Advanced Process Control and Statistical Process Control Data for Thickness Prediction of AlCu and WTi Metal Layer in Semiconductor Manufacturing
Authors/Creators
- 1. Faculty of Electrical Engineering University of Sarajevo
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2.
Infineon Technologies (Austria)
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3.
University of Sarajevo
Description
Dataset Description
These datasets are designed to predict the physical properties (thickness) of the AlCu and WTi metal layers after the physical vapor deposition process in semiconductor manufacturing. It is split into X and Y to allow for supervised learning approaches. It is also adaptable for single-value and vector-value, structured output, learning tasks.
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X represents the conditions in the equipment during the process defined within recipes - Advanced Process Control Data.
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Y represents physical measurements and aggregated metrics of layer properties after process - Statistical Process Control Data.
About X (input)
The input dataset consists of aggregated metrics of equipment-internally tracked sensor traces, recording physical parameters such as gas flows, temperatures, voltages and currents. Column names are Sensor_i, where i is the sensor number.
About Y (output)
The output dataset contains physical measurements of thickness on 17 points denoted as RAW_VALUE_t_i, where i is point number.