Back-propagation ANN to Predict Cleanliness and Quality of Cotton Spinning Preparatory Output: A Comprehensive Research - Shaikh, Tasnim N.; Pujara, Hardik (Recent Patents on Engineering, 2024)
Background: Modern spinning preparatory has undergone drastic technological changes, but still, individual’s expertise-based decisions govern the complex and non-linear multivariant relationships prevailing amongst raw material (cotton) variables, machine variables, process variables (waste), and product (card sliver) quality. The scientifically precise prediction regarding the cleanliness and quality of card sliver and waste control for the given inputted cotton variables processed on the state-of-the-art machinery setup without waiting for the production and testing of card sliver is still impossible. Methods: The present work describes the use of Aritificial Neural Networks (ANN) for ruling out these limitations on scientific grounds. Previous research and patents were reviewed. A complex system targeted at ANN was developed using the
Keywords: Neps/gm