Data analytics is being used in a variety of industries to gain insights into the underlying information. These insights can help extract meaningful information from the vast amount of data. Large amounts of data are also being generated by various sensors within roll-to-roll manufacturing machines. This information can be used to improve process efficiency and to reduce waste. However the problem is that the amount of data is overwhelming and there are no methods available to discern the data. This paper will demonstrate the use of data analytics for roll-to-roll manufacturing with some application examples. Detection of some common issues such as flutter, wrinkles/creases, splices, necking, etc., based on the raw data collected from sensors will be shown in this paper.