Workpiece Quality Prediction for Gear Hobbing based on Sensor Data

In gear hobbing, as in other soft machining processes, it is essential to maintain the required workpiece quality to avoid rejects or increased rework. To track the workpiece quality, the manufactured gears usually have to be measured on a measuring machine. In order to ensure workpiece quality even with long measuring intervals, process monitoring offers an approach to check the gear quality already during the manufacturing process. In this report, the potential of acceleration data with regard to the assessment of workpiece quality is investigated. In this investigation, both analytical and artificial intelligence based methods are considered.