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processes which requires lot of human interactions. Due to the high degree of variability in raw materials, high reliability on human knowledge and interactive behaviour of the textile materials, it is difficult to predict the performance of the manufacturing process. Statistics and Analytics is applied right from identifying defective materials, colour matching and to have control on process parameters. Artificial Neural Network (ANN) is used in analysing defective fabrics, prediction of raw material properties, optimizing the manufacturing processes and clothing sensory comfort. Multi-Layer Back Propagation technique is used to train the ANN to best identify the defects from the images. Analytics and Statistics has tremendously changed the traditional way of pattern inspection by using numerous images of fabrics to analyze the fabric for weaving, knitting, finishing etc., Artificial Intelligence (AI) enabled color tolerating method is used for rendering colours within the acceptable limits to the fabrics. Karl Pearson Institute has supported textile companies to achieve sustainable production by helping them in optimum utilization of resources, decrease the consumption of water and energy thereby resulting in reduction of pollution of the environment.