Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, in conjunction with the Leaders for Global Operations Program at MIT, 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (pages 81-82). / As the retail industry grows more popular, ABCD, a world-class electronic commerce (e-commerce) business, is increasingly building new Fulfillment Centers (FCs) to support this rapid demand growth. It is integral for ABCD to validate the installation quality and functionality of Material Handling Equipment (MHE) in these newly built FCs so operations can avoid errors. To achieve this objective, ABCD introduced the Installation and Operational Qualification (IOQ) process in late 2014. While the IOQ process reduces early operational failures, it does not completely eliminate them. Inadequate IOQ and tighter installation timelines are leading to degraded installation quality, resulting in operational issues and costs for ABCD. As the FC network continues to grow, there is a need to improve installation quality to reduce early operational issues and enhance the FC start-up experience. / This project is a part of the ABCD Operation Engineering teams' effort to improve the existing IOQ process and the FC start-up experience. This initiative consists of three main phases. The first phase - the research phase - is dedicated to understanding the current processes and problem statement. It also includes a study of available data sources to discover failure patterns across different FCs. The second phase involves developing analytical frameworks and machine-learning models to uncover the most problematic equipment in the FC. The third phase focuses on evaluating the effectiveness of the current IOQ process based on Phase 1 and 2 findings, and identifying opportunities to better the process. The thesis summarizes the outcomes from all of these phases. The project focuses on improving IOQ coverage, efficiently reprioritizing the testing schedule, introducing threshold metric for installation quality, and exploring predictive and preventative maintenance opportunities. / This thesis also includes recommendations for refining the data-gathering process to improve future model outcomes. The ultimate goal is to improve FC installation quality and enhance the IOQ process to eliminate start-up issues. The approach taken and the recommendations proposed seek to approximate the ideal state as closely as possible. Incremental adoption of these recommendations will help deliver better-installed FCs, reduce early operational issues, improve start-up experiences, and strengthen ABCD's infrastructure. / by Bidusha Poudyal. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (pages 78-79). / Verizon may rely on third-party logistics providers (3PLs) to manage some aspects of the reverse supply chain of Fios equipment. As a result, it depends on the 3PL to continually strive for increased quality, reliability, capacity, and speed. Above all, in order to have a successful partnership, the process must be economical for the 3PL. As several sources of variation are detrimental to the 3PL's margins and cause operational problems, Verizon is investing in the supplier relationship to ensure that the 3PL is profitable and positioned for the future. Making sure there is a "win-win" relationship is beneficial for both parties and helps to ensure that the investments that have been made will continue to result in success, including operational improvements. To do this, a culture of continuous improvement and data-driven decisions needs to be cultivated and developed at the 3PL. The goal of this project is two-fold. First, there is a need to understand the variation that exists in the 3PL's process as well as the associated costs, which include overtime, ineffective labor and production planning, and high turnover. The secondary goal of the project is to empower the 3PL to make data-driven decisions in the future and start to shift their culture to one that aligns better with Verizon's. By showing the benefits of collaboration between the two companies, this project will help build trust. In this thesis, we discuss how process mining is used to understand the 3PL's current state and guide data-driven continuous improvement. We introduce several opportunities for handling variation, including creating visibility into return volumes, reducing defects caused by incorrect packaging, and creating feedback mechanisms for operators. This is done in close collaboration with the 3PL to ensure they will ultimately have ownership of implementation. / by Hannah Phillips . / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Cataloged from the official PDF of thesis. / Includes bibliographical references (page 54). / Retailers across the globe continue to grow their private label portfolio to offer customers an alternative to existing brands. Typically, retailers source private label products directly from manufacturers to remove middlemen from the value chain, thereby capturing greater value and subsequently passing it on to customers. Combined with the growth of e-commerce as the primary method for consumers to shop for products, expanding private label portfolio has made e-retailers to re-think their supply chain. Amazon began its journey in Private-Label Brands (PB) in 2009 with the launch of Amazon Basics. Since then, it has expanded its presence across multiple categories. The majority of these products are imported from Asia-Pacific region (APAC) and require sourcing larger quantities to account for long-lead time between production runs and high variability in demand to maintain competitive costs. / These factors result in PB inventory dwelling for a long period at the Amazon Robotic Fulfilment Centers (FCs), reducing the turns-ratio of expensive storage bins there, which could otherwise be utilized for storing high-velocity products. The growth of PB products raises the need to build more storage space, which is expensive in highly automated robotic FCs. Additionally, since fixed storage cost is proportional to the space occupied in FCs, high 'dwell time' translates to high storage cost. To increase utilization of FC storage bins, the Inbound Supply Chain Team plans to build a low-cost upstream storage (LCS1) to supply the FCs and store excess PB inventory there. Alternatively, Amazon can also use its third party storage center in APAC, another low-cost storage node (LCS2), after sourcing PB products from manufacturers in Asia before shipping to regional markets in US, EU, Japan etc. / This could provide an opportunity for inventory savings from risk pooling by optimizing inventory storage across various nodes in the supply chain. Using multi-echelon inventory optimization techniques, this thesis explores the tradeoffs between using low-cost storage node close to end customers in the US (LCS1) versus that close to manufacturing source in APAC (LCS2). The objective of the thesis is to find the optimal inventory placement strategy across three storage points - FCs, LCS1 in US, and LCS2 in APAC - to achieve the best-in-class customer experience (InStock availability) at minimal inventory storage cost. / by Shouvik Das. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 67-69). / Consistently high quality is important to any manufacturing environment, and especially so when operating in the highly regulated medical space, which typically targets zero defects in products serving patients. The New Product Introduction (NPI) process is a complex one, with many potential failure modes than can result in unanticipated costs, delays, and defective products. This project sought to streamline the NPI process through achieving three main objectives. First, NPI tools, processes, and checklists in current use were characterized. Second, insights for improving the NPI process were collected. Third, a new playbook was introduced to improve a specific aspect of the NPI process. Finally, recommendations were provided to direct future areas for potential improvement. While many of the tools in use were useful project management aids, recurring issues were identified, particularly at the front end of NPIs. A due diligence checklist was developed to structurally align the different parties involved with NPIs, facilitate communication, organize information, and increase the effectiveness of decision-making. This checklist was implemented using i- nexus, a software-based project management tool. This paper is focused on the manufacturing environment within Flex Inc.'s medical manufacturing division. However, this paper also discusses the relevance of checklists and other tools outside of this context. Project management environments in which these tools could improve quality, timeline, financial, and customer service outcomes are explored as potential areas for additional future work. / by William Geoffrey Winegar. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

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, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 62-64). / Nike established the Advanced Manufacturing team to create a future of manufacturing that will be able to better meet growing customer expectations, battle rising costs of production, and unlock new design capabilities. While new methods of manufacturing are groundbreaking for Nike, there is currently no standard operating procedure on how to properly integrate these new methods into footwear manufacturing. Nike would like to better understand the current process and identify ways to increase the ease of deployment to ensure profitability and improved speed to market. To do this, the research explored the current state of bringing onboard a new factory partner to the factory network, investigated metrics through which to evaluate inefficiencies, and provided suggestions for process improvements to create a more efficient future state. Future state projections show significant decrease in factory setup time. Preliminary implementation of the suggestions shows encouraging results in decreasing cost and increasing speed to market. While results are currently theoretical, this research provides a baseline framework to identify waste and develop process improvements to more efficiently onboard a new factory partner. / by Amanda Rikki Lurie. / M.B.A. / S.M. in Engineering Systems

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, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 83-84). / This thesis addresses the allocation of gas turbine aircraft engines to maintenance facilities. Scheduling a global engine maintenance network can be very complex and challenging. This project pertains particularly to the V2500 IAE engine maintenance network managed by Pratt & Whitney. Using a mathematical program to automate engine allocation was believed to reduce the workload on the organization and the cost of maintaining the 3100 engine fleet. An introduction to the engine maintenance network will be covered along with an explanation of Fleet Hour Agreements (FHA). A literature review of mathematical programming is included to provide background of pertinent information. The current state of the business is analyzed. An integer linear program is developed to closely represent the current state of the business. Historical data was used to feed the model, and the outputs from the model were compared to actuals. A sensitivity analysis is performed to better understand the constraints of the current business and the feasibility of the model. An optimization model should not be used to plan engine maintenance given the current state of business. The business is too dynamic and the network is highly constrained by capacity. The results also show a much smaller savings than were originally expected. This is mostly due to better understanding the cost of maintaining the engines at the different shops. The variation was much lower than originally expected. The current state is operating close to optimal with great flexibility and should continue on as is. / by Brandon Paul Gorang. / M.B.A. / S.M. in Engineering Systems

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, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 62-64). / Objective: In place of traditional stainless steel systems, the "Flexible Manufacturing" technology used at Amgen employs the impulse mixer single-use system, a bag technology, to house the product and serve as the locale for biological reactions. However, the impulse mixers have experienced high failure rates. About 14% of impulse mixers have failed, and these failures jeopardized $10 M of raw materials; they have also delayed manufacturing production by at least 12 days. This thesis identifies the root causes for the impulse mixer failure and proposes recommendations to reduce future failures. Methods: Semi-structured interviews (n=12) were conducted with system designers and with operators using the impulse mixer. A kaizen event to discuss impulse mixer failure was conducted for three days with ten key stakeholders from all manufacturing plants. A survey was implemented to gather and assess operators' perspectives (n=12) on the impulse mixer technology. Furthermore, quantitative data about 101 impulse mixers used from July 2013 to October 2015 were collected from all manufacturing sites. Qualitative methods were used to develop key themes from the semi-structured interviews and kaizen event around root causes, and statistical analysis of the quantitative data and survey were performed to identify and verify root causes. Hypotheses: The study proposes four hypotheses concerning impulse mixer failure: 1) preparatory training protocol changes will decrease the odds that impulse mixer single-use technology will fail; 2) operational training tools change will decrease the odds that impulse mixer single-use technology will fail; 3) operator's knowledge and confidence decrease as the operators are farther removed from interacting with the supplier, and 4) the plastic material's lack of strength influences impulse mixer technology to fail. Results: On the job training on the floor by the supplier to manufacturing operators (operational training) demonstrated to be very impactful in decreasing failure. Supplier, operational training of how to install the bag technology, is statistically significantly related (p<0.005) to the likelihood that the impulse mixer would fail. The odds of failure were about 1 in 6 for the first operational training. In contrast, in a third operational training the odds of failure dropped to about 1 in 220. Recommendations: The supplier needs to provide more training to the manufacturing operators in how to install the technology. More interaction between the supplier and operator will decrease the technology failures in the floor. At the moment, there is a very complex system for operators to acquire information from the supplier, making it difficult for operators to acquire information when they needed it. A leaner system where the interaction is direct is needed. / by J Guadalupe O. Mota. / M.B.A. / S.M. in Engineering Systems

Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 81-83). / In the semiconductor industry where the technology continues to grow in complexity while also striving to achieve lower manufacturing costs, it is becoming increasingly important to drive cost savings by screening out defective die upstream. The primary goal of the project is to build a statistical prediction model to facilitate operational improvements across two global manufacturing locations. The scope of the project includes one high-volume product line, an off-line statistical model using historical production data, and experimentation with machine learning algorithms. The prediction model pilot demonstrates there exists a potential to improve the wafer sort process using random forest classifier on wafer and die-level datasets. Yet more development is needed to conclude final memory test defect die-level predictions are possible. Key findings include the importance of model computational performance in big data problems, necessity of a living model that stays accurate over time to meet operational needs, and an evaluation methodology based on business requirements. This project provides a case study for a high-level strategy of assessing big data and advanced analytics applications to improve semiconductor manufacturing. / by Naomi Arnold. / S.M. in Engineering Systems / 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. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 60-61). / Aircraft Company X (AX) manufactures and assembles an immense variety of parts utilized as drive systems and rotor components across its multiple aircraft. The company's value proposition is maintaining the ability to build and service all legacy parts and as a result there is a great deal of variety found in its manufacturing processes. This variety stems from upgrades to manufacturing technology, improvements in material science, design variations, and individual part engineering modifications. In order to be responsive to fluctuating demand while minimizing costs, AX must broadly implement postponement into numerous applications as a way to extract the most value from its resources. This thesis uses multiple applications of postponement within AX to establish a methodology that can be used across various materials, both metallic and non-metallic. This methodology guided implementation of postponement through material physical form consolidation, material substitutions, and even provided insight into which manufacturing technique given a particular material form is optimal. The benefits are numerous to include a roughly 30% inventory reduction, improved buying power resulting in cost savings of over 10%, a reduction of material shortages by over 40%, and shorter lead times for finished goods. Extensions of these applications include aligning AX's supply chain with its suppliers utilizing identified tolerances and adding layers of postponement beyond raw material inputs. / by Julius Myers. / M.B.A. / S.M. in Engineering Systems

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 Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 67). / Company X provides healthcare diagnostics testing services. The company competes in the market by providing cost effective, short turn-around-time (TAT) solutions and a large variety of test selections. Reducing operating costs is a major area of ongoing improvement for Company X, and this effort includes reducing reagent costs in high volume diagnostics platforms across the nation. The objective of this thesis is to identify the major causes of reagent waste, and reduce unnecessary reagent consumption on a specific high volume testing platform which can test multiple different assays. The project targeted finding measures to mitigate reagent waste which can be employed in all sites. The current state analysis identified quality control testing that exceeded regulatory requirements and minimum standards defined in the SOPs and unoptimized distribution of assays to instruments as causes of unnecessary reagent consumption. The analysis also identified patient tests repeated due to mechanical errors in the instruments as another cause of reagent waste. Countermeasures are developed to mitigate these issues. In order to reduce reagent consumption due to superfluous quality control testing, a workflow study is conducted. The workflow study targets the minimization of quality control testing and instrument calibrations by optimizing the load distribution over similar instruments within a laboratory site. The optimal distribution of patient test volumes to instruments is modeled and solved as a linear programming problem. In addition to workflow optimization, process standardization and preventive maintenance strategies are explored. / by Hakan Sonmez. / M.B.A. / S.M.