Title page for ETD etd-10252004-205544


Type of Document Master's Thesis
Author Gider, Ayse
Author's Email Address agider1@lsu.edu
URN etd-10252004-205544
Title An Online Fabric Database to Link Fabric Drape and End-Use Properties
Degree Master of Science (M.S.)
Department Human Ecology
Advisory Committee
Advisor Name Title
Yan Chen Committee Chair
Jacquelene Robeck Committee Member
Jenna T Kuttruff Committee Member
Jianhua Chen Committee Member
Keywords
  • fuzzy linear clustering
  • fabric drape
  • kawabata fabric evaluation system
  • predicting end-use
  • cusick drape tester
  • fabric database
Date of Defense 2004-05-07
Availability unrestricted
Abstract
The main obstacle for adaptation of fabric selection through the Internet is that there is no objective selection method that is suitable for fashion fabrics. The purpose of this research is to develop an objective evaluation method for selecting fabrics through an online fabric database. The relationship between fabric mechanical properties and fabric drape was investigated. One hundred eighty-five commercial fabrics from different manufacturers were tested using the Kawabata fabric evaluation system (KES-FB) and Cusick drape tester. Applying regression analysis, the parameters that were significantly correlated with drape coefficient (DC) were determined.

The test results, fabric structural parameters, and contact information for fabric manufacturers, were included in the database. A web-site with a user interface allowing users to implement various types of searches was published on the Internet. Fuzzy linear clustering technique was used to predict fabric drape property. The accuracy for predicting fabric drape using this technique was 94%. This means the model using fuzzy linear clustering is an efficient method to predict fabric end-use properties.

Additionally, a new method to measure drape coefficient using Photo Shop was developed by this author. Instead of weighing paper rings, shaded drape area was used to calculate the drape coefficient. With the new Photo Shop method, the cost, testing time and human error was reduced while the accuracy of the test result was increased.

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