Predicting fabric GSM and crease recovery angle of laser engraved denim by fuzzy logic analysis

Joy Sarkar, Moni Sankar Mondal, Elias Khalil

Abstract

This study intends to develop and validate a fuzzy logic based model to predict the GSM and crease recovery angle of laser engraved denim. Laser engraving is a popular method for creating a faded look in denim. Conventional fading methods have a lot of drawbacks while laser engraving is a complete solution with better productivity and less rejection rate. But the important laser parameters like Pixel Time and Dots Per Inch (DPI) influence the GSM and crease recovery angle of the treated denim. Though this relationship is nonlinear, a fuzzy logic based model has been developed to demonstrate the relationship among Pixel Time, DPI as input variables, and GSM, crease recovery angle as output variables. The developed model has been validated by trial. The Mean Relative Error was found 1.68, 2.18, and 2.25 for GSM, warp way crease recovery angle, and weft way crease recovery angle respectively. On the other hand, the coefficient of determination (R2) was found to be 0.966, 0.952, and 0.958 for the GSM, warp way crease recovery angle, and weft way crease recovery angle respectively. The authors found that the developed model is a completely new approach to predict the GSM and crease recovery angle of the laser engraved denim and therefore can be used as a decision-making tool in the apparel designing and manufacturing which can exclude a lot of existing trial and error hassle of the process designers.

Conclusion

The proposed model is quite capable of explaining the changes in GSM, warp, and weft way crease recovery angle of laser engraved denim with response to the changes in laser pixel time and Dots Per Inch (DPI). The decision-makers in the garments sector and garments designers would be able to make decisions regarding the fine-tuning of the said parameters when required. As the model can explain the effects of laser parameters on treated fabric parameters with satisfactory accuracy, this principle can be used to predict other fabric properties. This particular investigation actually opens the door of the suitability of eliminating the trial and error method of the textile sector, which is time-consuming as well as requires a lot of loss in terms of time and material. The conclusions may be drawn from this investigation are: a) The Mean Absolute Error between the predicted values and experimental values of GSM, warp way crease recovery angle (CRA-Warp), and weft way crease recovery angle (CRA-Weft) were found to be 1.68, 2.18, and 2.25 respectively which is lower than the acceptable limit of 5%. b) The correlation coefficient (R) between the predicted and experimental values of the output variables GSM, CRA-Warp, and CRA-Weft were found to be 0.983, 0.976, and 0.979 respectively. c) The Co-efficient of determination (R2) was found to be 0.966 for GSM, 0.952 for warp way crease recovery angle (CRA-Warp), and 0.958 for weft way crease recovery angle (CRA-Weft) which indicated a good fit of the model data with experimental data and hence suggests that the model is well compatible. Finally, it can be concluded that the proposed model can be used in the predicting and fine-tuning of some particular parameters of laser-treated garments with response to two most important laser parameters and the principle of this model can be used for further fabric and garment properties which can save a lot of time and effort for textile professionals.

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