Visualizing the Yield Pattern Outcome for Automatic Data Exploration

Abstract

Non close loop manufacturing process, typically in the hard disk media industries rely from its inspection machine to generate production yield temporal data that can be used for future analysis. In order for an engineer to proactively perform maintenance on its process equipment and avoiding unnecessary unplanned down time, they need to be able to predict the outcome of the yield before products arrives at the inspection machine. The future prediction of the yield outcome can be achieved by visualizing the historical data pattern generated from the inspection machine, transform the data pattern and map it into machine learning algorithm for training in order to automatically generate a prediction model without the visual interpretation needs to be done by human.