A new mixed integer linear programming model for product development using quality function deployment
Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product deve...
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Veröffentlicht in: | Computers & industrial engineering 2009-10, Vol.57 (3), p.906-912 |
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description | Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product development, determining the fulfillment levels of design requirements (DRs) is crucial during QFD optimization. However, in real world applications, the values of DRs are often discrete instead of continuous. To the best of our knowledge, there is no mixed integer linear programming (MILP) model in which the discrete DRs values are considered. Therefore, in this paper, a new QFD optimization approach combining MILP model and Kano model is suggested to acquire the optimized solution from a limited number of alternative DRs, the values of which can be discrete. The proposed model can be used not only to optimize the product development but also in other applications of QFD such as quality management, planning, design, engineering and decision-making, on the condition that DR values are discrete. Additionally, the problem of lack of solutions in integer and linear programming in the QFD optimization is overcome. Finally, the model is illustrated through an example. |
doi_str_mv | 10.1016/j.cie.2009.03.005 |
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Additionally, the problem of lack of solutions in integer and linear programming in the QFD optimization is overcome. Finally, the model is illustrated through an example.</description><subject>Customer satisfaction</subject><subject>Decision making</subject><subject>Integer programming</subject><subject>Kano model</subject><subject>Linear programming</subject><subject>Mixed integer linear programming</subject><subject>Optimization</subject><subject>Optimization techniques</subject><subject>Product development</subject><subject>Quality function deployment</subject><subject>Studies</subject><issn>0360-8352</issn><issn>1879-0550</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EEuXxA7hZHLglrOM4jsUJIV5SJS5wtlJnU7lK7NZOgP573JYTB04rjb7ZnR1CrhjkDFh1u8qNxbwAUDnwHEAckRmrpcpACDgmM-AVZDUXxSk5i3EFAKVQbEa6e-rwiw72G1tq3YhLDLS3DptA18EvQzMM1i3p4Fvsaef3ajuZkbb4ib1fD-hGOsUds5ma3o5b2k3OjNa7hKx7v90RF-Ska_qIl7_znHw8Pb4_vGTzt-fXh_t5ZrgQY1YsRMkEVMZUSWC8q0oJjEvgUC9AiVZ2nVKqYiVwLhaSNRKxVFgoJsu6lvyc3Bz2ppSbCeOoBxsN9n3j0E9R81IqpgqVwOs_4MpPwaVsukgHS1XsIXaATPAxBuz0OtihCVvNQO9q1yudate72jVwnWpPnruDB9ObnxaDjglxBlsb0Iy69fYf9w8AtopC</recordid><startdate>20091001</startdate><enddate>20091001</enddate><creator>Delice, Elif Kılıç</creator><creator>Güngör, Zülal</creator><general>Elsevier Ltd</general><general>Pergamon Press Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20091001</creationdate><title>A new mixed integer linear programming model for product development using quality function deployment</title><author>Delice, Elif Kılıç ; Güngör, Zülal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c355t-2b541506cc6c3513f64701370308b095d7ff9996140335b71a7ee49e291748873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Customer satisfaction</topic><topic>Decision making</topic><topic>Integer programming</topic><topic>Kano model</topic><topic>Linear programming</topic><topic>Mixed integer linear programming</topic><topic>Optimization</topic><topic>Optimization techniques</topic><topic>Product development</topic><topic>Quality function deployment</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Delice, Elif Kılıç</creatorcontrib><creatorcontrib>Güngör, Zülal</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & industrial engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Delice, Elif Kılıç</au><au>Güngör, Zülal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new mixed integer linear programming model for product development using quality function deployment</atitle><jtitle>Computers & industrial engineering</jtitle><date>2009-10-01</date><risdate>2009</risdate><volume>57</volume><issue>3</issue><spage>906</spage><epage>912</epage><pages>906-912</pages><issn>0360-8352</issn><eissn>1879-0550</eissn><coden>CINDDL</coden><abstract>Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product development, determining the fulfillment levels of design requirements (DRs) is crucial during QFD optimization. However, in real world applications, the values of DRs are often discrete instead of continuous. To the best of our knowledge, there is no mixed integer linear programming (MILP) model in which the discrete DRs values are considered. Therefore, in this paper, a new QFD optimization approach combining MILP model and Kano model is suggested to acquire the optimized solution from a limited number of alternative DRs, the values of which can be discrete. The proposed model can be used not only to optimize the product development but also in other applications of QFD such as quality management, planning, design, engineering and decision-making, on the condition that DR values are discrete. 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subjects | Customer satisfaction Decision making Integer programming Kano model Linear programming Mixed integer linear programming Optimization Optimization techniques Product development Quality function deployment Studies |
title | A new mixed integer linear programming model for product development using quality function deployment |
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