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. / Employee health and safety are a top priority in aerospace manufacturing. As companies increase their production systems capacity in preparation for upcoming rate targets, new opportunities for continuous improvement start becoming evident and time critical. A strong collaboration of Health and Safety, Quality, Manufacturing and Research and Technology groups is paramount to ensure that adequate technologies are developed and deployed in the right stages of the manufacturing system in a way that is compliant with both technology readiness and the business needs. The integration of collaborative automation on ergo-motivated continuous improvement projects pose two major challenges in this aerospace manufacturing process. Firstly, the availability of resources to measure the current state, i.e. the identification and prioritization of the sub-steps and specific tasks in the process that require technological intervention. Secondly, the potential incompatibility of production systems, continuous improvement and technology development road maps that limit the speed at which new technologies flow to the shop floor. By leveraging the existence of historical safety performance and labor-tracking data, the proposed methodology offers an immediate approximation of occupational risk of the current state. This allows a "first gate" deliverable for any given continuous improvement project for the Occupational Health and Safety group with minimal use of resources, a framework for the R&D organizations to create and prioritize ergonomically-driven projects and ultimately complement business cases to propel technologies towards final deployment. The methodology results in a statistical risk profile that highlights the manual sub-steps of a product line that show better candidacy for collaborative automation. Continuous improvement and conventional Lean/Six Sigma tools where furthermore applied to demonstrate process capability and move a collaborative robot through the production system implementation roadmap in record timing. / by Guillermo Pamanes Castillo. / 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 117-119). / The use of highly effective intravenously infused specialty drugs has increased significantly over the past two decades as they have led to dramatic improvements in patients' quality-of- life. At Massachusetts General Hospital, these drugs are administered in ten independent outpatient clinics. While some clinics only need to offer sporadic treatments and have low utilization of resources, other clinics find patient access is severely limited due to high utilization, poor scheduling practices, and inadequate staffing. This thesis describes methods to increase patient access to infusion while improving resource utilization. Underlying this improvement is a specially developed scheduling algorithm that smooths chair utilization while permitting flexible, multi-day scheduling. By employing the new scheduling algorithm, the recommended centralized infusion unit will be able to provide more expedient care, offer emergent appointments, avoid unnecessary hospital infusion admissions, and make more efficient use of clinical resources. Adding only two days of flexibility to appointments reduces resource requirements by up to 57%. Also, the day-to-day variability in patient volume is stabilized. Finally, the centralization of administrative resources ensures efficient prior authorization processing, leading to significant financial savings. / by Adam Ryan Marshall. / 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, 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 38-39). / The main goal of this project is to identify opportunities to improve the reliability of the DxHTM product line, an automated hematology instrument for analyzing patient blood samples. The product was developed by Beckman Coulter Diagnostics, a division of a Danaher operating company with principal manufacturing and support operations based near Miami, Florida. A critical business metric used to reflect reliability is the Emergency Service Call (ESC) rate. An ESC for an instrument is defined as the number of unscheduled, on-site technician visits during the one year warranty period. Though Beckman Coulter already deploys an extremely robust quality control system, ESCs can still occur for a wide variety of other reasons resulting in an impact to reliability. Any tools that support the reduction of ESCs may help generate positive perceptions among customers since their instruments will have greater up-time. This project entails an evaluation of a new initiative called "Reliability Statistical Process Control" (R-SPC). R-SPC is a form of manufacturing process control developed internally consisting of an electronic tool that collects raw instrument data during manufacturing. Unusual measurements are automatically sent to a cross functional team, which examines the potential trend in more detail. If an abnormal trend is identified, the examination could generate a lasting improvement in the manufacturing process. Currently, the success of R-SPC is measured by the extent to which it reduces ESCs. Because an unusual measurement engenders further actions to investigate an instrument, it is desirable to show with empirical evidence that the measurement is linked to reliability. To assess whether particular measurements were systematically related to the ESC rate, relevant data were analyzed via the Pearson Chi Squared statistical test. The tests revealed that some of the variables now monitored do not appear to affect the ESC rate for the range of values studied. In contrast, several proposed "derived" parameters may serve as better indicators of an instrument's ESC rate. Moreover, the Chi Squared methodology described can be used to investigate the relationships between other variables and the ESC rate. The thesis concludes by offering several specific recommendations to help refine the R-SPC initiative. / by Marshall Edward Fox. / 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, 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 119-123). / Additive manufacturing (AM) has emerged as an effective and efficient way to digitally manufacture complicated structures. Raytheon Missile Systems seeks to gain limited production capability with metals AM, which can only be achieved with qualified, predictable processes that reduce variation. The project documented in this thesis produced two results needed to qualify AM for use on flight-critical parts: i) creation of a standard qualification process building upon Raytheon's product development knowledge, and ii) selection and identification of key metals AM process factors and their corresponding experimental responses. The project has delivered a qualification test plan and process that will be used next year to drive adoption and integration of Raytheon's metals AM technology. The first phase of the designed experiment on AM process factors was completed by experimenting with coupon orientation, position on the build platform, coupon shape and hot isostatic pressing (HIP) post-treatment for an Al alloy (AlSi10Mg) produced via laser powder bed fusion using 400-watt laser equipment. Only coupon orientation had a statistically significant effect on dimensional accuracy, increasing the variance of y-axis (within the build plane) error by ~50%, although this is considered a small increase. HIP decreased yield and ultimate stresses by ~60% while increasing ultimate strain by ~250%. Vertical orientation of coupons decreased yield and ultimate stresses by ~25% and increased ultimate strain by ~30%. Small coupon area on the build platform, associated with thin rectangle coupons, decreased yield stress and ultimate strain by ~5%. The processes and case study from this thesis represent a general advance in the adoption of metals AM in aerospace manufacturing. / by Andrew James Byron. / 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, 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 (page 43). / Aircraft Company X (ACX) designs and manufactures aircraft. ACX operates Manufacturing Center 1 which produces parts and assemblies for both assembly and spares business lines. Accurate scheduling is crucial for meeting demand and the on time delivery of parts, a key driver of customer satisfaction. Managers currently use a manual process to generate a short interval schedule for production in this volatile, high variety, low volume environment with reentrant flow. The current process is not only time consuming but also disrupts coordination between supporting functions. This thesis explores the challenges of developing and implementing an automated scheduling tool in a flexible job shop with re-entrant flow, part families, sequence dependent set-up times, and machine eligibility restrictions. First, a model is developed from current scheduling rules used by shop floor supervisors. The model uses the earliest due date dispatching rule and part family information to schedule a group of parallel machines. This model is then incorporated into a scheduling tool, which is implemented and tested in the plant. Finally, the results of the implementation are discussed along with improvement to the tool. The purposed tool demonstrated during testing the ability to save a significant amount of the supervisors' time by reducing their involvement in scheduling, to reduce set-up times by grouping similar parts, and to align support functions by providing a unified build plan for the plant. / by Stephen Paul Baxter. / 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, 2017. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2017. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (page 67). / Large, multi-national retailers have massive, worldwide supply chain networks which move product from a supplier to the end consumer. During the product's transit from a factory to a regional distribution center, customers may change or cancel their order, or the planned arrival date of the product at the distribution center may change. These products are packed in containers and arrive at the distribution center daily. Each day, humans may make decisions of which containers will be received at a distribution center and there are opportunity costs associated with selecting the wrong container to receive, namely, that the distribution center will become filled with product which is not immediately needed to meet outbound demand. This thesis analyzes one method of receiving containers at a distribution center and the impacts it has on satisfying customers' orders. A model for a lean inventory management system and a container selection optimization model are described in it. Representative data is presented and the model is used to solve which containers should be received. Finally, the efficacy of the model and a comparison to a heuristic are discussed. / by Russell G. Forthuber. / 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 35-36). / This thesis develops a method by which overtime could be reduced in a highly variable drug substance purification manufacturing environment. Purification production overtime (20%) is a big cost driver at Building XX1 (BXX). Current production planning and labor resource evaluation methods at BXX Purification are manual, do not capture schedule delays, and do not adequately account for labor availability. Because of this, BXX is unable to accurately evaluate to what extent labor resource contributes to bottlenecking or how to improve overtime. A tool is devised in the Virtually Exhaustive Combinatorial System (VirtECS®) Scheduler software whereby purification production schedules are modeled and optimized. The model simulates production delays and the flow of production. Results lead to a more accurate understanding of how labor resource constrains the lot cycle time and where improvements in shift structure could be made to improve lot cycle time and variability of lot cycle time. The purification production schedules of two monoclonal antibodies (mAb) were modeled with the use of VirtECS® Scheduler. These two drug substances are selected to reflect the majority of BXX's mAb pipeline. The plant, BXX, produces a high mix of clinical and commercial launch drug substances, and is subject to a number of stochastic scheduling delays. Excel® is used to generate random sets of process times to simulate delays. These process times are fed into VirtECS®, a production schedule optimization tool, which then produces a simulated set of production schedules. Scheduling decisions of shift labor allocation and when manufacturing should start production during the week are simulated using the model. Results from this evaluation illustrate opportunities for BXX to improve overtime. Lot cycle time is found to be reduced by up to 5.9% based on model results by moving the start of production towards the end of the week and allocating more resources to the third shift from second shift. Additionally, cycle time variability, could be reduced by up to 22%. The model makes a number of assumptions which simplify purification operations whose effect should be further investigated. Future improvements for VirtECS® are proposed to better model BXX processes. / by Seth McIntire. / 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 63-64). / Usage of single-use systems (SUS) in biomanufacturing has expanded rapidly in recent years. Amgen uses SUS at several commercial manufacturing sites, in addition to pilot plants and clinical production. Each single-use assembly is typically custom designed and manufactured by a third-party integrator. This has led to the proliferation of single-use specifications, with hundreds of assemblies in the Amgen library. These specifications collectively require tens of thousands of manhours to create, maintain, and eventually decommission. In addition, the purchase of so many unique assemblies hinders the ability to competitively bid on each design, increasing commercial risk. Finally, each Amgen site must maintain required inventory levels of its specific assemblies, with few opportunities to optimize safety stock between facilities. The goal of this project is to evaluate the hypothesis that increasing the usage of modular design principles will reduce procurement cost, supply risk, and inventory requirements. In addition, standardization of SUS will result in the creation of fewer unique assemblies, greatly reducing the overhead requirement from the engineering, quality, and process development organizations. This thesis proposes actions Amgen may implement to achieve a more modular SUS design framework and to realize the aforementioned benefits. Studies completed during this research are supportive of increased modularity. An inventory analysis showed that safety stock levels decrease by 30% when a sample of similar assemblies are shared between sites. A study of a new single-use process at an Amgen site suggests that adopting two modular approaches genderless aseptic connectors and sterile welding - yield the most desirable outcome, with 5-year NPV savings exceeding $3 million USD. This number would increase substantially if applied to SUS across commercial manufacturing. While only modestly reducing the number of required assemblies, this scenario also involves the least amount of time required to connect the assemblies and address nonconformances. Some modular design practices, such as utilizing standard lengths and building large assemblies out of small ones, are counterproductive due to the increased number of connectors and potential for leaks. Therefore, a moderate modular approach is recommended, along with the adoption of supplier standard designs when available. / by Clinton Scot Rendall. / 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 57). / The large multi-channel apparel distribution center was built as a purely wholesale building in the 1900s. With distribution becoming more complex due to e-commerce and smaller orders for more frequent replenishment, the requirements for the distribution center have changed significantly. The manner in which work flows through the building is influenced by batch size and release logic, which have not evolved to keep up with changing demand. Under the current flow of work, associates cannot stay busy working at the same processing (packing) station. Unstaffed processing stations are used as buffers, and associates move to unstaffed processing stations when they run out of work. The current flow prevents staffing all of the processing stations which significantly reduces the long-term throughput capacity. This thesis lays out a methodology to improve flow and unlock throughput capacity by changing batch size and control logic to meet future demand. The key enablers of this thesis were: 1) The collection of data to evaluate progress at key steps in the process 2) A holistic understanding of how the system functions, as well as the implications on the longterm throughput capacity / by Ryan Cannon Morrison. / 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 103). / Modular engineering allows the creation of a product architecture that prepares the product families of companies for a fast response to changes in technology and customer demand. This thesis will focus on developing and proposing a methodology for implementing modular engineering at AIP's portfolio companies and ensure that the implementation is replicable in any other of its companies. AIP companies are from very diverse industries and offer multiple heterogeneous products. The proposed methodology will make it possible to target companies and products that are good candidates for the implementation of modularity from the standpoint of cost benefit. One AIP portfolio company is currently implementing modular engineering. This project was the base for creating a use case. This thesis explores the methodology used by the portfolio company for designing a modular architecture and proposes an automated approach using machine learning techniques. This will allow a faster creation and evaluation of the modular architecture. In addition, the modular project benefits are: fewer unique part numbers, less assembly time, lower direct purchasing costs, fewer suppliers, faster time to market, shorter lead-time and more market offerings. The bottom line benefit is a streamlined operation that would add value to the company. Finally, this thesis summarizes the lessons learned of the modular engineering implementation to serve as a guide for future implementations on portfolio companies. / by Chen Josué Arámbula González. / M.B.A. / S.M.