A stage-wise conversion factor approach for predicting fabric width and mass per unit area in cotton/elastane single lacoste knitted fabrics

The precise control of the width and mass per unit area (GSM, g/m²) is of paramount importance in an industrial production environment of cotton/elastane knitted fabrics owing to the dimensional variability that elastane introduces. This work describes a robust method to quantitatively predict the evolution of fabric width and GSM during the manufacturing process of cotton/elastane single lacoste knitted fabrics, using a stage-wise conversion-factor-based predictive framework. Fabrics were knitted using 34 Ne cotton yarn and 40 denier elastane on circular knitting machines with a diameter of 26–38 in.. The samples were collected at different processing stages such as grey, heat-setting, stentering, finishing, and relaxation. It is observed that heat-setting leads to the highest dimensional expansion due to elastane relaxation and loop rearrangement which in turn decreases GSM value whereas subsequent processes promote structural stabilisation of fabrics. GSM conversion factors varied from 0.95 to 1.08 and width conversion factors from 1.00 to 1.10 for different processing stages, respectively. The predictive ability was validated using independent production samples, showing close agreement between predicted values and measured ones with a much reduced deviation level under industrial scenario. Dimensional stability was confirmed by shrinkage (−1.7% to −4.1%) and spirality (0.5%–1.5%) being within acceptable tolerance limits for industry purposes. The framework proposed here converts traditional empirical process control into a numerical and repeatable predictive method, aiming towards greater process optimisation, less variability in production and more consistent quality of industrial knitted fabrics.