運用灰關聯分析法建構品質機能展開之決策模式

Constructing a Decision-Making Model for Quality Function Deployment Using Grey Relational Analysis

以設計者的觀點而言，如何定義出產品最能滿足顧客需求的關鍵性設計需求，是設計師開發成功產品的重要影響因素。而品質機能展開正是一項強有力的以顧客為導向的工程技術，能將顧客需求映射為替代性的設計需求。因此，本研究之目標為轉譯顧客的語言為設計者的語言，以增強顧客的滿意度與設計者的效率。 本研究針對目標產品施行完整性的品質機能展開程序。經由建構品質屋相關之一系列矩陣，創造出一個整體性架構以鏈結與映射顧客需求至設計需求；基於顧客需求與設計需求間的關係矩陣，應用灰關聯分析法建立品質機能展開之多屬性決策模式。一種正規化互依法用於處理設計需求間的相關性，這是由於設計需求間的互依性可能導致彼此評分的消長，因此重建關係矩陣作為品質機能展開之多屬性決策模式之決策矩陣，以得到更為精準的分析結果。並以個人數位助理產品作為說明本研究所提方法之案例，評比設計需求重要度，以找出關鍵性的設計需求來進行發展；設計者可依據顧客需求與設計需求之評比結果，設計者可定義設計準則規範與適當設計活動，以開發並改良現有市場中的目標產品。研究結果顯示整合灰色關聯分析法於品質機能展開程序中的決策模式，有助設計者進行有效的設計需求評價及發展產品設計準則，該項決策機制亦能提升產品設計品質。

From a designer's perspective, how to define critical design requirements that satisfy most customer requirements is a significant factor determining the success of the product designed. Quality function deployment is a powerful customer-oriented engineering technology well suited for mapping customer requirements onto design characteristics. Thus, the objective of this study is to translate the customer language into the designer language for enhancing both the satisfaction of customers and the efficiency of designers. This study applied the entire quality function deployment process to the targeted product. A series of matrices was derived to establish an integrated architecture for linking customer needs to design requirements. From the relationship matrix between customer needs and design requirements, a multiple-attribute decision-making model for quality function deployment was constructed using grey relational analysis. A normalized interdependency method was employed to tackle the correlation between design characteristics. This is because interdependency of design characteristics can change their rating scores for each other. Therefore, the relationship matrix was reconstructed as the decision matrix in the multiple-attribute decision-making model of quality function deployment to obtain more precise analysis results. A case study of personal digital assistants was conducted to validate the proposed methodology. The importance of design requirements was rated to determine the critical design requirements to be developed. According to the rating results of customer and design requirements, designers could define design criteria and proper activities to develop and redesign the targeted product in the marketplace. Results show that the decision-making model integrating quality function deployment with grey relational analysis can help designers conduct effective design requirement evaluation and develop product design criteria. The proposed decision-making mechanism can also enhance product design quality and competitiveness.