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    A Simplified Systematic Method of Acquiring Design Specifications From Customer Requirements

    Source: Journal of Computing and Information Science in Engineering:;2009:;volume( 009 ):;issue: 003::page 31004
    Author:
    Nuogang Sun
    ,
    Xuesong Mei
    ,
    Youyun Zhang
    DOI: 10.1115/1.3184600
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Faithfully obtaining design specifications from customer requirements is essential for successful designs. The natural lingual, inexact, incomplete, and vague attributes of customer requirements make it very difficult to map customer requirements to design specifications. In general design process, the design specifications are determined by designers based on their experience and intuition, and often a certain target value is set for a specification. However, it is on one hand very difficult, on the other hand unreasonable, so a suitable limit range rather than a certain value is preferred at the beginning of design, especially at the concept design process. In this paper, a simplified systematic approach of transforming customer requirements to design specifications is proposed. First, a two-stepped clustering approach for grouping customer requirements and design specifications based on the house of quality matrix is presented, by which the mapping is limited to within each group. To further simplify the inference mapping rules of customer requirements and design specifications, the minimal condition inference mapping rules for each design specification are extracted based on rough set theory. In the end, a suitable value range is determined for a specification by applying the fuzzy rule matrix.
    keyword(s): Design , Surface roughness AND Fuzzy reasoning ,
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      A Simplified Systematic Method of Acquiring Design Specifications From Customer Requirements

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    http://yetl.yabesh.ir/yetl1/handle/yetl/140120
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    contributor authorNuogang Sun
    contributor authorXuesong Mei
    contributor authorYouyun Zhang
    date accessioned2017-05-09T00:32:01Z
    date available2017-05-09T00:32:01Z
    date copyrightSeptember, 2009
    date issued2009
    identifier issn1530-9827
    identifier otherJCISB6-26005#031004_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/140120
    description abstractFaithfully obtaining design specifications from customer requirements is essential for successful designs. The natural lingual, inexact, incomplete, and vague attributes of customer requirements make it very difficult to map customer requirements to design specifications. In general design process, the design specifications are determined by designers based on their experience and intuition, and often a certain target value is set for a specification. However, it is on one hand very difficult, on the other hand unreasonable, so a suitable limit range rather than a certain value is preferred at the beginning of design, especially at the concept design process. In this paper, a simplified systematic approach of transforming customer requirements to design specifications is proposed. First, a two-stepped clustering approach for grouping customer requirements and design specifications based on the house of quality matrix is presented, by which the mapping is limited to within each group. To further simplify the inference mapping rules of customer requirements and design specifications, the minimal condition inference mapping rules for each design specification are extracted based on rough set theory. In the end, a suitable value range is determined for a specification by applying the fuzzy rule matrix.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Simplified Systematic Method of Acquiring Design Specifications From Customer Requirements
    typeJournal Paper
    journal volume9
    journal issue3
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.3184600
    journal fristpage31004
    identifier eissn1530-9827
    keywordsDesign
    keywordsSurface roughness AND Fuzzy reasoning
    treeJournal of Computing and Information Science in Engineering:;2009:;volume( 009 ):;issue: 003
    contenttypeFulltext
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