Optimal new product design using quality function deployment with empirical value functions

Dawson, Donald W.; Askin, Ronald G.

doi:10.1002/(sici)1099-1638(199901/02)15:1<17::aid-qre203>3.0.co;2-j

Cited by 65 publications

(23 citation statements)

References 5 publications

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“…The customer requirements A variety of forms R 12 Well fit the whole shape on function keys R 13 Good color combination R 14 Good quality of color screen R 2 Cluster II: ergonomic aspects R 21 Comfortable feeling on touch R 22 Easy to hold and push buttons R 23 Easy to take and store R 24 Easy to set up and use R 25 Avoidable of carelessly turn off buttons…”

Section: Identification Of Customer Requirementsmentioning

confidence: 99%

“…Fung et al [12] combined the concepts of AHP and fuzzy logic to determine target values for product characteristics. Moreover, Dawson and Askin [13] introduced a nonlinear mathematical program for determining optimal engineering characteristics under the concern of costs and life-cycle time constraints. Finally, Vanegas and Labib [14] developed a fuzzy quality function deployment model to determine the target values of design characteristics.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Using AHP and TOPSIS approaches in customer-driven product design process

Lin

Wang

Chen

et al. 2008

Computers in Industry

379

147

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Section: Identification Of Customer Requirementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Using AHP and TOPSIS approaches in customer-driven product design process

Lin

Wang

Chen

et al. 2008

Computers in Industry

379

147

View full text Add to dashboard Cite

“…In order to address the fuzziness of the modelling, quite a few previous studies have adopted the fuzzy set theory on modelling the relationships between CNs and ECs (Thurston and Carnahan 1992;Fung, Popplewell, and Xie 1998;Park and Kim 1998;Verma, Chilakapati, and Fabrycky 1998;Wang 2001). As an alternative, a stepwise regression analysis method has been utilised to produce second-order polynomials to model the functional relationships between CNs and ECs in QFD (Dawson and Askin 1999).…”

Section: Tools and Methods To Support Concept Selectionmentioning

confidence: 99%

Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

Eres

Bertoni

Kossmann

et al. 2014

Journal of Engineering Design

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Designing complex engineering systems, such as an aircraft or an aero-engine, is immensely challenging. Formal systems engineering practices are widely used in the aerospace industry throughout the overall design process to minimise the overall design effort, corrective re-work, and ultimately overall development and manufacturing costs. Incorporating the needs and requirements from customers and other stakeholders into the conceptual and early design process is vital for the success and viability of any development programme. This paper presents a formal methodology, the value-driven design (VDD) methodology that has been developed for collaborative and iterative use in the extended enterprise (EE) within the aerospace industry, and that has been applied using the concept design analysis (CODA) method to map captured customer needs into engineering characteristics and to model an overall 'design merit' metric to be used in design assessments, sensitivity analyses, and engineering design optimisation studies. Two different case studies with increasing complexity are presented to elucidate the application areas of the CODA method in the context of the VDD methodology for the EE within the aerospace sector.

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“…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. Finally, Vanegas and Labib (2001) developed a fuzzy quality function deployment model to determine the target values of design characteristics (Lin et al, 2008).…”

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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Optimal new product design using quality function deployment with empirical value functions

Cited by 65 publications

References 5 publications

Using AHP and TOPSIS approaches in customer-driven product design process

Using AHP and TOPSIS approaches in customer-driven product design process

Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design

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

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