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 Mechanical 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 129-130). / Canam Group ("Canam") is a manufacturer of steel components and building products used in the construction industry. The company uses a distributed network of manufacturing centers throughout North America to build and ship joist and deck product to its customers. Each manufacturing center utilizes a similar set of equipment assets in the production process. Equipment assets are not connected to a data collection system capable of monitoring their performance and health. As a result, comparing the performance of similar equipment across sites is a challenge for the organization. The motivation for this thesis is to determine how Internet of Things (IIoT) technologies can be applied to an industrial business like Canam to improve asset monitoring capabilities. An experimental approach is used to demonstrate how IIoT frameworks discussed in literature can be employed in practice. / In the first experiment, a network connectivity audit is performed to answer a set of practical questions about data communication within an industrial machine network. In the second experiment, a commercial tool is deployed at a specific equipment asset and integrated into the production workflow to collect data about the performance of the equipment. Downtime data collected from the IIoT tool deployed in the experimentation phase is compared with data collected using an existing manual data collection process. The data collected from the IIoT device revealed a systematic under-reporting of downtime in the manual process. Machine availability was shown to be 46% as compared to 90% recorded in the manual process. A model is presented to demonstrate that improving availability of critical equipment could lead to a 6% increase in plant throughput. / The thesis concludes by combining the findings of the experimental results and literature review to develop a framework from which the business can establish an organizational vision for IIoT, an implementation plan, a project scoping methodology and vendor selection criteria.. / by David Woodruff. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 56-57). / This thesis proposes a supply chain model to improve the lead time for Caterpillar Medium Wheel Loaders in the North America market. The Medium Wheel Loaders division is undergoing many commercial value chain challenges: long lead time to dealers, high demand variability and high degree of configuration complexity. The long lead time may cause Caterpillar and its dealership network to build inventory, leading to high holding costs and inventory management issues. In addition, its customers may turn to competitors to meet their demand causing Caterpillar to lose sales. This project analyses structurally significant features needed to build the core machines at the factory and the parts required for the late stage differentiation at the distribution centers. In addition, it proposes the supply chains models using core configuration and delayed product differentiation concept and optimized inventory in the chain. Finally, the project determines whether the new supply chain brings value not only to Caterpillar but also to the dealers. The project focused on the 950GC machines sold on the North America market. A preliminary study shows that from a pool of a few hundred sold in North America, over hundred different configurations were used, for an average of less than 3 machines sold per configuration. A further analysis of the machines configurations demonstrates that following the core strategy, the machines configurations could be reduced from a few hundred to 8 core configurations. Our models indicate that Caterpillar experiences an increase of inventory while the dealers see their inventory goes down. As a result, Caterpillar incurs more inventory cost with the core strategy while the dealers see their profit increases. But with a better service level and shorter lead time, Caterpillar may increase its market shares. / by Bi Zan Valery Lorou. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 60-61). / Ascent Aerospace's leadership recognizes the transformative potential of additive manufacturing (AM) to the aerospace tooling industry. As a middle market company, Ascent required a deliberate approach to identifying areas with the highest potential for value creation. Without the research and development budget of an aerospace OEM, the best path forward for Ascent is to leverage existing AM technologies and those requiring minimal further development. The motivation for this project is to identify the best path forward for Ascent in leveraging AM as a value creation tool. Ascent had no AM capability at the beginning of this project, using a supplier when AM components when specifically requested by a customer. The thesis describes a methodology and results for identifying where to integrate AM into operations. It discusses the data and analysis used to find impact areas. The thesis also addresses some of the barriers impacting the adoption of AM. The analytical methods and organizational factors for additive adoption provide a holistic view of how to integrate AM into regular operations. Abstracted away from the case studies, the method should be actionable at any capitally constrained company to generate value through the adoption of AM. Recommendations on future work on how to approach the adoption of AM will be discussed, along with specific future work related to the thesis. / by Thomas J. Mangan, IV. / M.B.A. / S.M. / M.B.A. Massachusetts Institute of Technology, Sloan School of Management / S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 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 73-75). / Quest Diagnostics provides diagnostic information to clinicians, allowing them to make informed decisions on the appropriate course of treatment for their patients. Quest advertises an 8 a.m. next-day turnaround time for a subset of clinical tests, a service that provides competitive advantage for Quest. When this 8 a.m. turnaround time goal is missed, it causes ripple effects throughout the customer support organization resulting from increased client complaints. This research approaches Quest's late-release challenges through an analysis of phlebotomy services, courier route planning, and specimen accessioning to find precisely the source and cause of challenges preventing Quest from achieving their turnaround time goals. Prior to this research, Quest hypothesized that their logistics network could provide a consistent in-flow of patient specimens into their Marlborough, MA facility, improving the lab's likelihood of reaching their turnaround time goals. A simulation of a new demand-focused vehicle routing solution suggested that creating routes to provide a steady inflow of specimens would increase operating costs by 72%; what appeared to be an attainable, low-cost solution was found to be quite the opposite. We then provide an analysis of pre-analytical processes outside of logistics. Patient service centers (PSC) will soon provide 47% of the total specimen-volume to the Marlborough laboratory compared to 36% currently, thus evaluation of PSC processes and methodologies were conducted to identify ways to release a larger percentage of specimen volumes during midday courier pickups. Recommendations for process improvements to provide couriers with more patient samples during midday pickups are provided. Specimen accessioning processes and staffing were also analyzed, revealing that between 17%-24% of the subject tests results were unable to be resulted prior to 8 a.m. due to insufficient staffing for a second-stage accessioning task. Alterations to Quest's logistics network proved to be costly and low-impact, whereas slight alterations to phlebotomy-service processes and in-lab staffing could provide far higher value to Quest's customers with less impact to operations. By redirecting their focus to these other pre-analytical processes, Quest could focus their efforts on higher impact, lower cost options to improve operations and meet their turnaround time goals. / by Kevin M. Thomas. / S.M. / M.B.A.

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 (pages 93-96). / Dell's target to provide quality products based on reliability, security, and manageability, has driven Dell Inc. to become one of the largest PC suppliers. The recent developments in Artificial Intelligence (AI) combined with a competitive market situation have encouraged Dell to research new opportunities. Al research and breakthroughs have risen in the last years, bringing along revolutionary technologies and companies that are disrupting all businesses. Over 30 potential concepts for Al integration at Dell Inc. were identified and evaluated to select the ones with the highest potential. The top-most concept consisted of preventing in real time the failure of hardware. This concept was investigated using a data science process. Currently, there exist a number of machine learning tools that automate the last stages of the proposed data science process to create predictive models. The utilized tools vary in functionality and evaluation standards, but also provide other services such as data and model storage and visualization options. The proposed solution utilizes the deep feature synthesis algorithm that automatically generates features from problem-specific data. These engineered features boosted predictive model accuracy by an average of 10% for the AUC and up to 250% in recall for test (out of sample) data. The proposed solution estimates an impact exceeding $407M in the first five years for Dell Inc. and all of the involved suppliers. Conservatively, the direct impact on Dell Inc. is particular to batteries under warranty and is expected to surpass $2.7M during the first five years. The conclusions show a high potential for implementation. / by Mario Orozco Gabriel. / 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., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 71-72). / General trends in the commercial aircraft aftermarket indicate an increased reliance of leased engines in operators' spare engine strategies. A methodology for forecasting short-term engine lease demand is developed using Pratt & Whitney's existing simulation capability. This method demonstrates the ability to estimate demand mean and variance. This forecast is then used in a single SKU inventory model to set inventory levels. Using historical data this method demonstrates the ability to recommend inventory levels that minimize stock outs. A less computationally intensive system dynamics model is then constructed to replicate the lease demand forecasting model. Sensitivity analysis is performed using the system dynamic model and influential parameters are identified. The results of the sensitivity study are used to propose and test a new sales strategy for short-term engine lessors. / by Erin C. Kellogg. / 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 87-88). / As aerospace Original Equipment Manufacturer's (OEM's) order backlogs soar to between six to ten years and growing, the community sees automation as vital to increasing throughput. Yet the community seems divided on the quantifiable financial benefits. While automation in aerospace assembly dates back to 1937, there is little substantive research on quantifying its business case. This thesis develops a financial model that predicts the benefit of introducing automation into an OEM's manual assembly line. The hypothesis of this project is that there is, in fact, a quantifiable benefit to implementing assembly automation into a current manual assembly process. Based on an initial automation capital investment, the financial model calculates the Net Present Value (NPV) of an aerospace automation project given various OEM production inputs such as: the annual production schedule, learning curve metrics, labor hour savings through automation, rework, health & safety metrics, and automation operating and downtime costs. A current program was used as a case study against the financial model. One significant finding is the effect production learning has on the labor hours saved from automation introduced in this thesis as the 'Efficiency Factor'. Based on the OEM's conservative production data and an initial automation investment of $12M the NPV for the project is about $16M for the firm order (600 ship sets) and about $27M for the entire program (2000 ship sets). / by Sean Michael Caetano. / 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 (page 55). / One of Company X's many services is to refurbish systems at regular intervals during their use. Quick turnaround times are of the utmost importance both to keep Company X's costs low and to ensure the systems are returned to perform their services in the field as rapidly as possible. This research had two distinct elements in service to accelerated turnaround times: 1) Improving inventory management practices to align with the need for replacements for failed parts to reduce cycle times, and 2) Diagnosing the reasons for and developing mitigations against failures in the blind mating of two connectors. Regarding the first element of the research performed, Company X hypothesized that improving the inventory management system would yield shorter cycle times. In order to test this hypothesis, part failure and inventory histories needed to be compared to confirm if parts were not in stock at the time of failure. A model was developed to analyze both of these history files but the poor quality of the data precluded accurate conclusions from being drawn. Once the data input methods have controls placed on them, the model will serve to accurately represent the failure rates and types of failures of all parts, allowing for proper stocking of inventory needed to service these failures. An investigation of process failure rates and their impact on cycle time was also conducted. This analysis included quantifying how many times each operation was performed, at which steps failures occurred or were noticed most, and how much time was required to complete each operation and service each failure. This analysis ultimately yielded the generation of a diagnostic tool with a flexibility that allowed simultaneous analysis to be performed on over 1,100 operations. One of the key insights generated by using this tool was that the majority of failures are found at late-stage inspections, highlighting that improving the thoroughness of early-stage inspections could prevent the necessity of substantial rework to remedy the issues found late in the process. With respect to the second element of the research performed, an understanding of why and how connectors were failing was sought out. Through observing the process and analyzing the historical data detailing the connector's failure modes, multiple explanations for the failures and related solutions resulted. The first failure mode was loose connections, for which a tool was shortened to increase the operator's ease of accessing the connector to properly apply torque and secure the connection. The other modes of failure were caused due to connector misalignment, for which a bracket was redesigned as an auto-alignment feature to aid in the mating process, and operator deviations from the work instructions were addressed as they pertained to connector failures. The combination of these actions are expected to yield an annual savings of $100,000, net of costs. / by Tyler Lee Capps. / 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 (pages 116-121). / The long development lead time and high R&D costs for biologics drugs makes it imperative to eliminate delays and inefficiencies. Limited process development capacity can lead to delays in the availability of life-saving drugs and a large opportunity cost for biopharmaceutical companies. This study investigates the combined viability and impact of two approaches, namely applying lean principles and using high-throughput technology to increase capacity and productivity in pivotal biologics drug process development. Specifically, the project will explore a framework for improved handoffs and work design, and propose management systems to sustain implementation. In parallel, the study tests the sensitivity of the process development cycle to various resource constraints through a discrete event simulation and develops heuristics for the effective use of high-throughput equipment in upstream and downstream processes to increase process development capacity. The two approaches identified a potential increase in throughput of 2.75X (+175%) in preparation for an anticipated 2.3X (+129%) growth in biologics program demand in pivotal process development. / by Maria Dominique Bautista Rustia. / 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 (pages 61-63). / Beckman Coulter, one of Danaher's operating companies, provides diagnostic equipment and consumables to the health industry. A variety of plastic manufacturing methods are used to make instrument parts and consumables worldwide via third-party manufacturers who operate assets owned by the original brand. Worldwide, more than 200 of these manufacturers operate more than 2000 tools owned by Beckman Coulter. The lack of a centralized visibility of the real-time condition of these tools promotes a faulty maintenance plan that causes unexpected failures, reduces its productivity, and stimulates a "fire-fighting" environment within the engineering team. The motivation for this research is to contribute to protect the company's revenue stream by improving the efficiency of the manufacturing assets, which will ultimately improve the on-time deliveries and reduce procurement and operational costs. The thesis proposes that those objectives can be achieved through an efficient and effective system to track the current condition of manufacturing assets (primarily tooling) designed for the complex network of part manufacturers. The system provides reliable and dynamic information about the progress of the tools' life-cycle, record maintenance and failure events, monitors the OEE, and collects relevant data to enable a predictive model for future failures. The research starts investigating root causes for low effectiveness, through the analysis of the current state, and evaluates alternatives to track assets' condition and life-cycle across the complex and large supplier network. The selected alternative is to use the parts receipts, currently available through the company's ERP, as a proxy for the tools' shot-count. This indicator is used as the cornerstone for the Manufacturing Assets Management System, which acts as a single-reference point database and interface to visualize the assets' life-cycle, interdependencies with other elements in the network, condition, and effectiveness. It is also a depository for maintenance and failure data which could enable predictive maintenance. It is designed to scale up and to be useful for any internal and external manufacturing assets. Lastly, the thesis analyzes the ideal conditions and characteristics that the system would require to achieve Industry 4.0 standards, exploring and proposing the most effective technologies that are viable to be implemented in a large, commoditized, supplier-based, manufacturing network, to enable more advanced predictive analytics designed to improve OEE. / by Álvaro Mufarech Rey. / M.B.A. / S.M.