Dyeing process parameter optimization and quality characteristics modeling for viscose blended knitted fabrics / Md Ismail Hossain

• Main Author: Md Ismail , Hossain
• Format: Thesis
• Published: 2016
• Subjects: T Technology (General)
• Online Access: http://studentsrepo.um.edu.my/7489/1/All.pdf; http://studentsrepo.um.edu.my/7489/5/ismail.pdf; http://studentsrepo.um.edu.my/7489/

The demand of viscose knitted fabrics is increasing rapidly due to its lower price and exclusive quality characteristics. In latest epoch of globalization, customers demand high quality products, lowest price and shorter lead time for product development and delivery. However, traditional knitting & dyeing process consists of trial and error approach which is time consuming, less efficient, cost ineffective and produces fabrics of inferior quality. Moreover, automatic control of knitting & dyeing process are developing slowly due to the complexity of that manufacturing process. Process optimization and quality characteristics modeling is one of the most viable and efficient alternative technique to meet the customers requirement. Conventional trial-and-error approaches, full factorial experimental design as well as artificial neural network (ANN) and genetic algorithm for optimization did not succeed due to the large volume of works, longer experimental time and huge raw material availability. In this context, Taguchi method is an efficient tool for process optimization in quality engineering. Moreover, various factors affecting the quality characteristics of knitted fabrics are non-linear and interactive with each other‘s. In this background, Fuzzy logic (FL) is a scientific and engineering solution for quality modeling because FL model performs remarkably well in non-linear domain with smallest amount of experimental data. The main objectives of this study were to optimize the dyeing process parameters and develop mathematical model for the prediction of color strength of viscose/lycra blended knitted fabrics through Taguchi method as well as develop intelligent prediction models for color strength of viscose/lycra, cotton/lycra and lyocell/lycra blended knitted fabrics and bursting strength of viscose/lycra blended knitted fabrics using fuzzy logic approach. Further the aim was to build ANN prediction model to compare the fuzzy models performance and a resin finishing model for controlling the dimensional stability of viscose jersey knitted fabrics by fuzzy technique. It was found from experimental study that viscose/lycra blended knitted fabrics color strength is approximately 60 % stronger while bursting strength is approximately 100 % weaker than that of cotton/lycra blended knitted fabrics. Further, color fastness of dyed fabrics depends more on the type of reactive dyes and dyeing method rather than washing parameters and type of fibers. The optimal factors in the viscose/lycra blended knitted fabrics dyeing process were found to be dye concentration 9 %, Time 60 minutes, temperature 75 oC, salt concentration 50 g/l, alkali concentration 14 g/l and liquor ratio 1:8. Further, coefficient of determination (R2) and mean absolute error (MAE) between the experimental results and that predicted by the Taguchi mathematical model were found to be 0.921 and 3.48 %, respectively. It was concluded that Taguchi method was successful for optimization and prediction in complex dyeing. Furthermore, it was found that fuzzy models exhibit excellent prediction performance for viscose/lycra, cotton/lycra and lyocell/lycra blended knitted fabrics with less than 5 % MAE and coefficient of determination (R2) more than 0.984. Additionally, ANN model showed superior prediction performance than fuzzy model and fuzzy resin finishing model was highly effective for maximum shrinkage control with minimum loss in bursting strength for viscose plain knitted fabrics.