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 (pages 97-101). / Large Structure Manufacturing (LSM) is in the midst of implementing a new robotic fastening system that has been designed with flexibility as a key feature. This thesis describes work done build a model of the new system in order to estimate the capacity of the system. It then presents several recommendations to increase the throughput of the system. Additionally, lessons learned from this work are presented so they can be applied to future automation projects. / by Matthew John Cragun. / M.B.A. / S.M.

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 121-124). / Heart failure (HF) is a complex chronic condition that can result from any cardiac disorder that impairs the ventricle's ability to fill with or eject blood. The American Heart Association predicts that there will be about 10 million HF patients in the US by 2037, with total hospitalization costs exceeding $70 billion. This represents a considerable burden to hospitals nationwide, including the Massachusetts General Hospital (MGH) -- a leading medical center that has long grappled with patient overcrowding and capacity constraints. This thesis presents an extensive mapping of the HF care pathway at MGH, followed by the results of a detailed retrospective analysis of the general behavior of HF patients admitted to MGH. Here, we notice that the majority of HF admissions originate as self-referrals via the Emergency Department (ED) and take place on weekdays, between the hours of 9am and 6pm. Moreover, we find that about 57% of hospitalized HF patients often have no scheduled follow-up appointments with their providers in the two weeks leading up to their admissions and, similarly, about 43% have no scheduled appointments in the eight weeks post hospital discharge. These represent two critical time periods in the events of acute heart failure decompensation. In an effort to prioritize targeted outpatient care, we propose a predictive model which aims to identify patients at greatest risk of a first hospital admission following encounters with their primary care providers and/or cardiologists in any given year. We perform logit-linear regressions on multiple prior first admissions and use predictors that, among others, include clinical risk factors, socioeconomic features and histories of prior medications. Some of the model's most significant predictors, as identified by the Akaike information criterion (AIC), include patient's age, marital status, ability to speak English, estimated average income, previous administration of loop diuretics, and the total number of medications prescribed or administered. To assess the quality of our predictions, we turn to the receiver operating characteristic (ROC) and its resulting average area under the curve (AUC) of 0.712. As the team continues to focus on developing interventions that offer better care to HF patients, the value of our model lies in its ability to prioritize patient needs for outpatient care and monitoring, and to guide the allocation of limited care resources. / by Mariam A. Al-Meer. / 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. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 89-91). / This thesis presents methods to identify sources of variation in rolled goods manufacturing by defining the critical input process parameters, and the application of statistical process control. Sources of variation are prioritized according to a process control hierarchy, and reduced or eliminated through iterative cycles of rapid experimentation. This work emphasizes the value of team work, breaking down the organizational barriers between departments, knowledge sharing and the importance of a scientific approach to problem solving. FilterCo manufactures and assembles filter media catering to the ultrafiltration market growing at ~12% over the next five years. In a high growth scenario, production yield variability presents on-time delivery complications while below target yields drive significant scrap value. As FilterCo seeks to improve product lead time for its customers, while reducing WIP inventory, it must seek to maximize OEE with respect to product yield, equipment performance and availability. The variation identification, reduction and process control methodologies presented in this thesis are demonstrated to advance the goal of reducing production yield variation. The impact of the work has been verified on three filter media grades and have shown ~40% reduction in production yield variation, and rolled throughput yield improvements of ~30%. These improvements on the three membrane grades alone have resulted in an annualized saving equivalent to 60% of the total 2015 scrapped membrane value. / by Jeremy Brian Rautenbach. / S.M. / M.B.A.

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 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. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 84). / Launch vehicle hardware is traditionally very expensive to design, develop, produce and certify, because it must operate in extreme environments with high reliability. The result is that most hardware for NASA-funded launch vehicles is custom built to execute a specific mission on a single platform. In contrast to other industries (e.g. automotive), very few components are used across product platforms, a strategy known as reuse that has the potential to decrease the cost, schedule and risk of new product introduction. Budget constraints on NASA's next launch vehicle, the Space Launch System (SLS), brought about a desire to realize some of the benefits associated with reuse. However, the reuse strategy as employed has met limited success. This brings about the fundamental question: is there something inherently unique about launch vehicle design that prevents or limits reuse? If not are there strategies that can be implemented to realize the benefits of proactive reuse during launch vehicle design? The Boeing Company, the prime contractor of the SLS cryogenic stages, would like to develop a reuse approach as they begin work on the next phase of the SLS, the Exploration Upper Stage (EUS), to improve project affordability. To develop this approach, a case study of the Core Stage (CS) was performed to identify lessons learned, resulting in the following insights: 1. Capturing the benefits of reuse is enabled by modularity and platforms within single-vehicle architectures rather than across vehicles. The time offset between any two launch vehicles is too great (20-30 year product lifecycles) for reuse across vehicles. Furthermore, manned and unmanned vehicles carry different requirements which must be considered when evaluating the potential for shared assets. 2. Race should be defined as the baseline, rather than as an opportunity. This requires aligning incentives and architecting the organization to enforce reuse from the outset. 3. Plan for forward reuse. Consider future requirements when designing the current vehicle. Reuse will not happen by coincidence; it must be designed into the system. These insights form the basis of a reuse approach for the Exploration Upper Stage (EUS). In combination with some organization and process-based suggestions, a strategy to realize the benefits of reuse has been developed for the EUS and other future launch vehicles. / by Marissa Ann Good. / 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, 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 (pages 81-87). / Computational modelling has completely redefined the experimentation process in many industries, allowing large sets of design concepts to be tested quickly and cheaply very early in the innovation process. Harnessing the power of computational modelling for protein drug formulation has numerous, currently unrealized, benefits. This project aims to be the first step in the development of a high throughput predictive computational model to screen for excipients that would decrease protein aggregation in solution and thus increase its stability and enable clinical effectiveness. Protein drug formulation currently relies heavily on empirical evidence from wet-lab experiments and personal experience. During the biologic drug development process, proteins that target specific disease pathways are identified, developed, isolated, and purified. Scientists then conduct a series of wet-lab experiments to identify the optimal formulation that will allow the protein to be used as a drug therapy. A critical part of formulation development is the identification of inactive ingredients called excipients that perform various important functions including prevention of protein aggregation. Despite their critical role in enabling proteins to be effective therapies, very little is understood about excipient-protein interaction. Furthermore, often a limited set of compounds are tested for their use as excipients since wet-lab experiments are expensive and time consuming. This project accomplishes the following goals: ** Identification of databases of compounds that could be used as excipients in biologic formulation; ** Development of a high throughput method to computationally model a target protein and 247 potential excipients; ** Evaluation of potential relationship between computational output and wet-lab results based onxperimentation with 32 of the 247 excipients; ** Recommendations on next steps that include feedback on types of proteins and excipients to be tested for the validation of the method developed in this project. / by Jayanthi Jayakumar. / 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 Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 70). / Helicopter manufacturers typically build each aircraft to order, and the lead time for make or buy parts and assemblies can be several months or more. The manufacturers generally have a backlog of orders at any given time, so customers in the helicopter market can expect to wait several months for delivery. However, due to the current economic conditions causing softened demand in the industry, some manufacturers have worked through most of their backlog and now have a finished goods inventory that allows for little or no wait for customer delivery, providing these companies a sales advantage. Between this effect of market conditions and recognition of the cost reduction benefits associated with shorter product lead times, successful helicopter companies with continued high demand and backlog, such as Sikorsky Aircraft Corporation, are seeking ways to deliver helicopters in a consistently shorter time frame. In the past, Sikorsky has approached the issue through speculative ordering and parts production prior to customer point of order. This approach has had limited success due to higher than forecasted variability in demand. In order to provide a more optimal means for speculative ordering and parts fabrication, the cause of demand variability was explored and implementation of a parts supermarket of critical, high lead time parts was considered. The solution proposed would be used as a pilot to ensure a consistent, shortened lead time for the main gearbox assembly. This methodology could then be applied to other sections of the helicopter. Analysis of the proposed supermarket reveals that by properly sizing the safety stock of 26 critical parts and using disciplined parts ordering, the objective lead time could be met. The calculated findings indicate large opportunities for cost savings in the implementation of this supermarket by offsetting original and spare parts demand to reduce variability, and by helping suppliers to establish reliable lead times through more consistent ordering patterns at Sikorsky. / by Brendon Bielat. / 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, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 70-71). / Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance for judging customer orders when the market changes. As a result, during the economic downturn of Q3 and Q4 '08, Intel's model could not predict how much billings would decrease. The demand forecast had large amounts of error caused by the bullwhip effect (order amplification in a supply chain). This project creates a new demand forecast model in two phases. The first phase investigated the supply chain of OEMs and Retailers. The second phase of the project used the supply chain information discovered in phase one to create a new demand forecast that reduces the error caused by the bullwhip effect. The first phase determined that the average time it takes a CPU to go from Intel to end customer purchase is seventeen weeks. The first phase also indentified ownership of products throughout the supply chain and parties making purchase decisions. The supply chain information was then used in the second phase of the project to create a demand forecast model. The new model is a heuristic model that simulates quarterly purchase decisions of retailers and OEMs including lead times and inventory. The resulting model allows Intel to monitor and react to consumption changes faster than waiting for customers to change their demand forecasts. The model also provides a better forecast during times of change. The model reduces the error due to the bullwhip effect and indentifies early when a downturn or upturn is going to happen in ordering behavior. / by Emily Smith. / 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. 70-71). / Novartis Vaccines and Diagnostics has made a strong commitment to manufacturing seasonal influenza vaccines through their cell culture technology called Optaflu®. The goal of this project is to improve overall process yield by modifying the upstream process. The focus is on using a batch process to generate a high-density cell culture and then infecting said culture. This thesis presents the approach of using a Design of Experiment series to change a manufacturing process. Current vaccine production occurs with a fed-batch process by feeding glucose as a carbon-energy source for the final cell expansion step. This cell culture is diluted, infected, harvested, and purified for use in an influenza vaccine. Primarily, the project aims to increase cell density, using a batch process, at the infection step which should improve overall process yield. The project can therefore be broken into two main steps: batch cell growth and highdensity infection. Experiments for this project were conducted with a small-scale laboratory process that mimics the production process. The planned approach was a Design of Experiment series to screen parameters and partially optimize the cell growth process, a scale-up cell growth experiment, and finally another Design of Experiment series to explore high-density cell infection. While initial small-scale experiments showed extremely positive results, the results were not consistent and could not be replicated at a larger scale. A number of exploratory experiments were run to attempt to identify which factors inhibit high-density cell growth, particularly around scale-up, but no key parameter was identified. Given the process improvement and cost savings implications from the success of the initial small-scale experiments, this project is worth further exploration. / by Andrew Hill. / 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. 63-65). / With increasing cost pressure on commodity vaccine products, Novartis Vaccines & Diagnostics is continually looking for ways to improve operating efficiencies and decrease costs. As the largest drug product manufacturing site for Novartis flu vaccine products, Rosia Aseptic Operations experiences dramatic swings in required man-hours throughout the year to accommodate the seasonal nature of flu demand. This challenge is further exasperated by long training lead times for new aseptic operators and substantial severance costs for a permanent employee headcount reduction in Italy. With over 50% of the aseptic operators in Rosia on temporary contracts, management spends at least 25 hours per month reviewing headcount in order to make assessments on contract renewals and expirations. Therefore, this thesis investigates the hypothesis that understanding resource needs can decrease labor costs as well as save management time. A labor resource model based on a demand forecast, operational input data, and a scheduling optimization was developed and validated. The outputs of the model support decisions on overall staffing levels by department as well as provide tools to analyze the appropriate mix of temporary and permanent employee contracts and to understand the time lag associated with staffing decisions. Additionally, sensitivity analysis can be performed to see the effect of changes in policies and shift structures. The model reduces costs and saves management time in the Rosia Aseptic Organization through the longer-term depiction of headcount needs, the cost analysis structure and tools, insights from the production scheduling optimization, and the automatic, pre-crafted graphs and tables. Further discussion of the concepts of aggregate production planning, reveals additional opportunities for Novartis to reduce overall production costs through enabling strategies to match capacity with demand. / by Dannielle Sita. / 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, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 53). / Helicopter final assembly involves the installation of hundreds of components into the aircraft and takes thousands of man-hours. Meeting production targets such as total build days and total aircraft man-hours can be difficult when faced with challenges related to parts, workforce, and scheduling. A tool to identify key installations on which to focus efforts for maximum benefit can help improve performance to targets. The Critical Path Method was developed as a project management tool to aid in scheduling large and complex projects. Its application to manufacturing can provide the insights necessary to improve performance in an environment such as helicopter final assembly. This thesis provides a case study of helicopter final assembly. A critical path analysis is performed on the assembly process, using predecessor, duration, and resource data. The results of the analysis are used to draw conclusions about the system as a whole and to make recommendations to improve system performance. / by Sarah L. Daigh. / S.M. / M.B.A.