Hybrid Kansei engineering system and design support

Matsubara, Yukihiro; Nagamachi, Mitsuo

doi:10.1016/s0169-8141(96)00005-4

Cited by 137 publications

(51 citation statements)

References 3 publications

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“…Especially noteworthy in this context is the emergence and development of Kansei Engineering in Japan in the 1970s, which clearly identifies the need to include and indeed design the emotional dimension in engineering (Nagamachi 1995). Most of the existing Kansei tools, however, focus on deriving insights from triangulating external or systemic factors to, for example, lever decision support (Matsubara and Nagamachi 1997). We believe that the key to unlocking the individual, situation-dependent response of a human and the resulting effect on the situational user experience, with all its consequences, lies in measuring emotion reactivity, as determined from the physiological responses of the human body.…”

Section: The Need To Measure Emotions-a Call For Affective Engineeringmentioning

confidence: 99%

Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices

Balters

Steinert

2015

J Intell Manuf

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Section: The Need To Measure Emotions-a Call For Affective Engineeringmentioning

confidence: 99%

Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices

Balters

Steinert

2015

J Intell Manuf

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“…Actually, the concept of Kansei Engineering refers to many phases of product design processes. Therefore, Kansei Engineering system functions as the interface between the product designer and the product consumers [5].…”

Section: Kansei Engineeringmentioning

confidence: 99%

“…The system then infers the candidate design through the forward inference engine referring to the knowledge base and image database. Finally, the system outputs and displays the candidate design through the picture drawing module referring to the design database and graphic database [5]. The forward Kansei Engineering system (KES) is able to help the consumer's decision in choosing a product [7,8].…”

Section: Computer-aided Kansei Engineering Systemmentioning

confidence: 99%

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Review of research and development of computer-aided Kansei Engineering

Xue

2009

Front. Mech. Eng. China

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Kansei Engineering is an important research approach and has become the hotspot of research in design fields. The concept of Kansei Engineering is introduced based on the investigation of related literatures. The working process and the key technology of computeraided Kansei Engineering systems are discussed. Finally, the development trend of Kansei Engineering is outlined according to the development of computer and networking technology.

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“…Ishihara et al (1995) apply neural network techniques to enhance the inference between Kansei words and design elements in Kansei design systems. Matsubara and Nagamachi (1997) propose to develop hybrid expert systems for Kansei design support.…”

Section: Related Workmentioning

confidence: 99%

Analytical affective design with ambient intelligence for mass customization and personalization

Jiao

et al. 2007

Int J Flex Manuf Syst

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The fulfillment of individual customer affective needs may award the producer extra premium in gaining a competitive edge. This entails a number of technical challenges to be addressed, such as the elicitation, evaluation, and fulfillment of affective needs, as well as the evaluation of affordability of producers to launch the planned products. Mass customization and personalization have been recognized as an effective means to enhance front-end customer satisfaction while maintaining backend production efficiency. This paper proposes an affective design framework to facilitate decision-making in designing customized product ecosystems. In particular, ambient intelligence techniques are applied to elicit affective customer needs. An analytical model is proposed to support affective design analysis. Utility measure and conjoint analysis are employed to quantify affective satisfaction, while the producer affordability is evaluated using an affordability index. Association rule mining techniques are applied to model the mapping of affective needs to design elements. Configuration design of product ecosystems is optimized with a heuristic genetic algorithm. A case study of Volvo truck cab design is reported with a focus on the customization of affective features. It is demonstrated that the analytical affective design framework can effectively manage the elicitation, analysis, and fulfillment of affective customer needs. Meanwhile, it can account for the manufacturer's capabilities, which is vital for ensuring a profit margin in the mass customization and personalization endeavor.

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Hybrid Kansei engineering system and design support

Cited by 137 publications

References 3 publications

Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices

Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices

Review of research and development of computer-aided Kansei Engineering

Analytical affective design with ambient intelligence for mass customization and personalization

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