Using the HVI Fibrogram to Improve YARN Quality Predictions

Within-sample variation in cotton fiber length impacts processing performance and yarn quality. Excessive within-sample variation in fiber length can slow processing and contribute to imperfections in the yarn structure. HVI length parameters, Upper Half Mean Length and Uniformity Index, are based on the fibrogram measurement principle. In this experiment, we demonstrate that the fibrogram contains more information than is captured by current HVI length parameters, and this information is useful for predicting yarn quality. We extracted additional information from the fibrogram, and used this information to predict yarn quality. These results were then compared with the yarn quality predicted by standard HVI length parameters. Our experiment shows that the fibrogram holds important information that improves the prediction of yarn quality that is not captured by standard HVI length measurement protocols. The results also show that the additional length information extracted from the fibrogram is at least as good at explaining variation in yarn quality as the AFIS length distribution by number. This was demonstrated on three sets of samples representing a range of sample types. This approach suggests it should be possible to capture important information about within-sample variation in fiber length using the fibrogram.