20 - Affective meaning: The Kansei Engineering approach

When people are asked to described certain textiles, they frequently refer to the expressions of its properties such as attractiveness, uniqueness, shininess, robustness, comfortability, and so on. It shows how senses play important role in it. Human employs their senses when interacting with textiles, most notably visual and tactile/ haptic to absorb its expressive properties. Yet, our sensorial experiences may amplify when interacting with those of traditional textiles, such as batik, as we can entice sensations when seeing its motifs and patterns, smelling its materials, and touching its surfaces. The multi-sensorial importance of seeing, smelling, and touching in the interaction with and experience of textiles suggests that one should address senses in a systematic way when evaluating users' perception on traditional textiles. To address this issue, the paper proposes the incorporation of Kansei Engineering (KE) approach for identifying multi-sensorial experiences on the expressive properties of traditional textiles, using batik as a case of study. KE approach address person's psychological understanding when observing things in order to analyze and study the inherent relationship between person's perceptual knowledge and objects evaluated. This paper outlines the use of KE approach in correlating sensorial perceptions when experience with traditional textiles and ultimately expose users' preferences toward them. Background of KE approach on textiles will be explored and its application for the multi-sensorial investigation of traditional textiles will be discussed.

Android-based devices have become devices for every student in communication activities and learning media, therefore the Introduction to Linguistics course requires learning media, so the alternative is to use an Android-based application. The purpose of this study was to analyze the emotional factor in designing the interface for Android-based Introductory Linguistics teaching materials with the Kansei Engineering approach; make recommendations for the interface design of Android-based Introduction to Linguistics teaching materials. The method used is Kansei Engineering Type I (KEPack). The application of Kansei Engineering in the design of the Android-based Learning Application interface produces interface design elements in designing Android-based Learning Applications consisting of 7 major parts, namely Page Body, Header, Top Menu, Left Menu, Main Menu, Right Menu and Footer. To detect users of research android-based learning applications using 18 Kansei Word Specimens consisting of 4 applications, participants were taken with the slovin approach which collected 190 students from 360 students, the process of analyzing the elements needed in designing the application interface design with the Kansei Engineering approach, using the Kansei Engineering method. multivariate calculations. The methods are Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) and Partial Least Square (PLS). Display design sourced from all participants, which will be used for public display, for Introductory Linguistics Learning, namely the concept of "Colorfull" emotion.

This study used two product development methods: Kansei and value engineering. Kansei engineering was used to identify and translate consumer psychological impressions or feelings in the form of Kansei words to the design parameters, while value engineering was used to analyze the functional properties by considering cost, reliability, and performance. The consumers determined the priority attributes of analog rice products, namely a good taste, a fluffy and soft texture, as well as a bright color. Three alternative variations of the product development concept were formulated based on these priorities. The concept with the highest value was then concluded as an analog rice produced from 90% Sago flour and 10% MOCAF (Modified Cassava Flour) with a value of 1,131.

As the global population ages, there is a growing need for technologies that not only assist older adults in their daily lives but also enhance their emotional well-being and social engagement. While assistive robots have been widely developed for functional support, their ability to foster meaningful human-robot interactions remains limited. This study explores how Kansei Engineering for Older Adults, a design methodology focused on emotional experience of older adults, can improve the way older adults engage with AI-enabled robotic companions. Through ethnographic research and interaction studies, we examine how four AI-powered robots, designed with Kansei Engineering principles—including facial expressions, voice modulation, and haptic feedback—affect social engagement and emotional connection in older adults. We measure engagement through interaction frequency, duration, and qualitative user feedback, providing insight into how emotional responsiveness in robots influences trust, companionship, and long-term acceptance. Preliminary findings suggest that older adults respond more positively to robots that express emotions naturally and adapt their interactions based on user feedback. Participants reported feeling more connected and engaged, highlighting the potential for emotionally intelligent robotics to reduce loneliness and improve quality of life. This study contributes to the growing field of human-centered AI and gerontechnology, offering a framework for designing emotionally aware robotic systems that foster social and psychological well-being in aging populations. As technology continues to evolve, integrating Kansei-driven AI interactions may shape the future of companion robotics, caregiving technology, and digital social engagement for older adults.

Oolong tea is one of the tea commodities that has a distinctive taste and high global market potential. However, in Indonesia, the appeal of Oolong tea is still low compared to black tea and green tea. This may be due to the lack of packaging that can represent the character of the product and the emotional preferences of consumers. This study aims to develop a packaging design concept for Oolong tea based on Kansei Engineering by translating aspects of functionality, usability, and pleasure. A total of 30 respondents were involved in this study to conduct interviews and surveys using video stimuli as well as digital and physical packaging. The results of this exploration were analyzed using the TF-IDF method, Hierarchical Agglomerative Clustering, and K-means Algorithm. The TF-IDF analysis yielded 25 Kansei words. These were then grouped using the HAC method into four main concepts: Exclusive, Modern, Practical, and Reusable. Based on the K-means Algorithm, the Exclusive concept had the highest silhouette value. This indicates consumer preference for packaging with a luxurious and elegant feel. Based on these analysis results, it is evident that the Kansei Engineering approach, supported by statistical methods, can generate more emotional and relevant packaging concepts that can serve as references in the domestic market.

This paper presents a proposal to reconstruct some specific towns which were attacked and destroyed by Huge Tsunami, for example, in Tohoku region of Japan on the 11th of March, 2011. A collaborative approach has been employed to provide some trial proposal to reconstruct such damaged towns by means of Internet Community as follows. (1) Providing a proposal and pictures to reconstruct, especially offering visual design concept of living space for slope topography through social network system as an example of Internet Community; (2) consulting and discussing the above proposal and pictures among specific Internet Community with analysis by Kansei engineering; and (3) improving an original proposal into more efficient and flexible one. Suitable methods for adjustment are sometimes necessary to avoid occurrence of conflicts from many requests. Kansei Engineering may consolidate several kinds of requests, translate their expressions into set of numerical values(namely vectorize) and reduce conflicts of request into stable adjustment (namely, "not drastic" reformation). The paper explains in detail the above approach for practical collaboration for design of Living Space for Slope Topography and adjustment scheme by means of Kansei engineering approach. It also mentions some senario to brush up the proposal by means of the above collaborative approach and some problems to be resolved to make it more fruitful.

A satisfactory cross-border logistics service (CBLS) can help promote business activities in cross-border e-commerce. Kansei engineering (KE) is an approach to design the elements which satisfy customers' affective and emotional perceptions into services and products. In this study, the KE approach is applied to derive ideas for the development of CBLS. For this purpose, Partial Least Squares (PLS) is used to analyze the relationships between the feelings of customers and service elements of CBLS. Moreover, this study demonstrates the applications of text mining techniques to analyze the online contents regarding CBLS. Online content mining assists in identifying the service elements and Kansei words for CBLS. Importantly, the relationship between the feelings of customers and service elements of CBLS obtained by online content mining provides complementary results for CBLS design.

This paper reports a kansei engineering study of vehicle front mask design conducted in Japan, UK, and US. The objective is to compare three different countries in terms of kansei meaning and kansei construction as well. The subjects in three countries evaluated 24 passenger-car front masks on the 5-point SD scale. The 24 front mask pictures were presented on computer screen. The experimental results of three groups were analyzed through Factor Analysis and Hayashi's Quantification Theory Type I and compared the similarity and difference in kansei evaluation among subjects from three countries. Three factors are extracted from the set of SD scales in describing vehicle front masks: Factor 1 “Value” with words such as “deluxe“, Factor 2 “Performance” with words such as “sporty”, and Factor 3 “Tradition” with words such as “classic” or “simple“. For feelings associated with the three factors, the overall shape of the whole mask, front grill shape and type, and headlight patterns have the broadest influence. No significant cross-cultural difference was identified in the perception of vehicle front masks.

Toddlers experience physical accidents in the house at a rate of 90 percent. Based on observations, the living room was the most dangerous part of the building compared to other parts. That condition made the parents feel that the safety of their little one was not fully supported. This study aims to design a living room that is safe and comfortable for Toddlers. The design output supports the interior designers in creating a safer Toddler environment. Kansei Engineering guides the identification of living room design for parents looking for their toddlers' safety. The Kansei words gathered from the study are comfortable, multifunction, safe, easy to clean, simple, large capacity, and harmonious. These Kansei words injected into the concept design, which is the harmonious design concept and the simple design concept, by using Principal Component Analysis. The harmonious design has a wood table (X5.1) with a sofa (X7.2) and TV (X9.1) and no flower vase (X11.2) as its decoration, while the simple design has a plastic table (X5.2) with a wood seat (X7.1) and with flower vase (X11.1) but no TV (X9.2). The insights gathered were designed with Blender 3D and integrated with virtual reality Oculus simulation through the SketchFab website.

Traditional reliability model, which is based on fault state logic of product composition units, has inherent limitations, e.g., it can't map the failure caused by cumulative error of performance degradation or parameter drift, and can't associate reliability requirements or product failure time with product design parameters so that little use is got to support testability or PHM function design, etc. In order to overcome these shortcomings, this paper proposesa physics of failure based reliability modeling framework, which is aimed at describing the nature of failure dynamics, of which failure was that the output performance variation driven by mechanisms to go beyond design specifications. This modeling framework includes simulation analysis of the expected dominant failure mechanisms (including device degradation or parameter drift, etc.) by way of classical stress-damage modeling, and study of failure mechanism impact on the product's output with fault injection when the corresponding mechanism taken place. Complete description of the failure dynamics closely links product failure events, design parameters and external conditions together, and it facilitates the reliability and PHM design effort. In this paper, a formal model and its simulation analysis approach were presented, and a case study of an electronic module was also given. This modeling approach is more applicable for digital product design scenario as generally complex simulation calculation is needed in this way.

A dominance-based rough set approach to Kansei Engineering in product development

This paper reopens Kansei Engineering (KE) that Nagamachi has founded and developed since 1970s from the perspective of design management. The frameworks of innovation of meaning and design thinking provide a new description of Nagamachi’s practice that translates unawakened future meanings of consumers’ life into product design. The product designing through KE therefore maximises its performance only when combined with solid design thinking, following the logic of science and utilising technology. In this sense, his hitherto works should actually be called Kansei Design. Furthermore, design thinking that consists of intuitive and analytical thinking also provides an opportunity for considering future application of artificial intelligence (AI) to KE approach. The two types of thinking are bridged by “abductive reasoning” of which development in programming is expected for increasing automated Kansei Design system.

<p><strong>A common problem often encountered in sanitary napkin packaging is inadequate product protection. Failure to open or reseal the packaging and the use of materials that cannot be reused are complaints from 97% of consumers regarding sanitary napkin products currently on the market. This research aims to analyze packaging design elements according to consumer preferences. In this research, the Kansei Engineering and Rough Set methods were used. Kansei Engineering has the advantage of being able to translate consumer emotions into design elements. The design element analysis process is carried out using the Rough Set method. The research results obtained consumer emotions in the form of 19 Kansei words and 29 packaging samples as design references. Analysis of sanitary napkin packaging design elements obtained recommendations in the form of cardboard material, folding cardboard packaging type, no additional features, box body, opening type with flap, medium size, feminine design, script typography, and image elements in the form of pictures and illustrations. This research succeeded in proving Kansei Engineering's ability to produce packaging designs according to consumer preferences through quantitative data analysis<em>.</em></strong></p><p><strong><em>Keywords</em></strong> - <em>Model Kano, Rough Set, Design Element, Packaging</em></p>

Product development becomes more and more complex. Products obtain more and more functions and at the same time they must be still attractive for the customers to ensure a successful product launch. To predict their acceptance and to gain knowledge on how to design attractive products new methods are developed in the field of the emotional design. Such a method is the Kansei Engineering, which collects the customers hidden subjective needs and their translation into concrete products. We present and validate a new form of the Kansei Engineering method for emotional assessment by the customers during the product development, based on an interactive product experience in Virtual Reality. The major novelty of our kind of method is the use of immersive representations which focuses on both, the product itself and its environmental context, too. Customers experience these virtual representations quite dynamically and with this freely describe their emotional influence on them. We come to the conclusion that more reliable emotional customer feedback can be acquired through the implementation of the proposed context paradigm shift. The fusion of product and environmental context enables the simultaneous role of the customer as a subject (actor) and an object (observer) in the virtual world, thus promoting reliable emotional reactions. Despite of some disadvantages, we propose Immersive Kansei Engineering as a reliable method for emotional product assessment by the customer.

Augmented reality (AR) is believed to be the next wave of online learning. New user experiences become possible to afford AR capabilities with the advent of powerful smartphones. Most studies related to the use of augmented reality in education focused on cognition with little consideration given to emotions which is important in learning. Therefore, this research aims to identify salient connections between emotions and design elements of augmented reality-based mobile learning material by applying Kansei Engineering (KE) approach. In this research, mobile augmented reality application related to the human heart was prepared to be used as a case study. Seven specimens of the mobile augmented reality application were evaluated with 55 emotions of Kansei Words (KW). 28 students from one of the public universities performed the evaluation experiment. The gathered data were then analyzed using Factor Analysis and Principal Component Analysis. The results revealed the important pillars of emotions or kansei semantic space emotions for augmented reality-based mobile learning materials. Based on Factor Analysis, it revealed four main pillars; professional-motivated, confused, wandering-thrilled and one additional pillar; trustable. Besides that, this research described design elements of augmented reality-based mobile learning material that might evoke specific emotions based on five identified pillars. Ultimately, this research is an attempt to guide the design with affective elements during preparation of augmented reality learning materials in the future.