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 101-107). / This thesis provides a new framework for understanding how conditions, people, and environments of the Intensive Care Unit (ICU) effect the likelihood the preventable harm will happen to a patient in the ICU. Two years of electronic medical records from seven adult ICUs totalling 77 beds at Beth Israel Deaconess Medical Center (BIDMC) were analysed. Our approach is based on several new ideas. First, instead of measuring safety through frequency measurement of a few relatively rare harms, we leverage electronic databases in the hospital to measure Total Burden of Harm, which is an aggregated measure of a broad range of harms. We believe that this measure better reflects the true level of harm occurring in Intensive Care Units and also provides hope for more statistical power to understand underlying contributors to harm. Second, instead of analysing root causes of specific harms or risk factors of individual patients, we focus on what we call Risk Drivers, which are conditions of the ICU system, people (staff, patients, families) and environments that affect the likelihood of harms to occur, and potentially their outcomes. The underlying premise is that there is a relatively small number of risk drivers which are common to many harms. Moreover, our hope is that the analysis will lead to system level interventions that are not necessarily aiming at a specific harm, but change the quality and safety of the system. Third, using two years of data that includes measurements of harms and drivers values of each shift and each of seven ICUs at BIDMC, we develop an innovative statistical approach that identifies important drivers and High and Low Risky States. Risky States are defined through specific combinations of values of Risk Drivers. They define environmental characteristics of ICUs and shifts that are correlated with higher or lower risk level of harms. To develop a measurable set of Risk Drivers, a survey of current ICU quality metrics was conducted and augmented with the clinical experience of senior critical care providers at BIDMC. A robust machine learning algorithm with a series of validation techniques was developed to determine the importance of and interactions between multiple quality metrics. We believe that the method is adaptable to different hospital environments. Sixteen statistically significant Risky States (p < .02) where identified at BIDMC. The harm rates in the Risky States range over a factor of 10, with high risk states comprising more that 13.9% of the total operational time in the ICU, and low risk states comprise 38% of total operating shifts. The new methodology and validation technique was developed with the goal of providing a basic tools which are adaptable to different hospitals. The algorithm described within serves as the foundation for software under development by Aptima Human Engineering and the VA Hospital network with the goal of validation and implementation in over 150 hospitals. In the second part of this thesis, a new heuristic is developed to facilitate the optimal design of stochastic manufacturing systems. The heuristic converges to optimal, or near optimal results in all test cases in a reasonable length of time. The heuristic allows production system designers to better understand the balance between operating costs, inventory costs, and reliability. / by J Adam Traina. / S.M. / M.B.A.

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 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 student-submitted PDF version of thesis. / Includes bibliographical references (pages 93-94). / An understanding of capacity utilization within any manufacturing system is critical in setting operational strategy. Production lines and machines must have their performance accurately tracked and available for reporting if a business is to continually improve their performance. With capacity utilization and manufacturing performance known, a business can provide short-term corrections and also adapt its manufacturing capabilities to meet long-term market requirements. Boston Scientific is a manufacturer of medical devices and is known for its ability to scale up new technologies through the use of an applied Lean Manufacturing framework in its final product assembly. The company also internally houses several component manufacturing groups that supply its assembly operations. While the company has a defined strategy for its assembly operations, strategy for its internal components suppliers is less clear. This thesis discusses building the foundation to transform the Spencer Components manufacturing group into a world class plastics operation. In particular, the ability to utilize manufacturing data to inform short and long term decisions is a critical foundation for any organization in its quest to become World Class. This thesis studies how Spencer Components, a Boston Scientific internal component manufacturer, utilizes newly acquired manufacturing data to improve its operations and begin its transformation into a world class high-mix low-volume plastic components manufacturer. Prior to this research internship, no electronic performance data systems were in use, and Boston Scientific was blind to the operational performance of Spencer Components. While the technology of the new data system is several decades old, a considerable amount of effort was required to successfully implement it within the well-established manufacturing system. Upon implementation equipment utilization improved and inventory targets that previously appeared unattainable were achieved. In addition, a continuous improvement environment was created and allowed Lean Manufacturing techniques such as Single Minute Exchange of Die (SMED) and operational improvements such as Economic Order Quantities (EOQ) to be implemented, tracked, and iteratively improved. A new capacity planning tool was created to identify long-term capital requirements associated with component demand. While Spencer Components is not yet a World Class manufacturer, it now has the tools to achieve its goal of becoming one. / by Stephen Edward Laskowski. / S.M. / M.B.A.

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 (page 141). / Data analytics and visualization are topics of significant interest in the business and manufacturing communities. This research investigates the hypothesis that, if production floor managers consume properly analyzed data, then their ability to solve problems and prevent production system disruptions improves. This research tests this hypothesis through simulation and a pilot program on Boeing's closet fabrication line and identifies the types of data managers require to improve their operations. The closet fabrication line struggles to complete orders on time, and this problem serves as the central focus for this research. A root cause analysis indicates that issues delivering parts to the closet fabrication line contribute to this problem. Given this issue, this research applies data analysis and visualization tools to facilitate the process improvements required to solve the parts delivery problem. This analysis supports the validity of the initial hypothesis. The results of the discrete event simulation predict an 11% decrease in the time required to fabricate a closet and a 50% decrease in the number of days late the production line delivers closets. The pilot program yields an 11% reduction in build duration and a 32.5% decrease in the duration of the average late completion, while increasing the percentage of complete kits delivered from 39.4% to 80.0%. While the pilot program encompasses a small data set of ten closets, it provides an initial validation of the hypothesis. These results also indicate that information regarding warehouse inventory status, the production queue, and the priority of orders in the queue are valuable data that managers require to improve manufacturing performance. / by David Engel Amiot. / 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 Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 81). / Traditional brick and mortar retailers are being forced to adapt as consumer preferences shift towards online shopping. In response, many retailers are developing infrastructure and processes to handle the increased service levels (faster cycle time) that accompanies this digital volume. One challenge that arises during this transition is how to implement the new processes in existing, capital intensive, warehouses. This thesis presents methods for improving service performance by reducing wave cycle time in a large, multi-channel distribution center. By prioritizing digital consumers' orders, lower priority waves are consistently disrupted, which leads to extended wave cycle times and potentially delayed orders to wholesale customers. By analyzing historical data from distribution center operations, it is possible to test hypotheses and develop strategies for reducing cycle time. These hypotheses can then inform experiments to test the effects of operational changes. The impact of this work has been verified in two phases. In the first phase, improving transparency of lagging orders reduced average cycle time by 45%. In the second phase, the wave strategy for high priority orders was modified and resulted in an additional significant time savings and led to an increase in service performance, defined as shipped on time. / by Matthew Reno Wallach. / 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 Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Some pages printed landscape. Cataloged from PDF version of thesis. / Includes bibliographical references (pages 82-84). / The application of silicone inside of glass insulin cartridges helps reduce injection forces during drug delivery. This is important for a less painful patient experience. Insulin pen designs are increasingly reliant on consistent and repeatable injection forces as mechanized injection replaces manual injection. A minimum silicone layer thickness of 40nm is required to produce low gliding forces of approximately two Newtons with little variability. Differences seen in final gliding forces across production areas at Sanofi Insulin Frankfurt are small, but this variation makes it difficult to design for set-force mechanical injection. While the minimum silicone layer thickness required is established, how to achieve it consistently is less understood. This project looked at three insulin packaging lines at Sanofi Insulin Frankfurt that use different methods for siliconization. Differences between these lines were investigated in order to understand which parameters are the most important for creating an acceptable silicone layer thickness. First, each production line was mapped from loading of empty cartridges through the end of the heating tunnel, before insulin is packaged. Differences in the process were found in cleaning procedures, silicone application methods, and production settings. Points for potential variability were found at silicone mixing steps and during start/stop conditions. Lab experiments were developed to test cleaning procedures, heating time, standing time, air pressure of silicone blowout, and silicone concentration. Results from these experiments showed that some production processes have a greater effect than others on silicone layer thickness and subsequent gliding forces. Differences in cleaning procedures on each of the lines have little effect on overall silicone layer thickness and gliding forces. Time in the heating tunnel and standing time have a moderate effect. The largest effects were seen from silicone emulsion concentration and air blow out pressures in the flushing method of silicone application. The following recommendations are given to improve performance consistency across production areas: (I) standardize processes across production areas where possible, (2) reduce air pressure in the flushing process, and (3) eliminate process steps that can lead to several of these effects occurring in the same cartridge. / by Alexandra M. Unger. / M.B.A. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, In conjunction with the Leaders for Global Operations Program at MIT, 2018. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management 2018 In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 147-150). / This thesis presents work performed during the course of an internship at An Aerospace Company (AAC) and research performed at Massachusetts Institute of Technology (MIT) Lincoln Laboratory as part of a fellowship. Both efforts entailed the development of architecture tradespace exploration models for space systems. The tradespace exploration model developed at AAC, called the Earth Observation Architecture Isoperformance Model (EO-AIM), uses automation techniques, isoperformance, and constraint programming to rapidly construct potential space-based passive optical EO sensor architecture concepts which meet a given set of customer requirements. Cost estimates are also generated for each sensor concept via integration with stakeholder-trusted cost modeling software allowing for cost to be treated as both an independent variable and consequence when evaluating various architecture solutions. The EO-AIM then uses simple algorithms to identify potential satellite bus options for hosting each sensor architecture in orbit. The total cost of populating an entire constellation based on the sensor architecture is finally estimated using cost estimates for the sensor, satellite bus, and the best launch vehicle option capable of lifting the satellite(s) to orbit. In general, the EO-AIM seeks to bolster's AAC's capabilities for conducting architecture trade space exploration and initial proposal development given advancements in satellite bus, launch vehicle, and sensing technologies. The tradespace exploration model developed at MIT Lincoln Laboratory is a satellite network mixed integer linear program (MILP) which is used for making system architecture decisions and estimating final architecture cost. The satellite network MILP is formulated as both an assignment problem and a network maximum flow problem which must send sensor generated data to a ground user. Results of the MILP vary with the selected objective function and provide insights on the potential benefits of architecture decisions such as sensor disaggregation and the utility of introducing additional communication nodes into existing networks. The satellite network MILP is also capable of verifying network data volume throughput capacity and providing an optimized link schedule for the duration of the simulation. Overall, the satellite network MILP model explores the general problem of optimizing use of limited resources for a given space-based sensor while ensuring mission data needs are met. It is a higher fidelity alternative to the simple satellite bus and launch vehicle compatibility algorithm used in EO-AIM. Both models are shown to improve architecture tradespace exploration of space-based passive-optical EO systems. With a simple demonstration, it is exhibited that using the EO-AIM can increase sensor architecture concepts generated by a factor of ten or more by creating all feasible sensor architecture concepts given user inputs and settings. Furthermore, the use of the satellite network MILP to examine alternative network architecture options for NASA's HyspIRI mission resulted in a system architecture with 20% higher data throughput for marginally less cost. / by Jeffrey Louis Menezes. / S.M. / M.B.A.

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, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 66-67). / This thesis describes how a 55% reduction in error rate and a 92% decrease in cycle-time were achieved in a batch production records process in a biotech manufacturing facility by utilization of value-stream mapping. The project focuses on careful analysis of the current state of a batch production record review process, including an in-depth value stream map, to identify sources of rework and waste in the current process. Analysis of the value stream map led to the recommendation of real-time review of the documentation by Quality Assurance and Manufacturing on the production floor, enabling significant cycle-time and error rate improvements. / by Rebecca Ford. / S.M. / M.B.A.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 88-89). / The Boeing 737 program has recently announced an increase in the production rate from 31.5 airplanes per month to 35 airplanes per month. Throughout the production value stream, opportunities to improve quality and reduce flow time are being thoroughly investigated. This thesis contributes to the investigation by focusing on improving the inspection process through a prototype computer data collection tool and the formation of a corrective action team. / by Bradley C. Geswein. / S.M. / M.B.A.