Fault detection and classification in etch tools



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Texas Tech University


During my 18-month tenure as a coop engineer in the Advanced Process Control module and the Etch module at Advanced Micro Devices, 1 played an important role in the advanced process control mechanism. The objective of my thesis project report is to explain the features and benefits of the fault detection and classification mechanism, with illustrations of its advantages in the etch module ofFab 25 AMD.

Advanced process control (APC) is a novel technique in the semiconductor industry. The crux of APC is that some wafer defects do not get detected until the end of the manufacturing process and that the health of a piece of equipment is an indicator of the quality of the product it produces. Since any adverse change in the tool health would have a negative impact on product quality, it would be possible to immediately detect a wrongly processed wafer and take corrective actions, by monitoring equipment health.

Using a unique model-based technique, real-time monitoring mechanism, and efficient classification strategies, the FDC Department at AMD has made it possible to accurately determine the health of a piece of equipment in real-time. Equipment-related problems are immediately revealed when the equipment health falls outside a statistically derived limit, which is calculated fi-om in-process data when the equipment is healthy and operating normally.

The report gives an idea about my specific roles as a coop engineer, scaling different proportions in various steps of the FDC implementation mechanism. The steps involved in the setting up of the FDC mechanism and the continuous real-time monitoring of the etch plasma stripper processes have been clearly outlined and a few instances of potential faults detected through FDC have also been explained. Current shortcomings and suggestions regarding future enhancements to the existing FDC mechanism have also been presented.