• Title/Summary/Keyword: Quality function deployment(QFD)

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A Study on Method for Realization of Cost-based Quality Function Deployment(QFCD) (비용을 고려한 품질기능전개 구현방법에 관한 연구)

  • Choi, Yong-Jung;Lee, Phil-Jae;Han, Woo-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.4
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    • pp.221-228
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    • 2007
  • Qualify Function Deployment(QFD) is a technique which was born in Japan as a strategy for assuring that quality is built into new products. QFD was first used in 1972 by Kobe Shipyard of Mitsubish Heavy Industrials Ltd. and was then referred to as the quality tables. After QFD is proposed, it has been applied by both many large and small companies around the world. Many studies related QFD are performed till now but study related "cost-based QFD(QFCD)" hasn't been performed actively. If cost-based QFD is not performed. the produced results will be included possibility that is not significant as well as realistic. Therefore, the purpose of this study is to improve effectiveness and efficiency for product development's result through QFD by introducing QFCD's concept and execution procedure.

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A Study on the development quality control by application of QFD and Stage-gate in defense system (QFD 및 Stage-gate 모델을 활용한 국방분야 개발단계 품질관리 방안 연구)

  • Jang, Bong Ki
    • Journal of Korean Society for Quality Management
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    • v.42 no.3
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    • pp.279-290
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    • 2014
  • Purpose: The purpose of this study is to propose adoption of QFD and Stage-gate in order to analyze the quality of korea defense system. Methods: Drawing change data of initial production phase in korea defense system were anlayzed and a practical method was proposed. Results: The results of this study are as follows; Off line Quality Control should be introduced in development phase. Specially, in case of defense system, the best method is QFD(Quality Function Deployment) and Stage-gate process. At first, QFD 1 step defines product planning from VOC(Voice Of Customer), QFD 2 step specifies part planning from product planning, QFD 3 step defines process planning from part planning, QFD 4 step defines production planning from previous process planning. Secondly, Stage-gate process is adopted. This study is proposed 5 stage-gate in case of korea defense development. Gate 1 is located after SFR(System Function Review), Gate 2 is located after PDR(Preliminary Design Review), Gate 3 is located after CDR(Critical Design Review), Gate 4 is located after TRR(Test Readiness Review) and Gate 5 is located before specification documentation submission. Conclusion: Off line QC(Quality Control) in development phase is necessary prior to on line QC(Quality Control) in p roduction phase. For the purpose of off line quality control, QFD(Quality Function Deployment) and Stage-gate process can be adopted.

System Requirement Analysis of Guided Missile using Quality Function Deployment(QFD) and Analytic Hierarchy Process(AHP) (Quality Function Deployment(QFD)와 Analytic Hierarchy Process(AHP)를 이용한 유도무기의 시스템 요구도 분석)

  • Noh, Kyung-Ho;Hwang, Sung-Hwan;Lee, Ki-Seung;Kang, Dong-Seok;Kim, Ji-Eok
    • Journal of the Korean Society of Systems Engineering
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    • v.5 no.1
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    • pp.67-72
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    • 2009
  • User Requirements are analyzed and quantified by decision making models and system engineering methods to select alternative concepts which satisfy the various requirements. In this study, the design concepts for guided missile are derived using Quality Function Deployment(QFD) and Analytic Hierarchy Process(AHP). The design alternatives that satisfy the user requirements are extracted by QFD and Morphological Matrix, then the best design concept are obtained using AHP and Pugh concept Selection.

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Quality Function deployment:Methods and modeling issues

  • 김광재
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1997.10a
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    • pp.189-192
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    • 1997
  • New product development is a complex managerial process which involves multiple functional groups, each with a different perspective. Quality function deployment (QFD) is a new product development process which stresses cross-functional integration. QFD provides a specific approach for ensuring quality through each stage of the product development and production process. This paper provides an overview of QFD including its concepts and methods, and then proposes an integrated approach to formulating and solving the QFD process. This paper also discusses issues associated with the prescriptive modeling of QFD.

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A Study on the QFD Model for Information Systems Outsourcing (정보시스템 아웃소싱을 위한 QFD모형에 관한 연구)

  • 우태희;임충묵
    • Journal of the Korea Safety Management & Science
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    • v.6 no.1
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    • pp.147-155
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    • 2004
  • The goal of this paper is to offer a quantitative decision model using Quality Function Deployment(QFD). We consider the factors outsourcing that affect the benefits of the organization and the fifth alternatives that were selected to be considered for outsourcing as customer requirements and technical attributes in QFD. For selecting the outsourcing system, we compute the priority considering interdependencies among alternatives. Thus this paper propose a decision model, which uses the quality function deployment to help practitioners set priority and users in structuring the outsourcing problems.

A Study on Application to Quality Function Deployment for Environment Evaluation (환경 평가를 위한 QFD 시스템 적용에 관한 연구)

  • Yang, Kwang-Mo;Choi, Seung-Hee;Park, Jae-Hyun;Song, Soo-Jung
    • Proceedings of the Safety Management and Science Conference
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    • 2005.11a
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    • pp.276-280
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    • 2005
  • Industrial processes and operations can not be accomplished independently but are connected with each others through suppliers and customer, and these ideas are fundamental notions of Life Cycle Assessment(LCA). This paper will introduce Life Cycle Assessment(LCA) in environment which is rising, and would like to build environmental management system using approach of Quality Function Deployment(QFD) and Safety Function Deployment(SFD) belonging to the assessment method.

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An Application of QFD to the Development of Full Automatic Temperature Controller (QFD를 적용한 전자동 온도조절장치 개발사례 연구)

  • 이기룡;박병춘
    • Journal of Korean Society for Quality Management
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    • v.30 no.1
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    • pp.61-73
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    • 2002
  • The Quality Function Deployment(QFD) is a Quality Management technique to maximize customers' satisfaction by reflecting customer requirements into all business processes, including concept definition, product planning, parts planning, process planning, production planning, and sales planning. The basic concept of the QFD is to translate customers' requirements appropriately into engineering characteristics, into parts characteristics, into process characteristics, and into specific requirements and activities in production. In this study, we reviewed and analyzed the application process of the QFD to the development of A2 FATC (Full Automatic Temperature Controller), an automotive component developed and produced by company A. It has been reported that by applying the QFD to the development of A2 FATC, company A. achieved 34% improvement in control robustness quality characteristic, 27% improvement in deviation quality characteristic, and 30% improvement in overall quality characteristics.

A Hybrid QFD Framework for New Product Development

  • Tsai, Y-C;Chin, K-S;Yang, J-B
    • International Journal of Quality Innovation
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    • v.3 no.2
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    • pp.138-158
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    • 2002
  • Nowadays, new product development (NPD) is one of the most crucial factors for business success. The manufacturing firms cannot afford the resources in the long development cycle and the costly redesigns. Good product planning is crucial to ensure the success of NPD, while the Quality Function deployment (QFD) is an effective tool to help the decision makers to determine appropriate product specifications in the product planning stage. Traditionally, in the QFD, the product specifications are determined by a rather subjective evaluation, which is based on the knowledge and experience of the decision makers. In this paper, the traditional QFD methodology is firstly reviewed. An improved Hybrid Quality Function Deployment (HQFD) [MSOfficel] then presented to tackle the shortcomings of traditional QFD methodologies in determining the engineering characteristics. A structured questionnaire to collect and analyze the customer requirements, a methodology to establish a QFD record base and effective case retrieval, and a model to more objectively determine the target values of engineering characteristics are also described.

Applying Quality Function Deployment in the Apparel Industry

  • Diane M. Scheurell;Ph. D.
    • The International Journal of Costume Culture
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    • v.2 no.2
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    • pp.14-30
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    • 1999
  • Quality Function Deployment (QFD) is a product development tool used to ensure that the voice of the customer is heard and translated into products. This paper shows the applicability and usefulness of this product development tool in the apparel industry by developing an apparel example and taking it through the four matrices that encompass a QFD process.

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A Genetic Algorithm for Solving a QFD(Quality Function Deployment) Optimization Problem

  • Yoo, Jaewook
    • International Journal of Contents
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    • v.16 no.4
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    • pp.26-38
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    • 2020
  • Determining the optimal levels of the technical attributes (TAs) of a product to achieve a high level of customer satisfaction is the main activity in the planning process for quality function deployment (QFD). In real applications, the number of customer requirements for developing a single product is quite large, and the number of converted TAs is also high so the size of the house of quality (HoQ) becomes huge. Furthermore, the TA levels are often discrete instead of continuous and the product market can be divided into several market segments corresponding to the number of HoQ, which also unacceptably increases the size of the QFD optimization problem and the time spent on making decisions. This paper proposed a genetic algorithm (GA) solution approach to finding the optimum set of TAs in QFD in the above situation. A numerical example is provided for illustrating the proposed approach. To assess the computational performance of the GA, tests were performed on problems of various sizes using a fractional factorial design.