Kansei/affective engineering [electronic resource] / edited by Mitsuo Nagamachi.
Nagamachi, Mitsuo, 1936-
2010
TS170 .N34 2010eb
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Title Kansei/affective engineering [electronic resource] / edited by Mitsuo Nagamachi.
Author Nagamachi, Mitsuo, 1936-
ISBN 9781439821343 (electronic bk.)
9781439821336 (pbk.)
Publication Details Boca Raton, FL : CRC Press, 2010.
Language English
Description 1 online resource (xiii, 309 p.) : ill.
Call Number TS170 .N34 2010eb
Dewey Decimal Classification 658.5/75
Summary Providing a guided tour through the each stage of process, this book explores how to apply Kansei/Affective Engineering. This book describes the psychological survey and psycho-physiological measurement of consumer feelings and the multivariate statistical analysis of this survey data, including rough set models. Since soft computing technology is very useful from the viewpoint of product design, the author details the Expert system, neural networks, GA, and other methods that are relevant to support the designer's decision or the customer's choice.
Note Description based on print version record.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Series Industrial innovation series ; Kansei engineering
Available in Other Form Kansei/affective engineering.
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Chapter 1. Kansei/Affective Engineering and History of Kansei/Affective Engineering in the World
Chapter 2. Methods of Kansei/Affective Engineeringand Specific Cases of Kansei Products
Chapter 3. Psychological Methods of Kansei Engineering
Chapter 4. Psychophysiological Methods
Chapter 5. Statistical Analysis for Kansei/Affective Engineering
Chapter 6. Soft Computing System for Kansei/Affective Engineering
Chapter 7. Rough Set Theory and Kansei/Affective Engineering
Chapter 8. Kansei/Affective Engineering and Web Design
Chapter 9. Kansei/Affective Engineering for the European Fast-Moving Consumer Goods Industry
Chapter 10. Kansei/Affective Engineering Applied to Triggers in Powered Hand Tools
Chapter 11. Kansei, Quality, and Quality Function Deployment.

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