2026-09-20T11:53:40Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/438312022-01-28T21:21:37Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
David Hardt and Roy Welsch.
Davis, Daniel Jacob
Leaders for Manufacturing Program.
Leaders for Manufacturing Program at MIT
Massachusetts Institute of Technology. Department of Mechanical Engineering
Sloan School of Management
2008-12-11T18:35:00Z
2008-12-11T18:35:00Z
2008
2008
http://hdl.handle.net/1721.1/43831
262694782
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.
Includes bibliographical references (p. 139-143).
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.
(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.
by Daniel Jacob Davis.
S.M.
M.B.A.
143 p.
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.
Mechanical Engineering.
Leaders for Manufacturing Program.
Achieving Six Sigma printed circuit board yields by improving incoming component quality and using a PCBA prioritization algorithm
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="134be235-8cde-48f1-99e1-25a255e4b582">
<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>Achieving Six Sigma printed circuit board yields by improving incoming component quality and using a PCBA prioritization algorithm</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2008</PublicationDate>
<Authors>
<Author>
<DisplayName>Davis, Daniel Jacob</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>Mechanical Engineering.</Keyword>
<Keyword>Leaders for Manufacturing Program.</Keyword>
<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.</Abstract>
<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.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>