The Relationship Between Computer-Aided Acquisition and Logistics Support (CALS) and Concurrent Engineering

1989 ◽  
Author(s):  
Jonathan D. Wood ◽  
Robert I. Winner
Keyword(s):  
Concurrent Engineering ◽  
Computer Aided ◽  
The Relationship

Research on bra component design and perceptual image prediction

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fang Fang ◽  
Caili Hu ◽  
Ting Ting Yan
Keyword(s):  
Cognitive Psychology ◽  
Prediction Model ◽  
Indicator System ◽  
Content Type ◽  
Class Theory ◽  
Female Consumers ◽  
Component Design ◽  
Computer Aided ◽  
The Future ◽  
The Relationship

PurposeThe purpose of this paper is to apply the theory of perceptual image to clothing, study the effect of bra components on the perceptual image of Chinese female consumers aged 18 to 27, explore the relationship between them, promote the computer-aided bra design to be more rapid and accurate and meet consumer's needs better.Design/methodology/approachIn this paper, cognitive psychology and mathematical analysis methods were used, and two experiments were conducted. A reaction time experiment was conducted based on 3D virtual bra samples, proving that bra components have an effect on the consumer's perceptual image and obtaining a revised bra component design indicator system by multi-dimensional Scaling (MDS). A projection experiment was conducted to study what kind of relationship exists between the two, and a prediction model was constructed by the quantitative I-class theory.FindingsIt is found that bra components have an effect on perceptual image of Chinese female consumers aged 18 to 27. A total of five important components (cup area, center front height, torso width, side wing width and center back shape) that affect the consumer's perceptual image were identified by MDS and references analysis, and then a bra perceptual image space composed of five pairs of words was constructed by subjective evaluation and cluster analysis. What is more, a prediction model was obtained by the quantitative I-class theory; after testing, the model can visually and effectively predict consumer's perceptual image according to bra components indicators, which provide a convenience for the positive design of bras.Research limitations/implicationsIn this article, the authors just studied bra components, but did not take fabric, color and other factors that also affect the perceptual image into consideration. Further research can use this method to study other important influential factors as well as their comprehensive impact. Also, the subjects are Chinese young women; consumers of other age or from other countries are not involved, and more extensive research can be done in the future.Practical implicationsThe bra component indicator system can help to build a more systematic and clearer bra design library, which provides convenience for designers to search and use them quickly, improving the efficiency of bra design. The prediction model is also helpful to bra designers and companies. When they already design a bra, they can use this model to predict consumer's perceptual image, thus carry out more accurate market positioning and promotion. When they want to satisfy consumers or design a specific effect, they can also refer to this model to reverse design of components. In general, the outcomes of this paper can help companies to quickly establish a computer-aided bra design system, which is conducive to designers to accurately design and better meet market's needs, and the method is also a good attempt to apply the theory of perceptual image in psychology to clothing and can be extended to other relevant fields in the future.Originality/valueBased on cognitive psychology, this paper attempts to apply the theory of perceptual image in psychology into clothing and takes bra as an example to study the relationship between bra components and consumer's perceptual image. The prediction model constructed here is conducive to the development of bra design and to meet personalized needs of consumers. This method can also be extended to other fields in the future.

Redesign of Liangzhu Pottery Based on Form Style Recognition

2012 ◽  
Vol 268-270 ◽  
pp. 1970-1973 ◽  
Author(s):  
Shang Shang Zhu ◽  
Shao Hong Li
Keyword(s):  
Factor Analysis ◽  
Form Factors ◽  
Traditional Culture ◽  
Type I ◽  
Cultural Artifacts ◽  
Computer Aided ◽  
Essential Form ◽  
Form Features ◽  
The Relationship ◽  
Kj Method

Take the Liangzhu pottery as examples, an approach of form style recognition was proposed to further exploring the redesign of cultural artifacts from industrial design. Firstly, six major images of Liangzhu pottery was investigated by using KJ method and Factor Analysis; Then the relationship between the essential form factors and the major images were analyzed through Quantification Type I; Finally, the perceptual image knowledge base of Liangzhu cultural artifacts and a computer-aided form redesign system was built. Based on this system, the particular images conveyed by the cultural artifacts and the corresponding form features can be obtained, the traditional culture can be expanded. Thus the theory of form style recognition in the redesign of cultural artifacts is tested.

Computer Aided Design and Analysis of Composite Structure

2014 ◽  
Vol 1036 ◽  
pp. 989-994 ◽  
Author(s):  
Michał Majzner ◽  
Andrzej Baier
Keyword(s):  
Layered Structure ◽  
Computer Aided Design ◽  
Object Oriented ◽  
Verification And Validation ◽  
Structural Components ◽  
Modeling And Analysis ◽  
Computer Aided ◽  
The Individual ◽  
Aided Design ◽  
The Relationship

Feature is one of the methods for representing objects from which are representing components, products and processes. This article presents methods for integration of features of methods in modeling and analysis of composite structural components. The aim of the research is to develop methods for verification and validation of composite layered structure, distinguishing components of the individual layers and identify the relationship between them. By applying the method of features it is possible to determine the structure of the composite fit to the requirements of design and construction. Proposed new types of feature, which allows the creation of object-oriented structures of composite components.

Analyzing up Front

2000 ◽  
Vol 122 (10) ◽  
pp. 88-91 ◽  
Author(s):  
Jean Thilmany
Keyword(s):  
Lead Time ◽  
Stress Tests ◽  
Element Analysis ◽  
Design Engineers ◽  
Software Packages ◽  
Engineering Company ◽  
Computer Aided ◽  
Depth Study ◽  
The Relationship ◽  
Senior Engineer

This article highlights that up-front computer-aided engineering (CAE) dramatically decreases product lead time. Up-front CAE entails vesting responsibility for performing finite element analysis tests and other analysis tests with the design engineers. The designers use specific software packages to analyze their first-stage designs. This way, they can easily change designs that do not pass analysis tests-such as vibration or stress tests-before passing them on to an analyst for in-depth study. Not every engineering company, however, is turning to up-front CAE even as it faces the need to get products to market faster. Some engineers, like Zlatko Penzar, find that their present analysis hierarchy works just fine. He is a senior engineer for the fuel systems division of Mannesmann in Dusseldorf, Germany, another auto components supplier. Engineering departments have to find their own answer to the relationship between designer and analyst. The important thing is that once an answer is agreed upon, it happens the same way every day. A working atmosphere that functions reliably and smoothly is really the key to successful product design.

Neural Networks for Modeling the Contact Foot-Shoe Upper

2010 ◽  
pp. 561-573
Author(s):  
M. J. Rupérez ◽  
J. D. Martín ◽  
C. Monserrat ◽  
M. Alcañiz
Keyword(s):  
Neural Networks ◽  
Computer Aided Design ◽  
Characteristic Curve ◽  
Neural Model ◽  
Computer Aided ◽  
Materials Used ◽  
Aided Design ◽  
Footwear Design ◽  
The Relationship

Recently, important advances in virtual reality have made possible real improvements in computer aided design, CAD. These advances are being applied to all the fields and they have reached to the footwear design. The majority of the interaction foot-shoe simulation processes have been focused on the interaction between the foot and the sole. However, few efforts have been made in order to simulate the interaction between the shoe upper and the foot surface. To simulate this interaction, flexibility tests (characterization of the relationship between exerted force and displacement) are carried out to evaluate the materials used for the shoe upper. This chapter shows a procedure based on artificial neural networks (ANNs) to reduce the number of flexibility tests that are needed for a comfortable shoe design. Using the elastic parameters of the material as inputs to the ANN, it is possible to find a neural model that provides a unique equation for the relationship between force and displacement instead of a different characteristic curve for each material. Achieved results show the suitability of the proposed approach.

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