Efficient Signal Transport Model for Remote Thermometry in Full-Scale Thermal Processing Systems

The rapid thermal processing of semiconductor devices is very temperature sensitive and requires precise temperature measurement. Light pipe radiation thermometers are widely used for temperature control during manufacturing by industry, and there is concern about errors associated with light pipe measurements. Modeling in simplified systems has helped in understanding the signal transport process in light pipes and errors associated with measurements in the past. Considering the small sensor area compared to the size of the semiconductor wafer and the remaining system components, modeling of the complete system has not been done due to the computational demand. A reverse Monte Carlo model can be used efficiently to model the signal transported to the photodetector in conjunction with a thermal model of the system to better characterize the system. The proposed method is demonstrated in a full-scale instrumented system with a light pipe thermometer, and the results are compared against previously published measurements from the system.