Neural Network Models for Transforming Consumer Perception into Product Form Design

2006 ◽  
pp. 799-804 ◽  
Author(s):  
Chung-Hsing Yeh ◽  
Yang-Cheng Lin
Keyword(s):  
Neural Network ◽  
Network Models ◽  
Consumer Perception ◽  
Product Form ◽  
Neural Network Models ◽  
Form Design ◽  
Product Form Design

scholarly journals Comparison of Two Quantitative Analysis Techniques to Predict the Evaluation of Product Form Design

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Hung-Yuan Chen ◽  
Yu-Ming Chang ◽  
Ting-Chun Tung
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Predictive Performance ◽  
Consumer Perception ◽  
Product Form ◽  
Modeling Technique ◽  
Form Design ◽  
Product Form Design ◽  
Product Forms

Consumer satisfaction with a product’s form plays an essential role in determining the likelihood of its commercial success. A consumer perception-centered design approach is proposed in this study to aid product designers with incorporating consumers’ perceptions of product forms in the design process. The consumer perception-centered design approach uses the linear modeling technique (multiple linear regression) and the nonlinear modeling technique (neural network) to determine the satisfying product form design for matching a given product image. A series of experimental evaluations are conducted to collect evaluation results for examining the relationship between the automobile profile features and the consumers’ perceptions of the automobile image. The result of predictive performance comparison shows that both the nonlinear neural network modeling technique and the multiple linear regression technique are comparably good for predicting the consumers’ likely response to a particular automobile profile since the predictive performance difference between the two modeling techniques is very slight in this study. Although this study has chosen a 2D automobile profile for illustration purposes, the concept of the proposed approach is expansively applicable to 3D automotive form design or other consumer product forms.

A neural network based approach for product form design

2002 ◽  
Vol 23 (1) ◽  
pp. 67-84 ◽  
Author(s):  
Shih-Wen Hsiao ◽  
H.C Huang
Keyword(s):  
Neural Network ◽  
Product Form ◽  
Form Design ◽  
Product Form Design

Method of complex copper-zinc ore typification using neural network models

2020 ◽  
Vol 5 ◽  
pp. 140-147 ◽  
Author(s):  
T.N. Aleksandrova ◽  
◽  
E.K. Ushakov ◽  
A.V. Orlova ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Network Models ◽  
Neural Network Models ◽  
Copper Zinc ◽  
Complex Copper

Digital twin of equipment as a basis for the consumer in digital production

2020 ◽  
Keyword(s):  
Neural Network ◽  
Tool Wear ◽  
Chip Formation ◽  
Network Models ◽  
Machining Accuracy ◽  
Neural Network Models ◽  
Digital Twin ◽  
The Neural Network ◽  
Digital Production ◽  
Cyberphysical System

The neural network models series used in the development of an aggregated digital twin of equipment as a cyber-physical system are presented. The twins of machining accuracy, chip formation and tool wear are examined in detail. On their basis, systems for stabilization of the chip formation process during cutting and diagnose of the cutting too wear are developed. Keywords cyberphysical system; neural network model of equipment; big data, digital twin of the chip formation; digital twin of the tool wear; digital twin of nanostructured coating choice

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