NDLI: A decision model for setting target levels in quality function deployment using nonlinear programming-based fuzzy regression and optimization

Content Provider	Springer Nature Link
Author	Sener, Zeynep Karsak, E. Ertugrul
Copyright Year	2009
Abstract	Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products and services to increase customer satisfaction. The inherent fuzziness of functional relationships between customer requirements and engineering characteristics, and among engineering characteristics in QFD modeling justifies the use of fuzzy regression. However, when linear programming is used in fuzzy regression, spread values of regression coefficients tend to approach zero. In order to overcome this problem, this paper employs a nonlinear-programming-based fuzzy regression approach to model functional relationships in product planning. Then, a fuzzy mathematical programming model is developed to determine target levels of engineering characteristics using the functional relationships obtained from fuzzy regression. Fuzzy mathematical programming model enables to account for the spread values as well as the center values of the parameter estimates of the functional relationships. A washing machine quality improvement problem is presented to illustrate the application of the proposed approach.
Starting Page	1173
Ending Page	1184
Page Count	12
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	48
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-10-11
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Quality function deployment Fuzzy regression House of quality Fuzzy optimization Computer-Aided Engineering (CAD, CAE) and Design Mechanical Engineering Production/Logistics Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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