Detection of electrical defects with SEMVision in semiconductor production mode manufacturing
In the semiconductor manufacturing process, defects often occur due to a marginal process window that affects the lithography and etch processes. These defects can result in bridging patterns and overlay issues, which consequently cause electrical shorts and partially etched interconnects producing electrical opens. SEM tools are typically used to review electrical failures through voltage contrast techniques. Manufacturers who fabricate with older process technology nodes often times need to use their tool sets more efficiently. This paper demonstrates an application of conventional SEM review with image to golden reference image inspection capabilities in Automatic Process Inspection (API) mode to perform electrical inspections of die features. This paper, a collaborative effort between Applied Materials and Microchip Technology Inc. details how to use a SEM review tool to detect systematic electrical defects. This methodology can prove beneficial while monitoring and developing patterning techniques for a specific design rule. This is done by catching electrical shorts and opens that are more visible at a lower resolution inspection while used in process monitoring. Outcomes of this effort show that conventional SEM review techniques have the capability to effectively and efficiently monitor the fabrication process. To develop this methodology, a SEM review was set up on known areas prone to process inconsistencies derived from features pushing the design rule. The SEM review was implemented in a production setting at process nodes between 100 to 200 nm. There are advantages and disadvantages with using e beam inspection tools. This paper demonstrates that by using a SEM review tool and selecting die locations for imaging that are more likely to fail electrically, SEMVision automatic review capabilities can be used more effectively and efficiently. The application developed may also be applied in fabrication facilities that have limited yield monitoring capacity.
2016 27th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)