scholarly journals Kansei Analysis of the Japanese Residential Garden and Development of a Low-Cost Virtual Reality Kansei Engineering System for Gardens

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Tatsuro Matsubara ◽  
Shigekazu Ishihara ◽  
Mitsuo Nagamachi ◽  
Yukihiro Matsubara
Keyword(s):  
Virtual Reality ◽  
Low Cost ◽  
Multiple Correlation Coefficient ◽  
Engineering System ◽  
Type I ◽  
Kansei Engineering ◽  
Quantification Theory ◽  
Garden Design ◽  
Design Elements ◽  
Residential Garden

Residential garden design using Kansei engineering is a challenging problem. Landscaping components, such as rocks, trees, and ponds, are widely diversified and have a large number of possible arrangements. This large number of design alternatives makes conventional analyses, such as linear regression and its variations like Quantification Theory Type I (QT1), inapplicable for analyzing the relationships between design elements and the Kansei evaluation. We applied a partial least squares (PLS) model that effectively deals with a large number of predictor variables. The multiple correlation coefficient of the PLS analysis was much higher than that of the QT1 analysis. The results of the analyses were used to create a low-cost virtual reality Kansei engineering system that permits visualization of garden designs corresponding to selected Kansei words. To render complex garden scenes, we developed an original 3D computation and rendering library built on Java. The garden is shown in public-view style with stereo 3D graphic projection. The rendering is scalable from low to high resolution and enables drop object shadowing, which is indispensable for considering the effect of daytime changes in insolation. Visualizing the garden design based on Kansei analysis could facilitate collaboration between the designer and customer in the design process.

scholarly journals Research on Optimized Product Image Design Integrated Decision System Based on Kansei Engineering

2020 ◽  
Vol 10 (4) ◽  
pp. 1198 ◽  
Author(s):  
Lei Xue ◽  
Xiao Yi ◽  
Ye Zhang
Keyword(s):  
Decision Model ◽  
Type I ◽  
Design Decision ◽  
Kansei Engineering ◽  
Decision System ◽  
Meaningful Improvement ◽  
Quantification Theory ◽  
Design Elements ◽  
Product Image ◽  
Qualitative Decision

In order to facilitate the development of product image design, the research proposes the optimized product image design integrated decision system based on Kansei Engineering experiment. The system consists of two sub-models, namely product image design qualitative decision model and quantitative decision model. Firstly, using the product image design qualitative decision model, the influential design elements for the product image are identified based on Quantification Theory Type I. Secondly, the quantitative decision model is utilized to predict the product total image. Grey Relation Analysis (GRA)–Fuzzy logic sub-models of influential design elements are built up separately. After that, utility optimization model is applied to obtain the multi-objective product image. Finally, the product image design integrated decision system is completed to optimize the product image design in the process of product design. A case study of train seat design is given to demonstrate the analysis results. The train seat image design integrated decision system is constructed to determine the product image. This shows the proposed system is effective and for predicting and evaluating the product image. The results provide meaningful improvement for product image design decision.

Quantifying Customer Perception of Product Harmony Using Kansei Engineering Method

2002 ◽  
Vol 46 (6) ◽  
pp. 720-724 ◽  
Author(s):  
Lijian Zhang
Keyword(s):  
Interior Design ◽  
Truck Drivers ◽  
Design Parameters ◽  
Kansei Engineering ◽  
Vehicle Interior ◽  
Quantification Theory ◽  
Customer Perception ◽  
Design Elements ◽  
Design Engineers ◽  
Significant Difference

Vehicle interior harmony has drawn increasing attention from customers in recent years. Kansei Engineering is an effective approach to quantify customers' perception of harmony, and to correlate it to design parameters of the products. Herein, we investigated the customer perception of the visual aspects of commercial truck door interior design using classification methods. This article describes how these visual impressions are related to design elements using quantification theory, a commonly used method in Kansei Engineering. The results reveal that trim material, shape, color, window shape, and map pocket are design elements that strongly affect the perception of “elegance” and preferences of truck drivers. The results also showed a significant difference between the perception of the truck drivers and that of design engineers.

Research on Kansei Engineering and its Application in Massage Chair Design

2011 ◽  
Vol 480-481 ◽  
pp. 1014-1017 ◽  
Author(s):  
Zhen Ya Wang ◽  
Ying Ying Liang ◽  
Hui Hui Shi
Keyword(s):  
Product Design ◽  
English Literature ◽  
Differential Method ◽  
Spiritual Needs ◽  
Engineering System ◽  
Kansei Engineering ◽  
Design Factor ◽  
Design Elements ◽  
Domestic Design ◽  
Chair Design

Kansei Engineering is a technical methodology to translate consumer’s Kansei into product design elements. The target of this technology is to provide designers and manufacturers with a technique to master the emotional and spiritual needs of consumers and then manifest them in product design to enhance competitive edge. In light of this situation and on the basis of finishing a lot of English literature reading about this technology, the author conducted systematical study about Kansei Engineering in this thesis with the aim to enhance understanding of it for domestic designers and accelerate spread of it. Basing on the study about the situations of China’s domestic design industry, the author analyzed several points that China’s design industry should learn from Japan and Kansei Engineering technology, and proposed a simplified Kansei Engineering Model which is easier to execute and suitable for domestic design industry. In conclusion, this paper gives an introduction to the theory of Kansei Engineering system, and explores the relationship between consumer's desire and massage chair design factor with the SD (Semantic Differential) method, providing effective reference for the massage chair design.

scholarly journals Optimal Design of Virtual Reality Visualization Interface Based on Kansei Engineering Image Space Research

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1722
Author(s):  
Qianwen Fu ◽  
Jian Lv ◽  
Shihao Tang ◽  
Qingsheng Xie
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Virtual Reality ◽  
Regression Analysis ◽  
Convolutional Neural Network ◽  
Kansei Engineering ◽  
Design Features ◽  
Design Elements ◽  
Design Scheme ◽  
Important Design

To effectively organize design elements in virtual reality (VR) scene design and provide evaluation methods for the design process, we built a user image space cognitive model. This involved perceptual engineering methods and optimization of the VR interface. First, we studied the coupling of user cognition and design features in the VR system via the Kansei Engineering (KE) method. The quantitative theory I and KE model regression analysis were used to analyze the design elements of the VR system’s human–computer interaction interface. Combined with the complex network method, we summarized the relationship between design features and analyzed the important design features that affect users’ perceptual imagery. Then, based on the characteristics of machine learning, we used a convolutional neural network (CNN) to predict and analyze the user’s perceptual imagery in the VR system, to provide assistance for the design optimization of the VR system design. Finally, we verified the validity and feasibility of the solution by combining it with the human–machine interface design of the VR system. We conducted a feasibility analysis of the KE model, in which the similarity between the multivariate regression analysis of the VR intention space and the experimental test was approximately 97% and the error was very small; thus, the VR intention space model was well correlated. The Mean Square Error (MSE) of the convolutional neural network (CNN) prediction model was calculated with a measured value of 0.0074, and the MSE value was less than 0.01. The results show that this method can improve the effectiveness and feasibility of the design scheme. Designers use important design feature elements to assist in VR system optimization design and use CNN machine learning methods to predict user image values in VR systems and improve the design efficiency. Facing the same design task requirements in VR system interfaces, the traditional design scheme was compared with the scheme optimized by this method. The results showed that the design scheme optimized by this method better fits the user’s perceptual imagery index, and thus the user’s task operation experience was better.

scholarly journals Evaluation of Kansei Engineering System based on Virtual Reality

1996 ◽  
Vol 32 (Supplement) ◽  
pp. 178-179
Author(s):  
Toshinori Fujie ◽  
Yukihiro Matsubara ◽  
Mitsuo Nagamachi
Keyword(s):  
Virtual Reality ◽  
Engineering System ◽  
Kansei Engineering

scholarly journals Redesign the User Interface of the Purwakarta Disdukcapil Mobile Application Using Kansei Engineering

SinkrOn ◽  
2022 ◽  
Vol 7 (1) ◽  
pp. 66-75
Author(s):  
Yudhi Raymond Ramadhan ◽  
Imam Maruf Nugroho ◽  
Imam Khaerul Anwar
Keyword(s):  
User Interface ◽  
Mobile Application ◽  
Partial Least Square ◽  
Least Square ◽  
Type I ◽  
Kansei Engineering ◽  
Design Factor ◽  
Design Elements ◽  
Ui Design ◽  
Emotional Factors

The function and usability of a mobile application are the main reasons for making the application. In addition, the User Interface (UI) design factor is also an important consideration in making a mobile application. Good UI design is the main attraction for the application to use. There are many ways to make a good UI design. Kansei Engineering (KE) is one of the methods that can be used in the UI design process. Since the creation of the Mobile Disdukcapil application, there has never been a study on the application's design interface. This research aims to make recommendations on design elements desired by users. The KE method can detect the user's feelings towards an interface. So that the KE method will produce a UI design for the Disdukcapil mobile application that is liked by the user. The methodology used refers to the Kansei Engineering Type I methodology. This research uses Kansei Words to represent the emotional factors of the user when viewing a product specimen. Kansei Word used as many as 10 words related to the UI display on the mobile application. The mobile application specimens used were 5 specimens, which were taken from various similar applications. This study involved 80 participants to fill out the questionnaire. The results of the questionnaire were processed using multivariate statistical analysis, namely Cronbach's Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA), and Partial Least Square (PLS). The results of this study are in the form of recommendations for UI design elements based on the most dominant emotional factors. Based on the results of data processing, the dominant emotional factors are "Colorful" and "Simple".

scholarly journals Perceptual design method for smart industrial robots based on virtual reality and synchronous quantitative physiological signals

2020 ◽  
Vol 16 (5) ◽  
pp. 155014772091764
Author(s):  
Wangqun Xiao ◽  
Jianxin Cheng
Keyword(s):  
Virtual Reality ◽  
Design Method ◽  
Industrial Robot ◽  
Three Dimensional ◽  
Industrial Robots ◽  
Physiological Signals ◽  
Robot Design ◽  
Type I ◽  
Design Elements ◽  
Three Dimensional Modeling

In the research of industrial robot design, designing using only the perceptual thinking and creativity of an industrial designer or overemphasizing the intervention of quantitative data research in the field of emotional cognition is relatively one sided. In this article, research on how to combine the above two aspects effectively will be conducted. The aim is to present a design method which provides artistic creativity and scientific support for industrial robot design. Therefore, a method for representing perceptual image spaces of industrial robots through pictures and semantics by evaluating the perceptual images and using statistical approaches such as factor analysis will be proposed. Perceptual design elements of industrial robots are decomposed from the perspective of style and color. After the quantitative type I analysis, the numerical relationships between the semantics of images and design elements are identified. Also, a method for mapping relationships between the perceptual image spaces and design elements of industrial robots is developed. After three-dimensional modeling and simulation, the semantic difference methods are used in combination with the emotional evaluation and measurement methods for physiological experiments such as eye tracking, skin conductance, heart rate, and electroencephalography experiments with the aid of virtual reality. Finally, a perceptual design method is extracted for smart industrial robots based on virtual reality and synchronous quantitative physiological signals.

scholarly journals Influence of Personality Traits on Consumer Preferences: The Case of Office Chair Selection by Attractiveness

2018 ◽  
Vol 10 (11) ◽  
pp. 4183 ◽  
Author(s):  
Ya-Chuan Ko ◽  
Chi-Hung Lo ◽  
Chi-Chuan Chen
Keyword(s):  
Personality Traits ◽  
Work Environment ◽  
Consumer Preferences ◽  
Working Hours ◽  
Living Standards ◽  
Office Workers ◽  
Type I ◽  
Quantification Theory ◽  
Design Elements ◽  
Office Environment

With increasing living standards, a modern product is required to provide emotional links between a user’s personality and their work environment, in addition to satisfying functional and physiological needs. Since office workers in Taiwan have average daily working hours of over 8 h, they spend lots of time on office chairs, and nowadays more companies are willing to buy good chairs so that their employees can deliver higher efficiency under a more comfortable office environment. After interviewing a group of experts, office chairs are classified into 7 types, and the participants’ personality traits are classified into 4 categories. The influence of different personality traits on the evaluation of office chairs by attractiveness is analyzed by quantification theory type I. Design elements that can better deliver an office chair’s attractiveness are determined. The results allow future designers to improve their designs by identifying the preferences of target users under difference office scenarios.

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