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Journal of Intelligent Manufacturing
Erschienen in: Journal of Intelligent Manufacturing 2/2020

15.09.2018

QFD and Fuzzy Kano model based approach for classification of aesthetic attributes of SUV car profile

verfasst von: Shwetank Avikal, Rohit Singh, Rashmi Rashmi

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 2/2020

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Abstract

The aesthetic appearance and features of a product are the most censorious elements for the accomplishment of a product in the industry. An aesthetic is the quality element which adds value to the product design. Product design is a basic need of every manufacturing company in which visual aspects play an important role to enhance the customer satisfaction. Therefore, Quality Function Deployment (QFD) can be considered as an effective tool for translating the customer’s voice into the design of the product and its specifications. The Kano model helps to identify the desires of a product that brings greater satisfaction or dissatisfaction level to the customer. Kano model tells the connection between the product’s attributes and its satisfaction to the customer. For achieving better results, Fuzzy Kano model has been more favorably applied over traditional Kano model. In this work, an approach of Integration of Kano model into QFD has been applied with an aim to examine the customer satisfaction based on aesthetic sentiments. A Sport Utility Vehicle has been selected for the study. The aesthetic attributes have been selected with the help of QFD and their importance and classification have been calculated using both Fuzzy Kano and Traditional Kano model. The result of Fuzzy Kano and Traditional Kano model has also been compared to calculate the effectiveness of the applied approach.
Vorheriger Artikel Resilient manufacturing
Nächster Artikel Condition monitoring and prediction of solution quality during a copper electroplating process

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Metadaten
Titel
QFD and Fuzzy Kano model based approach for classification of aesthetic attributes of SUV car profile
verfasst von
Shwetank Avikal
Rohit Singh
Rashmi Rashmi
Publikationsdatum
15.09.2018
Verlag
Springer US
Erschienen in
Journal of Intelligent Manufacturing / Ausgabe 2/2020
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI
https://doi.org/10.1007/s10845-018-1444-5

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