Siltronic AG is a global technology leader in the semiconductor wafer industry. This presentation will introduce the Siltronic AG approach to preparing batch process data for modeling with JMP Pro. It will demonstrate some interactive steps to clean and rearrange the dataset before modeling using an anonymized dataset containing both historical and experimental batch data. Once the best model algorithm is found, the boosted tree model will be tuned.
The Siltronic AG team found that a technically sound model may be physically worthless, meaning it had been overfitted. Therefore, the team started with a large set of factors, gradually reducing the factor list and testing the model's behavior to find the most effective factors (step backward strategy for a boosted tree in a small JSL routine). The last step provided the best insight into which levers are the strongest to optimize the process.