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, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 57-58). / Novartis Vaccines and Diagnostics operates a centralized equipment cleaning and preparation suite at a vaccine production facility in Marburg, Germany. The ~100 pieces of multi-use stainless steel, glass, and plastic equipment prepared at this centralized pretreatment suite all need to be disassembled, cleaned, reassembled, sterilized, shipped, and tracked. This highly complex cycle is problematic because of the coordination cost, possibility of assembly errors, and lack of operational flexibility. Additionally, the multi-use assemblies were designed as long as 20 years ago, and newer, more reliable alternatives exist. The goal of this project is to evaluate the hypothesis that replacing multi-use assemblies with single-use assemblies will reduce production risk and costs of goods sold of vaccines by reducing operational complexity. To understand the impact of adopting single-use assemblies, the one-time cost of switching (e.g. regulatory filings, validation studies, operational costs) are weighted against the potential for operational savings and risk reduction or transfer to vendors. The current-state variable costs and risks are evaluated with a cost model that accounts for variable equipment cost, operator cost, autoclave cost, and washer costs. Future state variable costs are determined through a request for proposal ("RFP") process with vendors. Novartis Vaccines and Diagnostics had previously conducted failure mode and effect analyses ("FMEA's"), and the critical and potentially critical risks affected by adopting single-use assemblies were reassessed. It is possible to reduce the complexity of pretreatment operations with single-use assemblies. Adopting the four of the assemblies studied in this project would reduce the number of components processed in a year by 40% and the number of unique components by 10%. Many critical or potentially critical risks, such as labeling, assembly, sterilization, transportation, and storage of assemblies will be transferred to third-party vendors. Because these vendors specialize in the production of single-use assemblies, they can invest in more costly capital equipment and processes such as higher class clean rooms and gamma sterilization. Some single-use assemblies will have a lower variable operating cost, while others will increase operating costs. Thus, new assemblies fall into three categories in a decision making framework: 1) Reduced risk and cost, 2) Pay for risk reduction, and 3) Continue with current state. Assemblies in categories 1 and 2 should be modernized from multi-use to single-use, while assemblies in category 3 should remain multi-use. / by Edward J. Alfano. / 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. 74-75). / For many manufacturing and automotive companies, traditional sourcing decisions rely on total landed cost models to determine the cheapest supplier. Total landed cost models calculate the cost to purchase a part plus all logistics costs to transport the part from the supplier to the plant. Although these models can provide a base comparison for suppliers, they do not contain the complete information necessary to make a supplier decision. There are several other factors that must be considered in the sourcing decision process to make a proper decision that considers the risks associated with supplier selection. The primary focus of the thesis is to improve the sourcing decision methodology for choosing between suppliers by identifying and developing models for the key elements in the decision process. A secondary focus of the project is to identify an inventory policy that reduces the supply chain cost of foreign suppliers. Four different aspects of the sourcing decisions process are discussed. The first section is the risk of air freight. Air freight risk is important in the context of the global versus local supplier discussion because it creates a major discrepancy when comparing the potential cost of each supplier. The thesis develops a model that provides an expected cost of air freight to measure air freight risk through the use of historical data. The second aspect discussed is the development of a more comprehensive cash flow model to determine the NPV of cash flows of each supplier that includes the impact of inventory policy and payment terms on net working capital. A more comprehensive model provides the true cash cost, not the accounting cost, of a supplier decision. The model is primarily used to compare local and foreign suppliers. The third part discussed is the impact of foreign exchange rates on the supplier decision and how certain assumptions can impact or alter the supplier decision. A means of testing how the supplier decision is impacted by foreign exchange assumptions and volatility is discussed. Finally, a dual mode sourcing model that ships parts by both air and ocean freight is developed to reduce overall logistics costs for parts procured from foreign suppliers. / by Joseph P. Franken, II. / 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. 46-48). / Company X uses large amounts of electricity in its manufacturing operations. Electricity prices at selected plants in the company's Region 1 territory rose by over 350% between 2000 and 2011, in part due to increasing reliance on high-cost fossil fuels. A focus on reducing these costs has identified numerous energy-saving projects in recent years, but with mixed implementation and performance results between the different plants in the region. Consequently, there is both a need to reduce exposure to high electricity prices and an opportunity to better share best-use practices between plants. This paper has two focuses: identifying and quantifying energy cost-reduction opportunities, and mapping the value-streams for the decision-making and implementation process for energy savings projects. From this Value Stream Map, recommendations are made for a new process that can be standardized and rolled out to other sites in the region. During the first phase of the project, data gathered from utility bills, power meters, and production records are used to identify the best opportunities for energy reduction within the plants. Using this technique, 7 GWh/year of potential energy cost savings are identified via reduced downtime, lighting motion detectors, high-efficiency lighting, and negotiable changes to energy contracts. For the benchmarking phase, the historical record of identified energy projects is compared with the number of projects actually implemented. An observational study of the local LEAN team from one plant is combined with interviews of engineers, managers, and financial analysts to build a process map of both the current and former processes for energy project identification, evaluation, and implementation. The results show a reduction in process steps and a step-change increase in the number of energy projects implemented. A key feature of the new approach is the creation of a dedicated energy team within the existing LEAN program. It is believed that emulating this integration of energy and LEAN at other sites will yield cost reductions as well. To follow up this work, a pilot study modeling this program at another site is recommended before further expansion to the rest of the region. / by Steven J. Stoddard. / 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, 2013. / 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 (p. 83-85). / Process Analytical Technology (PAT) became a well-defined concept within the pharmaceutical industry as a result of a major initiative by the FDA called "Pharmaceutical cGMPs for the 21st Century: A Risk-Based Approach." The FDA defines PAT as "a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes, with the goal of ensuring final product quality." The biotechnology industry has started incorporating PAT in manufacturing, because of regulatory pressure and because the previous blockbuster-oriented business model is becoming less viable. This thesis proposes a methodology for evaluating PAT systems and delivers guidance on how to develop and implement them to effectively manage risk in biopharmaceutical manufacturing. The methodology includes guidance regarding identifying opportunities, evaluating and implementing novel analytical technology, appropriately applying acquired data, and managing change associated with PAT implementation. Experimental results from a novel PAT system that acquires light scattering and UV absorbance data to control chromatography during large-scale manufacturing are presented as a case study. The case study follows the methodology to show how a system optimized for a laboratory can be scaled for use in biopharmaceutical manufacturing. / by Samuel T. Cosby. / 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 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. 72-76). / Abstract We have created a set of decision support tools to streamline the surgical case scheduling process by allowing surgical wait list cases (elective cases that cannot be assigned a slot on the operating room schedule at the time of booking) to be confirmed onto the operating room schedule up to three weeks in advance of the day of surgery. Prior to our research, wait list cases could not be confirmed more than a few days prior to the desired day of surgery due to uncertainty about available time prior to the release of dedicated OR capacity. Earlier confirmation of wait list cases serves three purposes: (1) to improve patients' ability to plan logistics to prepare for their visits, (2) to reduce wait list case backlogs for surgeons' offices, and (3) to reduce variability in the total daily caseload through proactive decision making. Our contributions assist scheduling personnel in confirming wait list case dates sooner to help medical institutions achieve these benefits. We have developed two Excel-based pieces of software: a prediction tool and a schedule optimization tool. The prediction tool predicts time that is available each day between one and three weeks in advance to accommodate wait list cases, and the schedule optimization tool automates the consolidation process for all cases that are currently booked on a future date so that rooms and equipment are used as efficiently as possible. Our platform lets users interact with simple GUIs in which they make selections to generate prediction results and optimized daily case schedules. Specifically, our prediction algorithm employs a multiple linear regression model over historical data to forecast unused time, and the optimization tool uses a mixed integer linear program to optimize the daily schedule by consolidating cases into a minimum number of rooms and closing any gaps between cases, subject to constraints that are specific to the facility and the date in question. We have achieved our desired outcome of maximizing operating room resource utilization by giving human schedulers a set of tools to use on a daily basis that simplifies the scheduling process and confirms wait list cases with more advance notice. This system is generalizable to other areas within healthcare delivery environments and any other industry where tasks are scheduled in advance into a fixed set of resources with a record of historical demand over time. / by Ryan M. Graue. / 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. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 55-56). / In pursuit of Novartis Pharmaceutical's vision to "Make Quality Medicine-On Time, Every Time" Novartis Ringaskiddy Limited (NRL), is pursuing Class A Manufacturing (MRP II) certification. Achieving Class A certification requires production plans be established and met with great accuracy. The Multi Synthesis Production Unit (MSPU) at NRL sets rolling eighteen month production commitments on a semi-annual basis. During planning a rudimentary tool is used to allocate production campaigns for over 40 different Active Pharmaceutical Ingredients (API) and intermediate products across roughly 200 pieces of equipment. This manual tool is time intensive to operate, prone to errors, and requires extensive knowledge of the facility. To address this problem, a simulation based model was developed using the software package, SchedulePro". The aim of this project was to create a system to support more effective and reliable production planning. The approach requires accuracy in modeling, a process to deploy the tool and a connection to people who use and benefit from the process. In order to evaluate the proposed model and understand potential benefits to Novartis, five case studies are used to compare the proposed planning process with traditional methods. First, when planning a future production year the proposed planning process demonstrates a reduction in required time as well as an increase in accuracy. Second, when evaluating the response to a change in demand a user with little knowledge of the plant can attain comparable response time as an experienced user of traditional methods. Third, when faced with an unplanned equipment failure the user is able to explore alternative production plans which minimize disturbance to the established production plan. Fourth, through the evaluation of alternative resource allocation plans the user can determine the lowest cost approach. Finally, when applied to a product launch evaluation the model is shown to reduce the number of planning cycles, focusing specifically on the ability of the site to support a product launch in a previously allocated year. / by Christopher J. Wilson. / 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 Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 51). / Aircraft are complex machines consisting of tens of thousands of parts and assemblies. Due to special engineering requirements, processes, and materials, the lead time for many of the parts can be several months resulting in a long aircraft lead time. During periods of high demand long aircraft lead time is less of a concern since manufacturers often have a large backlog, which is greater than the lead time, allowing them to build the aircraft to order. However, during periods of low demand, manufacturers may need to forecast demand and make the decision to start building aircraft before having a committed customer order. The longer the lead time of the aircraft, the further out into the future the manufacturer has to forecast, which leads to greater uncertainty and variability. In this environment it becomes essential to focus on lead time reduction to allow for better forecasting. Shorter aircraft lead times also have the added benefits of increasing flexibility in production and capacity planning, and lowering inventory holding costs and work in process. Reducing aircraft lead time can often be a difficult task. However, a structured approach to lead time reduction can be very powerful. This paper presents a framework for lead time reduction that is composed of a lead time reduction chart, which provides the correct areas of focus; a strategy flowchart, which identifies the components, strategies, and actions that can be implemented to reduce aircraft lead time; and a summary of reduction strategies that are focused on low rate, complex parts. While the framework is detailed toward aircraft lead time reduction, it is general enough to apply to most supply chain and manufacturing situations. This framework was used during a six month aircraft lead time reduction study at Sikorsky Aircraft Corporation, and analysis reveals that this structured approach was effective at reducing average aircraft lead time by 12.7%. / by John Andrew Marsh. / 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 Aeronautics and Astronautics, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 52-53). / This project was motivated by the desire to apply quality metrics to the multiple stages of the airplane development process at Boeing Commercial Airplanes. This project first identified integration and process discipline as most critical towards final quality of the engineering work. Integration, defined as the path and connectivity between teams and activities, was studied by analyzing performance of a small engineering support team. To understand the effects of early stage quality on later stages, i.e. process discipline, a system dynamics model was developed focusing on the design and development of components with suppliers. The case study regarding integration focused on the engineering work as a four-steps process: Inputs, Engineering Activities, Output and Customer Review. All unplanned reworked deliverables of a 5-7 members engineering team were analyzed. The study tracked the process step at which the error was first caused. The results found that 21% of unplanned engineering rework was caused due to inadequate delivery of inputs to the requested engineering work. Furthermore, the 21% of unplanned engineering rework had the highest hours per reworked deliverable of any stages. Over all, 75% of engineering rework was due mainly to the process rather than the actual technical engineering work. The system dynamic modeling achieved two main results: showcased the necessity to simplify the process, and the importance of accounting for iterations in engineering. Through the group-modeling discussions with the process owner, it was evident the need to provide clear checkpoints and reviews of the engineering work. Furthermore, discovering engineering rework within a given stage has the same effect as delivering first-pass engineering quality. This project provided a methodology to work with engineering teams to measure their quality performance. Furthermore, it has the potential to show the thresholds of quality from one stage to another in Airplane Development. / by Ammar Asfour. / 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 66-67). / As Amazon.com has grown, the company has invested in warehouse systems similar to those traditionally found in manufacturing. These systems are a complex and interconnected set of manned work processing stations linked together by conveyance. This thesis examines one such system, arranged as a set of parallel single piece workflow lines joined by a central computerized sorter that route work between lines, and examines the effect of sorter algorithms and line capacity on production output. Work studies, interviews, and a practical experiment suggest a deterioration in the feedback provided to the central sorter for work routing. A Monte Carlo simulation model of the system further supports this hypothesis, suggesting that system throughput is 11.7% lower than a system that perfectly routes work to line in a pull fashion. While perfect routing is not practically feasible, the thesis then explores two routing heuristics designed around starvation response and dynamic capacity analysis, which simulation suggest may yield a 6.73% increase in throughput. In doing so, the thesis provides a case study on process improvement using simulation to characterize a complicated mechanical production system that is otherwise analytically intractable. / by Willow Primack. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 51). / The quality of Caterpillar's welds is becoming increasingly important as their equipment is made leaner with the goals of increased performance, lighter weight and lower unit cost. Due to the inherently variable nature of arc welding, non-destructive weld evaluation is critical to ensure that welding processes remain in control, and that defective parts are quarantined and repaired before being released downstream. The "conventional" ultrasonic weld inspection technology in use at present has several limitations: -- Areas within common joint configurations cannot be adequately inspected due to geometry constraints; -- Discontinuity evaluation requires subjective real-time human interpretation by highly trained operators; -- The data produced by the instrumentation is unconducive to recording for off-line analysis; -- Imprecise defect sizing leads to Type I and Type II inspection errors - the unnecessary rework of good parts, and the inappropriate release of non-complying parts. This project addressed these limitations of conventional ultrasonic weld inspection by identifying and evaluating alternative commercially available technologies and by initiating the internal development of specific proprietary technologies tailored to Caterpillar's needs. Through collaboration with Caterpillar's non-destructive evaluation (NDE) community, as well as outside vendors, a technology known as "phased array" was selected and validated in the laboratory and production environments. Although phased array was not new to Caterpillar, its adoption within the production facilities had previously been limited. / by Michael T. Buelsing. / M.B.A. / S.M. in Engineering Systems