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Achieving Six Sigma printed circuit board yields by improving incoming component quality and using a PCBA prioritization algorithm

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dc.contributor.advisor David Hardt and Roy Welsch. en_US
dc.contributor.author Davis, Daniel Jacob en_US
dc.contributor.other Leaders for Manufacturing Program. en_US
dc.date.accessioned 2008-12-11T18:35:00Z
dc.date.available 2008-12-11T18:35:00Z
dc.date.copyright 2008 en_US
dc.date.issued 2008 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/43831
dc.description 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 Manufacturing Program at MIT, 2008. en_US
dc.description Includes bibliographical references (p. 139-143). en_US
dc.description.abstract Printed circuit board assemblies (PCBAs) are the backbone of the electronics industry. PCBA technologies are keeping pace with Moore's Law and will soon enable the convergence of video, voice, data, and mobility onto a single device. With the rapid advancements in product and component technologies, manufacturing tests are being pushed to the limits as consumers are demanding higher quality and more reliable electronics than ever before. Cisco Systems, Inc. (Cisco) currently manufactures over one thousand different types of printed circuit board assemblies (PCBAs) per quarter all over the world. Each PCBA in Cisco's portfolio has an associated complexity to its design determined by the number of interconnects, components, and other variables. PCBA manufacturing yields have historically been quite variable. In order to remain competitive, there is an imminent need to attain Six Sigma PCBA yields while controlling capital expenditures and innovating manufacturing test development and execution. Recently, Cisco kicked off the Test Excellence initiative to improve overall PCBA manufacturing yields and provided the backdrop to this work study. This thesis provides a first step on the journey to attaining Six Sigma PCBA manufacturing yields. Using Six Sigma techniques, two hypotheses are developed that will enable yield improvements: (1) PCBA yields can be improved by optimizing component selection across the product portfolio by analyzing component cost and quality levels, and (2) Using the Six Sigma DMAIC (define-measure-analyze-improve-control) method and the TOPSIS (Technique for Order Preferences by Similarity to Ideal Solutions) algorithm, PCBA yields will improve by optimally prioritizing manufacturing resources on the most important PCBAs first. en_US
dc.description.abstract (cont.) The two analytical tools derived in this thesis will provide insights into how PCBA manufacturing yields can be improved today while enabling future yield improvements to occur. en_US
dc.description.statementofresponsibility by Daniel Jacob Davis. en_US
dc.format.extent 143 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Sloan School of Management. en_US
dc.subject Mechanical Engineering. en_US
dc.subject Leaders for Manufacturing Program. en_US
dc.title Achieving Six Sigma printed circuit board yields by improving incoming component quality and using a PCBA prioritization algorithm en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.description.degree M.B.A. en_US
dc.contributor.department Sloan School of Management. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US
dc.contributor.department Leaders for Manufacturing Program. en_US
dc.identifier.oclc 262694782 en_US


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