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Designing-in of Quality Through Axiomatic Design

Author(s)
Suh, Nam P.
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Copyright: Institute of Electrical and Electronic Engineers (IEEE) This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site/mainsite/menuitem.818c0c39e85ef176fb2275875bac26c8/index.jsp?&pName=corp_level1&path=about/documentation/copyright&file=policies.xml&xsl=generic.xsl
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Abstract
Decisions made during the design stage of product & process development profoundly affect product quality and process productivity. To aid in design decision making, a theoretical framework is advanced: the axiomatic approach to design. Axiomatic design consists of: 1) domains in the design world, 2) mapping between these domains, 3) characterization of a design by a vector in each domain, 4) decomposition of the characteristic vectors into hierarchies through a process of zigzagging between the domains, and 5) the design axioms, viz, Independence & Information Axioms. Statistical process control (SE) and other methodologies to improve quality are valid only when they are consistent with the Independence & Information Axioms. This paper presents several criteria that govern the design & manufacture of quality products, To be able to control the quality of products, a design must satisfy the Independence Axiom. Based on this axiom and some theorems, several design criteria are derived & discussed. These criteria provide the bounds for the validity of some of the SPC techniques being used. When there is more than one acceptable design of a product or process, the Information Axiom must be used to select the best design(s).
Date issued
1995-06
URI
http://hdl.handle.net/1721.1/25610
Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Publisher
Institute of Electrical and Electronic Engineers
Citation
IEEE Transactions on Reliability, Volume 44, Number 20 (June 1995) pp. 256 -264. (Invited Paper)
Keywords
Axiomatic design, Robust design, Statistical process control

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