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Development of a fuzzy logic model for designing personalized ease allowance of a women trouser

Development of a fuzzy logic model for designing personalized ease allowance of a women trouser. Abher RASHEED Xianyi ZENG Sébastien THOMASSEY. Plan of the present ation …. Motivation Literature 2.1 Garment design 2.2 Body Morphology Experimentation 3.1 Fabric selection

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Development of a fuzzy logic model for designing personalized ease allowance of a women trouser

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  1. Development of a fuzzy logic model for designing personalized ease allowance of a women trouser Abher RASHEED Xianyi ZENG Sébastien THOMASSEY

  2. Plan of the presentation … • Motivation • Literature 2.1 Garment design 2.2 Body Morphology • Experimentation 3.1 Fabric selection 3.2 Observers / Models 3.3Draping and ease allowance • Fuzzy logic Model • Results • Conclusion • Future work

  3. Motivation… • A CAD system that can produce garment patterns automatically • Good style • Perfect fit for the client • Low cost • Design a mathematical model • Calculating personalized ease allowance • Body measurements • Fabric properties

  4. 2.1 Garment Design … • There are two methods of garment designing • 2D pattern making • Draping

  5. 2D Pattern Making … • Body measurements • Drawing construction lines • Pattern making • Verification - Trueing • Grading

  6. Draping… • Preparation of mannequins • Preparation of fabric • Draping on mannequin • Patron drawing • Seam allowances • Cutting and dart closing • Corrections

  7. 2.2 Body Morphology… • Morphologically, woman body is divided into 7 categories [McCormack H. 2005] • 8 shape • Hourglass • Pyramide • Inverse pyramide • Rectangular • Round • Oval

  8. Experimental Work … General scheme of mathematical model

  9. 3.1 Fabric Selection … • Six fabrics made of different materials were chosen for this study.

  10. Physical Tests Weight Bending length thickness Linearity Resilience Compression energy Sensory Evaluation Smoothingness Softness Stretchability Bulkiness Fall 3.1 Fabric Selection (Cont…)

  11. 3.1 Fabric Selection (Cont…)

  12. 3.1 Fabric Selection (Cont…)

  13. PCA (Principle Component Analysis) … Sample 1 Sample 3 Sample 4 Softness (var2) Stretchability (var3) Bending Length (var6) Weight (var8)

  14. 3.2 Observers / Models … • 3D body scanner was used to take the body measurements of the models.

  15. 3.3 Patterns Obtained by Draping …

  16. 3.3 Ease Allowance Measurement … Ease Allowance = mesurement on pattern – Body mesurement

  17. a Fuzzy Inference System …

  18. Fuzzy Inference System (Cont…) SFT = Softness STR = Stretchability GSM = Weight BEL = Bending Length WHD = Waitst to hips distance verticle EAH = Ease Allowance at Hips

  19. Fuzzy Rules (Cont…)

  20. Results Obtained

  21. Results Obtained (Cont…) Sample 1 Sample 3 Sample 4 Sample 5 WHD = Waist to hips distance verticle EAH = Ease allowance at hips

  22. Conclusion • The most important parameters are softness (SFT) and waist to hips distance (WHD). • Stretchability (STR) is also reasonably critical while bending length (BEL) comes after it. • Weight (GSM) has no significant influence on the results.

  23. Future Work… • More sophisticated study is required to find out a set of fabric parameters which greatly influence ease allowance. For this purpose, a bigger knowledge base has to be developed by using more fabrics samples with more variations. • By using same technique, mathematical expressions can be developed to find out ease on other points of the pattern. • A software can be designed, by using all the mathematical expressions, which will be able to draft a pattern automatically (by getting a few simple inputs)

  24. Thank you for your attention

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