Data science and machine learning are integral parts of most large-scale product manufacturing processes and are used to understand customer needs, detect quality issues, automate repetitive tasks and optimise supply chains. It’s an invisible glue that helps us produce more things for less, and in a timely fashion. To learn more about this fascinating topic, I recently spoke to Ranga Ramesh who is Senior Director, Quality Innovation and Transformation at Georgia-Pacific. Georgia-Pacific is one of the world’s largest manufacturers of consumer paper products and uses AI technologies throughout their manufacturing process. In this episode of Leaders of Analytics, we explore how computer vision and machine learning can be used to classify tissue paper softness and instantly detect quality issues that could otherwise render large volumes of product useless. Ranga’s work is featured as a case study in our recently published book, Demystifying AI for the Enterprise.