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Roy E. Welsch and Duane S. Boning. McCaghren, Neville G. (Neville Gregory) Leaders for Manufacturing Program. Leaders for Manufacturing Program at MIT Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Sloan School of Management 2006-11-08T16:48:43Z 2006-11-08T16:48:43Z 2005 2005 http://hdl.handle.net/1721.1/34848 63199771 Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2005. Includes bibliographical references (leaves 73-74). Most modern production processes automatically generate volumes of rich data, including equipment states, material presentations, labor content, and quality non- conformances. Unfortunately, much of this data is either discarded immediately, or stored in its raw form in disparate data sources for subsequent review or reporting. Accessing the data in these systems often requires time-consuming transformations, filtering for relevancy and substantial latency, rendering the potential wealth of information useless to daily decision- makers on the factory floor. Without such information, individuals on the floor rely on heuristics, experience, and intuition to inform their decisions, often resulting in inefficiency and suboptimal solutions. This work explores the idea that decision-making can be improved through the automated transformation of data into information for real-time display on the factory floor. This thesis reviews the technology infrastructure components, evaluation metrics and presentation displays deployed at Raytheon Company that can not only characterize a current process, but also suggest opportunities for process improvement. Case studies illustrate the identification of a process issue, the investigation of root causes and improvement alternatives, and the evaluation of change efforts, all using visual performance indicators. Work for this thesis resulted in several interactive dashboards in the Microwave area that characterize the production process in terms of schedule, cost, and quality compliance, with additional tools to investigate non-conforming processes. (cont.) The tools were first leveraged to improve line coordination and reduce process times for the radar sub-assembly process, resulting in a 50% increase in throughput, 70% reduction in throughput variation, and a cost savings of over 600 hours per radar for the targeted processes. More importantly, the technological and cultural foundations for continual process evaluation and improvement were laid, which have the potential to yield far greater improvements in the future. by Neville G. McCaghren. S.M. M.B.A. 74 leaves 5758947 bytes 5762029 bytes application/pdf application/pdf eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Sloan School of Management. Electrical Engineering and Computer Science. Leaders for Manufacturing Program. Enabling process improvements through visual performance indicators Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="7e112b7a-510e-4e39-aca8-ff3607d77547"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Enabling process improvements through visual performance indicators</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2005</PublicationDate> <Authors> <Author> <DisplayName>McCaghren, Neville G. (Neville Gregory)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Sloan School of Management.</Keyword> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Keyword>Leaders for Manufacturing Program.</Keyword> <Abstract>Most modern production processes automatically generate volumes of rich data, including equipment states, material presentations, labor content, and quality non- conformances. Unfortunately, much of this data is either discarded immediately, or stored in its raw form in disparate data sources for subsequent review or reporting. Accessing the data in these systems often requires time-consuming transformations, filtering for relevancy and substantial latency, rendering the potential wealth of information useless to daily decision- makers on the factory floor. Without such information, individuals on the floor rely on heuristics, experience, and intuition to inform their decisions, often resulting in inefficiency and suboptimal solutions. This work explores the idea that decision-making can be improved through the automated transformation of data into information for real-time display on the factory floor. This thesis reviews the technology infrastructure components, evaluation metrics and presentation displays deployed at Raytheon Company that can not only characterize a current process, but also suggest opportunities for process improvement. Case studies illustrate the identification of a process issue, the investigation of root causes and improvement alternatives, and the evaluation of change efforts, all using visual performance indicators. Work for this thesis resulted in several interactive dashboards in the Microwave area that characterize the production process in terms of schedule, cost, and quality compliance, with additional tools to investigate non-conforming processes.</Abstract> <Abstract>(cont.) The tools were first leveraged to improve line coordination and reduce process times for the radar sub-assembly process, resulting in a 50% increase in throughput, 70% reduction in throughput variation, and a cost savings of over 600 hours per radar for the targeted processes. More importantly, the technological and cultural foundations for continual process evaluation and improvement were laid, which have the potential to yield far greater improvements in the future.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>