Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 116-117). / Injectable drugs, like those manufactured by the BioPharmOps group of Novartis Pharmaceuticals AG, must conform to strict guidelines for purity and potency. Recent non-conformances of critical supplied consumables have revealed potential business and patient safety risks for biotechnology manufacturers worldwide. As a result, Novartis has launched a program to enhance control systems over all consumables and their suppliers. Within this program, the author has developed a system to identify, analyze, and mitigate the various risks which may impact the business due to non-conformances in supplied consumables. The first function of the system is the identification of key risks and their potential effects according to various failure modes that have been observed during the use of the consumables in production. This is accomplished with a standardized list of possible failure modes which can be applied to all consumables. The categorization allows the relative risk of each failure mode to be compared among consumables. Secondly, the risk of contamination is evaluated using a Failure Modes and Effects Analysis (FMEA) framework. The three dimensions of the FMEA framework are the severity, likelihood, and detectability of a failure. The severity of each failure mode is assessed by analyzing the quantitative and qualitative impact that a failure might have on the purity and potency of the drug. This calculation is based on the properties of each consumable and its use in the production system. The likelihood of failure events is assessed through an analysis of the complexity of the consumable and its supply chain, and a review of the quality systems at the supplier. Detectability analysis considers the tests and inspections in place at various stages including consumable manufacturing, receiving inspection, and in-process tests during drug manufacturing which could detect a non-conformance. The total risk level is evaluated as the product of these three dimensions and a threshold is defined for requiring additional mitigations for these risks. This risk assessment method is implemented in an automated worksheet to ensure consistency among users and efficient analysis. The third outcome of the system is the recommendation of mitigations to reduce total exposure to contamination risk. Mitigations may be internal (new tests and inspections) or implemented at the supplier (improved sampling rates, enhanced general quality systems, or new controls). The recommended mitigations provide guidance for the reduction of risks to an acceptable level, and when implemented, the impact and frequency of non-conformances will be diminished. Ultimately, this reduces Novartis' exposure to potential business loss and protects patients from injury caused by contamination. / by David Linders. / 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 Aeronautics and Astronautics; in conjunction with the Leaders for Global Operations Program at MIT, 2013. / This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from department-submitted PDF version of thesis / Includes bibliographical references (p. 71-73). / This work focuses on the application of a streamlined version of Multi-Attribute Tradespace Exploration (MATE) as a first-order analysis tool to aid in the selection of CubeSat communication systems. As CubeSats have become more capable, their need to support ever-increasing amounts of mission data has become imperative. However, the selection of a communications system is complex endeavor with multiple competing objectives and multiple stakeholders. This already challenging environment is compounded by the fact that CubeSats often operate with minuscule budgets on reduced timelines. So, in order to aid the decision maker while maximizing value, we show that MATE can be applied as a first-order analysis tool. / by Clayton B. Crail. / 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 Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / 14 / Cataloged from PDF version of thesis. / Includes bibliographical references (page 46). / Computer based supply chain simulation, optimization, and visualization capability have changed significantly in the past 45 years, expanding capability in lockstep with increases in computational power. The increase in accessibility of relatively cheap and powerful hardware has led to the development of a multitude of supply chain simulation, optimization, and visualization programs catered towards reducing corporate supply chain costs. Some of these programs are commercial business to business offerings, while a significant set are developed internally within the corporation. Expertise in this field is increasingly seen as an area of competitive advantage for modern goods based corporations. However, the danger lies in executing decisions based upon inaccurate simulation results, often meaning millions of dollars lost in waste rather than the desired savings. This thesis aims to identify the needs of a corporation regarding supply chain simulation, optimization, and visualization - particularly how a company may categorize offerings within this field - how these programs may fit within the organizational context of a company, and how to ensure correct utilization of a set of supply chain programs. Supply chain is very well understood, but little focus has been placed on correctly utilizing these programs to support success for a company's goal of becoming operationally efficient. A current state analysis of a major U.S. manufacturing company, Caterpillar, Inc., was conducted and a new framework was applied to understand Caterpillar's usage of supply chain programs. This thesis utilizes findings from Caterpillar as a sample case to reinforce research. An overall strategy is developed based on research at Caterpillar, and supports the creation of a group of internal experts disassociated from specific supply chain specialties, such as procurement or logistics, in order to ensure global efficiency. A generic strategy is presented for any corporation utilizing computer based supply chain simulation, optimization, and visualization. / by David Chou. / M.B.A. / S.M.

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 Chemical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 75-77). / Some biopharmaceutical companies have responded to evolution of the competitive landscape by placing additional emphasis on reducing their costs of manufacturing as a means of maintaining competitiveness. The prototypical current generation biopharmaceutical drug substance manufacturing facility requires a large upfront capital investment. Improving efficiency of use of existing facilities, such as by improving production throughput through the adoption of technology, represents one way in which a company may reduce its costs of manufacturing and/or avoid or delay investments in additional capacity needed to meet future demand. Reducing the variability in the performance of a liquid filling operation taking place during the protein production step is desirable, because it: (1) enables process optimization, including potential throughput expansion, (2) demonstrates control over the process, and (3) improves step yield reproducibility. The technical and economic bases for the implementation of an alternative process control strategy intended to reduce this variability are presented. This strategy involves controlling the fill operation using an inline concentration measurement of the parameter of interest. An engineering-probabilistic approach, consisting of a transient concentration profile model built into a Monte Carlo framework, is applied to predict the variability of the performance of a concentration-based control strategy for filling an agitated, gassed bioreactor. An optimization methodology for selecting an appropriate post-fill target concentration and for quantifying the economic benefit of reducing variability is proposed. / by Matthew P. Dumouchel. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 56-57). / A new airplane model is quickly ramping up in production rates, and in order to achieve the organizational targets and commitments, Flow Days, Unit Hours and Cycle Times must be reduced throughout the entire supply chain. The Continuous Improvement Group (CIG) is an initiative supporting these improvements by applying the Theory of Constraints to identify improvement opportunities and lead teams to implement solutions and make the improvements. This thesis details the approach of using historical manufacturing data to identify focus areas for analysis and a methodology for analyzing a specific manufacturing process. This analysis and the improvement opportunities identified for several processes in the Final Assembly of the new plane are discussed, as well as the efforts implement solutions to these opportunities. Finally, this thesis also describes the mindsets and organizational characteristics that are necessary in order to make large efficiency improvements in a complex manufacturing process. / by Erik L. Charpentier. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 69-71). / Infrastructure has to weather the elements and still function. Gas transmission and distribution piping at a utility are no exception. Atmospheric corrosion deteriorates the integrity of the natural gas system, and utilities need to respond with countermeasures in order to mitigate the risk. The ability to predict where atmospheric corrosion will cause leaks will allow for a better allocation of resources in mitigating the risk caused by corrosion. First a corrosion simulation model was developed to predict the number of leaks in each geographic area in PG&E's service area. Past meteorological data, past pollution data, 2014 atmospheric corrosion inspections on 2.27 million meters, leak data, and gas system asset information (meter age, type, etc.) were used. The qualitative observations and a quantitative model were then coupled in a simulation model to predict the number of leaks depending on the years between atmospheric corrosion inspections. Utilizing the output of the corrosion prediction model, an optimization model was developed to determine the atmospheric corrosion inspection frequency that will minimize the risk of leaks to the system. This model will allow PG&E to understand how reallocating inspection resources can reduce risk of leaks. The overall results indicate that data quality plays a very important role in coupling qualitative observations with a quantitative model. From the model developed and analyzed in this thesis, several opportunities for better data collection were identified. By collecting targeted data on localized corrosion and corrosion rates, qualitative inspections can contribute greatly to accurately model corrosion where quantitative models are lacking. / by Richard A. Mullen. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 69). / Inventory is the largest asset on Nike's balance sheet-$3.9 Billion on May 3 1 st, 2014-and a key indicator of supply chain health. With new markets, products, and channels being added to Nike's sales portfolio each year, the environment in which Nike's supply chain must operate is becoming increasingly complex. Nike has responded to this complexity by splintering their supply chain into smaller segments, tailoring each segment to specific market and consumer needs. As a result of these market developments and Nike's organizational response, the task of understanding and predicting inventory movements has become increasingly challenging for Nike's business planning teams. This project creates an analytical method by which Nike can combine historical supply chain performance with sales forecasts to accurately predict future changes to company inventory levels. To achieve this goal and facilitate simple and flexible inventory predictions, a model was developed around the key segmentation dimensions that define Nike's supply chain. Use of this model enables Nike's senior management team to accurately predict movements in inventory due to product mix changes in the baseline sales forecasts. Additionally, the model provides Nike with a mechanism to evaluate sensitivity to forecast errors and the inventory costs associated with key strategic decisions to grow or shrink segments of their business. Preliminary results from the model over the time period FY15 - FY18 show a 2% increase in baseline inventory by the end of FY18 due both to growth in Apparel relative to Footwear and to growth in Direct-to-Consumer relative to Wholesale. This upward pressure on inventory leaves Nike in a precarious spot with Wall Street analysts who associate inventory growth relative to sales with poor marketplace performance. By carefully segmenting inventory, applying segment specific forecasts, and analyzing aggregated results through the use of the model, Nike can more accurately predict and explain movements in inventory to shareholders. / by Ryan Jacobs. / 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 (pages 87-89). / This study aims to advance understanding of baked-in siliconization of cartridges for application in Insulin injection pens. This research is motivated by lack of knowledge of baked-in siliconization and business opportunities a better understanding can provide. The primary contribution from this work is the development of a recommended silicone profile that can significantly reduce friction force variation within a cartridge during device use. An Insulin pen delivers Insulin to patients by the mechanical pushing of a rubber stopper through a cylindrical glass cartridge forcing the Insulin through a hypodermic needle at the cap end. This cartridge is coated with a very thin layer of silicone to reduce the force necessary for injection. This silicone layer is introduced to the cartridge prior to filling in the manufacturing process. This step of the filling process was characterized and results revealed different silicone profiles and friction force profiles for different filling lines. Correlations between silicone profile and friction forces were then developed for cartridges. As predicated, lower levels of silicone thickness and a higher percent of dry spots led to increased friction forces and higher variation among samples. These correlations were used to recommend a silicone profile with an average layer thickness greater than 60nm with fewer than 20% dry spots. Finally, atmospheric pressure plasma (APP) treatment was explored as a pre-treatment step to improve siliconization. Findings from APP feasibility studies showed that APP increases glass surface energy and wettability, but that its effect wears off over time and therefore impact on siliconization is still unknown. These results set the stage for further research and process optimization of siliconization in the context of medical injection devices. Insights gained will contribute to design of new devices, improved manufacturing operations and increased quality for Sanofi and the pharmaceutical medical device industry. The opinions expressed herein are solely those of the author and do not necessarily reflect those of Sanofi. / by Scott D. McArthur. / 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 49). / As Amazon continues to experience a rapid growth in its e-commerce business, fulfillment efficiency needs to through safe implementation of advanced technology to create a better customer experience. Amazon has heavily invested in automating its outbound product sortation process that merges picked items but has yet to develop automation for multi-item packing. Individual item manipulation has been proven very challenging to automate due to the over 500 million unique products offered. This thesis proposes a container manipulation solution that integrates industrial robotics and other equipment with upstream sortation technology to automate the packing process. A physical prototype was built to test the concept and measure proficiency in critical quality metrics such as item accuracy, product damage, and packing density/orientation. Additionally, an operational simulation for the system was developed to determine the optimal capacity sizing for the integrated sortation and packing system. Lastly, sensitivity analysis on a financial model was performed to optimize for the net present value (NPV) and payback period. After a series of controlled experiments and process improvements, the prototype produced promising results, given the rudimentary nature of the prototype. The system generated item accuracy defects at 2%, product damage defects at 2% and packing orientation defects at 17%. While these results are not adequate to be used in live operation, a development path to acceptable performance appears attainable. Furthermore, implementation of the technology would generate approximately and $100M in NPV across the global fulfillment network. / by Andrew Walker. / 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. 99-104). / Application of system optimization theory, supply chain principles, and capacity modeling are increasingly valuable tools for use in pharmaceutical manufacturing facilities. The dynamics of the pharmaceutical industry - market exclusivity, high margins, product integrity and contamination constraints - coupled with increasing cost pressures, demand for specialized products increase, and growing industry complexity makes analytical business decisions necessary to sustain competitive advantage. The united application of capacity modeling, system optimization, and supply chain analysis tools, paired with implementation strategies on a multi-product vaccine production system are detailed to address important business difficulties. / by Kacey L. Fetcho-Phillips. / S.M. / M.B.A.