An intelligent hybrid system for customer requirements analysis and product attribute targets determination

Fung, Richard Y. K.; Popplewell, Keith; Xie, J.

doi:10.1080/002075498193912

Cited by 170 publications

(84 citation statements)

References 7 publications

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“…А Ustinovičius и oniewski в своей работе показали, что МАИ среди прочих аксиоматических, эвристиче-ских и группы методов вербального анализа реше-ний (ВАР) является оптимальным инструментом для попарного сравнения и численного ранжиро-вания альтернатив [12]. В 1998 г. Фанг и другие дополнили СФК методом «неточной логики» для выбора в случае неточных измерений (какого-то диапазона значений) самых оптимальных показа-телей ГИ [13]. Это первые попытки превращения СФК в новую методику.…”

Section: обзор методов и инструментовunclassified

Basic Approach to Identification of Critical Technologies: Estimation of the Most Important Engineering Attributes of a Product

Romanov¹,

Shpotya²

2016

Rocket-Space Device Engineering and Information Systems

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Аннотация. Обосновывается необходимость идентификации критических технологий. Определение важнейших инженерных характеристик изделия с помощью использования проектного подхода, жизненных циклов изделия (ЖЦИ) и инструмен-тов системной инженерии рассматривается как первый важный шаг перед идентификацией критических технологий. В рамках базового инструмента предлагается использовать традиционный подход «Структурирование функции качества» (СФК), состоя-щий из четырех фаз (так называемых «Домов качества»). Исследование авторов показало, что идентификация критических технологий возможна в ходе второй фазы СФК. Чтобы выполнить вторую фазу, необходимо сначала выполнить первую, у ко-торой в свою очередь есть существенные организационно-методические недостатки. Преодоление этих недостатков позволило авторам статьи предложить инженерную методику под названием «Усовершенствованное СФК» (далее УСФК). Демонстрация функций УСФК по разработке требований заказчика, численному фиксированию корреляций инженерных характеристик и ис-пользованию оценок корреляций в ходе финального ранжирования инженерных характеристик по правилам СФК производится на примере разработки первой стадии ЖЦИ «Замысел» малого космического аппарата (МКА) «Маяк». В итоге ранжирование по УСФК дало отличные от СФК результаты. Анализ результатов СФК и УСФК и их сравнение с реальным ходом разработки МКА «Маяк» подтвердили правильность результатов, полученных по УСФК, и неточность СФК. Abstract. This article justifies the importance of identification of critical technologies. Estimation of the most important engineering attributes using the project management approach, product lifecycles (PLC) and system engineering tools is considered to be the first important step before identification of critical technologies. Conventional system engineering instrument Quality Function Deployment (QFD) is emphasized as a basic tool. QFD consists of four phases (so called "Houses of quality"). The authors' research showed that identification of critical technologies is possible during the second phase of QFD. The second phase must be initiated once the first phase is completed. The first phase possesses organizational and methodological disadvantages. Overcoming these disadvantages allowed the authors to propose an engineering technique named "Improved QFD" (IQFD). The authors describe the development process of the first PLC stage "concept development" of "Mayak" nanosatellite as a demonstration of IQFD functions: development of customer requirements, numeric fixing of correlations among engineering attributes in the House of Quality, utilization of determined weights of correlations during the final QFD ranking of each technical attribute. The IQFD ranking results are different from the QFD results. The analysis of the QFD and IQFD results and their comparison with an actual workflow of "Mayak" nanosatellite engineering verified and validated the correctness of the IQFD results and the inaccuracy of the QFD results.

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Section: обзор методов и инструментовunclassified

Basic Approach to Identification of Critical Technologies: Estimation of the Most Important Engineering Attributes of a Product

Romanov¹,

Shpotya²

2016

Rocket-Space Device Engineering and Information Systems

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“…In a study by Fung et al [87], the authors proposed a novel approach for analyzing customers attributes and projecting them into the relevant design, engineering and product attributes in order to facilitate decision-making and to guide downstream manufacturing planning and control activities. The proposed hybrid system incorporates the principles of QFD, AHP and fuzzy set theory to tackle the complex and often imprecise problem domain encountered in customer requirement management.…”

Section: Qfd In Manufacturing Industriesmentioning

confidence: 99%

“…The proposed hybrid system incorporates the principles of QFD, AHP and fuzzy set theory to tackle the complex and often imprecise problem domain encountered in customer requirement management. The documentation above, which consider combined fuzzy and entropy method (Chan), fuzzy sets (Lin), fuzzy multi-criteria decision making (Wang), fuzzy optimal target setting (Vanegas and Labib), fuzzy interference technique [85], combined QFD and lifecycle analysis (Bovea and Wang) and fuzzy AHP [87] omit some important elements. There appears to be omission of cost elements also, which is critical in driving customer satisfaction modelling.…”

Section: Fuzzy Qfdmentioning

confidence: 99%

Manufacturing Quality Function Deployment: Literature Review and Future Trends

Oke

2013

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Abstract.A comprehensive review of the Quality Function Deployment (QFD) literature is made using extensive survey as a methodology. The most important results of the study are: (i) QFD modelling and applications are one-sided; prioritisation of technical attributes only maximise customer satisfaction without considering cost incurred (ii) we are still missing considerable knowledge about neural networks for predicting improvement measures in customer satisfaction (iii) further exploration of the subsequent phases (process planning and production planning) of QFD is needed (iv) more decision support systems are needed to automate QFD (v) feedbacks from customers are not accounted for in current studies.Keywords: QFD, literature review, house of quality, voice of the customer, customer satisfaction, improvement.

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“…Kalargeros and Gao (1998) further proposed a fuzzy analytic hierarchy process (FAHP) to evaluate the importance weightings of customer attributes. Fung et al (1998) combined the concepts of AHP and fuzzy logic to determine target values for product characteristics. Moreover, Dawson and Askin (1999) introduced a nonlinear mathematical program for determining optimal engineering characteristics under the concern of costs and life-cycle time constraints.…”

Section: Qfd Applications In Product Optimization Literature Reviewmentioning

confidence: 99%

Optimization Of The Product Design Through Quality Function Deployment And Analytical Hierarchy Process: A Case Study Of A Ceramic Washbasin

Erkarslan¹,

YILMAZ²

2011

METU JFA

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An intelligent hybrid system for customer requirements analysis and product attribute targets determination

Cited by 170 publications

References 7 publications

Basic Approach to Identification of Critical Technologies: Estimation of the Most Important Engineering Attributes of a Product

Basic Approach to Identification of Critical Technologies: Estimation of the Most Important Engineering Attributes of a Product

Manufacturing Quality Function Deployment: Literature Review and Future Trends

Optimization Of The Product Design Through Quality Function Deployment And Analytical Hierarchy Process: A Case Study Of A Ceramic Washbasin

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