Optimum Shirt Design Prediction Tool for Apparel Industry

Abstract

Abstract: The apparel industry is one of the world’s major upcoming trends of industrial, economical science. Apparel industry has interconnected design producing and manufacturing issues have become a greater concern. In the domain of apparel product manufacturing and marketing optimization and prediction the design has played a significant part of increasing productivity, overall profit, the consumer demand, and requirements towards the actual factory. Industry has been challenged over and over before adapted by adopting new methods of designing and predict the optimum garment based on the past records and analytical data sets. In my study Time series Analysis and the trained model is used to determine and predict the optimal product under various production constraints. Time Series Analysis is one of the most accurate data analysis and forecasting technique and it is widely used in this research works. There are various kinds of both the traditional statistical methods and the more advanced artificial intelligence (AI) techniques that have been used in various existing systems in relevant to this domain. Both those methods may suffer considerable drawbacks in which the former’s performance depend highly on the time series data’s features whereas the latter ones are slow. Hence there need to pay attention for development of an intelligent time series forecasting system which is fast, versatile and can achieve a reasonably high accuracy. Anyhow with the development of computer technology, automated apparel management systems and Machine Learning models are latest popular, especially in products classification and prediction. The proposed work provides analytical inferences from historical data of sales records for apparel industry and modelling them using time series analytics to make effective decisions by predicting and visualizing.