scholarly journals A Study of Kansei Engineering on Basic Design Elements

1999 ◽  
Vol 35 (1Supplement) ◽  
pp. 114a-114a
Author(s):  
Tatsuo Nishino ◽  
Mitsuo Nagamachi ◽  
Makoto Ichitsubo ◽  
Koji Komatsu ◽  
Shigekazu Ishihara ◽  
...  
Keyword(s):  
Basic Design ◽  
Kansei Engineering ◽  
Design Elements

scholarly journals A Study of Kansei Engineering on Basic Design Elements.

1999 ◽  
Vol 35 ◽  
pp. 428-429
Author(s):  
Tatsuo Nishino ◽  
Mitsuo Nagamachi ◽  
Makoto Ichitubo ◽  
Koji Komatsu ◽  
Shigekazu Ishihara ◽  
...  
Keyword(s):  
Basic Design ◽  
Kansei Engineering ◽  
Design Elements

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.

Software

2018 ◽  
Author(s):  
James A. Anderson
Keyword(s):  
19Th Century ◽  
Assembly Language ◽  
Human Cognition ◽  
Basic Design ◽  
Design Elements ◽  
The Core ◽  
Alan Turing ◽  
Word Level ◽  
Digital Hardware ◽  
Logic Functions

Digital computers are “protean” in that they can become almost anything through software. Their basic design elements came from a 19th-century British tradition in logic, exemplified by Boole and Babbage. It seemed natural to have logic realized in hardware. This tradition culminated in the work of Alan Turing who proposed a universal computing machine, now called a Turing machine, based on logic. Although hardware that computes logic functions lies at the core of digital hardware, low-level practical machine operations are grouped together in “words.” Programs are based on hardware operations controlling computation at the word level. This chapter presents a detailed example of what a computer does when it actually “computes.” Because human cognition finds it hard to use such an alien device, there is a brief discussion of how programming became “humanized” with the invention of software tools like assembly language and FORTRAN.

Research on Product Identity Design Based on Kansei Image in Mechanic Equipment

2013 ◽  
Vol 651 ◽  
pp. 569-574
Author(s):  
Peng Wang ◽  
Jian Ning Su ◽  
Chi Bing Hu ◽  
Shu Tao Zhang
Keyword(s):  
Testing Machine ◽  
Design Feature ◽  
Principal Component ◽  
Feature Space ◽  
Image Space ◽  
Analysis Method ◽  
Kansei Engineering ◽  
Design Elements ◽  
Product Identity ◽  
Kj Method

On the study of Kansei engineering and product identity, This paper presents the key methods and process of product identity design on Kansei image, including locating the Kansei image space, identifying the design feature space, mapping relation between Kansei image and design elements, mining product semantic. The research also establishes the Kansei image space model on the three cognitive dimensions of visual, quality and brand, and summarizes the design of processes and methods. In those aspects, some Kansei engineering methods are used to achieve industrial design, such as KJ method, SD method, Principal component analysis method, Quantification-I theory method. It is verified after the practical application of Hongshan testing machine that the method and process is reasonable and feasible.

Research of Kansei Image Based on Product Appearance Form Deconstruction

2014 ◽  
Vol 971-973 ◽  
pp. 1316-1320 ◽  
Author(s):  
Yan Zhou ◽  
Ping Yang ◽  
Si Yu Wang
Keyword(s):  
Mobile Phone ◽  
Subjective Evaluation ◽  
Emotional Problem ◽  
Emotional Reactions ◽  
Cluster Method ◽  
Subjective Feeling ◽  
Kansei Engineering ◽  
Design Elements ◽  
Engineering Theory ◽  
Form Design

Based on kansei engineering theory, with mobile phone model as the research object, on the speciation analysis of deconstruction, study of the correlation between form design elements and subjective feeling. To obtain mobile phone simulation modeling samples by the concept of orthogonal test. Through collecting a large number of perceptual image vocabulary, the multiple scale method, class cluster method was applied to typical filtered emotional vocabulary, as the shape of subjective evaluation metrics. Using the mobile phone modeling sample obtained from the screened and representative emotional semantic difference experiment on the emotional reactions of vocabulary, get the corresponding relation between mobile phones form design elements and subjective evaluation value. Quantitative fuzzy uncertainty of emotional problem, and using kansei engineering theory to improve product that cares consumers emotional has become the direction of product design.

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 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.

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