Determinations of 3D ease allowance in a ...
Type de document :
Article dans une revue scientifique: Article original
URL permanente :
Titre :
Determinations of 3D ease allowance in a virtual environment for customized garment design using fuzzy modelling
Auteur(s) :
Abtew, Mulat Alubel [Auteur]
Bahir Dar University [BDU]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Kulinska, Maria [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Zeng, Xianyi [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Bruniaux, Pascal [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Bahir Dar University [BDU]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Kulinska, Maria [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Zeng, Xianyi [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Bruniaux, Pascal [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Titre de la revue :
Computers in Industry
Nom court de la revue :
Comput. Ind.
Numéro :
133
Pagination :
-
Date de publication :
2021-11-28
ISSN :
0166-3615
Mot(s)-clé(s) en anglais :
Computer-aided design
Virtual garment
Three-dimensional (3D) ease allowance
Mathematical modelling
Fuzzy techniques
Garment Industry
Virtual garment
Three-dimensional (3D) ease allowance
Mathematical modelling
Fuzzy techniques
Garment Industry
Discipline(s) HAL :
Sciences de l'ingénieur [physics]
Résumé en anglais : [en]
The relationship between garment design parameters, wearer morphology, posture, fabric properties and ease allowance values is very complex and uncertain due to the presence existence of various human factors related to ...
Lire la suite >The relationship between garment design parameters, wearer morphology, posture, fabric properties and ease allowance values is very complex and uncertain due to the presence existence of various human factors related to designer and consumer perception. The aim of this work is to set up a series of mathematical models to characterize and determine the relationship between these parameters. For this purpose, fuzzy modelling techniques were proposed to extract IF-THEN rules by learning from the experimental data. First, the general modelling principle and related concepts were outlined. The different samples collected to obtain the learning data were described in detail. The samples were then characterized by instrumental measurements and sensory evaluations to form the input and output data for modelling. Based on the obtained input and output learning data, it became possible to determine the modelling procedure to extract relevant fuzzy rules. The computation then helps in determining the 3D ease allowance values from the desired human perception on fit, comfort and other design parameters. For a new sample and consumer morphology, the relevant degree of input data with respect to all the fuzzy rules was also calculated to find the most appropriate ease allowance value. The developed mathematical model followed by experiments also provides advantages in controlling and adjusting patterns according to perceptions of the designer and consumer. The concept of determining 3D ease allowance could be further integrated into the 3D clothing CAD approach to obtain a suitable garment surface on specific virtual human model environments to customize any garments in the fashion industry.Lire moins >
Lire la suite >The relationship between garment design parameters, wearer morphology, posture, fabric properties and ease allowance values is very complex and uncertain due to the presence existence of various human factors related to designer and consumer perception. The aim of this work is to set up a series of mathematical models to characterize and determine the relationship between these parameters. For this purpose, fuzzy modelling techniques were proposed to extract IF-THEN rules by learning from the experimental data. First, the general modelling principle and related concepts were outlined. The different samples collected to obtain the learning data were described in detail. The samples were then characterized by instrumental measurements and sensory evaluations to form the input and output data for modelling. Based on the obtained input and output learning data, it became possible to determine the modelling procedure to extract relevant fuzzy rules. The computation then helps in determining the 3D ease allowance values from the desired human perception on fit, comfort and other design parameters. For a new sample and consumer morphology, the relevant degree of input data with respect to all the fuzzy rules was also calculated to find the most appropriate ease allowance value. The developed mathematical model followed by experiments also provides advantages in controlling and adjusting patterns according to perceptions of the designer and consumer. The concept of determining 3D ease allowance could be further integrated into the 3D clothing CAD approach to obtain a suitable garment surface on specific virtual human model environments to customize any garments in the fashion industry.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Date de dépôt :
2023-06-20T11:56:31Z
2024-03-21T10:08:36Z
2024-03-21T10:08:36Z