An investigation of the relationship between fabric grain orientation and pattern grading Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/jh343w36q

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  • Pattern grading is a method of creating multiple sizes of a garment style. Grading to extreme sizes is not recommended since the design and drape of the garment can be distorted. Researchers suggest that customized fit is a solution for creating sizes in a garment style. However, manufacturers continue to grade patterns because it saves time and costs less to produce the multiple sizes needed in production. The purpose of this study was to investigate the relationship between fabric grain orientation and pattern grading and whether grading changes the drape of the garment. Different fabric grainlines and grade reference lines were used to determine the influence of traditional x and y coordinate grading methods on pattern shape and garment drape. A bias grain was used to determine if traditional x and y coordinate grading methods were appropriate for bias garments. It was thought that a bias garment would need new grade rules since the stretch of the bias could affect the overall fit and hang of the garment. A parametric model was developed in OptiTex™ software to represent a Misses size 12 and a dress pattern was then created and fit to this model. The pattern and model were then graded to a size 6 and a size 22. From the data, it appears that traditional grading methods and grading to larger and smaller sizes does not substantially affect the angle to the grainline at the grade points on the pattern perimeter. The center grade reference line in both the lengthwise and the bias dress was sufficient to produce additional garments that were similar to the base size pattern. The fit and drape of the original base size garment had the greatest influence on the fit and drape of the derived sizes. Therefore, if the garment grading increments are based on anthropometric data the fit and drape should be acceptable for individuals that are represented in the size data.
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