| Autor: |
Mark C. Kelling, Bernd Schulz, Jon-Tobias Hoeft, Matthew Sendelbach, William A. Muth, Benjamin Bunday, M. Zaitz, Andrew Brendler, Alok Vaid, Eric P. Solecky, Ron Fiege, Bill Banke, Srinivasan Rangarajan, Carlos Strocchia-Rivera, Andres Munoz, Carsten Hartig, John A. Allgair, Dmitriy Shneyder, Chas Archie |
| Rok vydání: |
2009 |
| Předmět: |
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| Zdroj: |
Metrology, Inspection, and Process Control for Microlithography XXIII. |
| ISSN: |
0277-786X |
| Popis: |
Ever shrinking measurement uncertainty requirements are difficult to achieve for a typical metrology toolset, especially over the entire expected life of the fleet. Many times, acceptable performance can be demonstrated during brief evaluation periods on a tool or two in the fleet. Over time and across the rest of the fleet, the most demanding processes often have measurement uncertainty concerns that prevent optimal process control, thereby limiting premium part yield, especially on the most aggressive technology nodes. Current metrology statistical process control (SPC) monitoring techniques focus on maintaining the performance of the fleet where toolset control chart limits are derived from a stable time period. These tools are prevented from measuring product when a statistical deviation is detected. Lastly, these charts are primarily concerned with daily fluctuations and do not consider the overall measurement uncertainty. It is possible that the control charts implemented for a given toolset suggest a healthy fleet while many of these demanding processes continue to suffer measurement uncertainty issues. This is especially true when extendibility is expected in a given generation of toolset. With this said, there is a need to continually improve the measurement uncertainty of the fleet until it can no longer meet the needed requirements at which point new technology needs to be entertained. This paper explores new methods in analyzing existing SPC monitor data to assess the measurement performance of the fleet and look for opportunities to drive improvements. Long term monitor data from a fleet of overlay and scatterometry tools will be analyzed. The paper also discusses using other methods besides SPC monitors to ensure the fleet stays matched; a set of SPC monitors provides a good baseline of fleet stability but it cannot represent all measurement scenarios happening in product recipes. The analyses presented deal with measurement uncertainty on non-measurement altering metrology toolsets such as scatterometry, overlay, atomic force microscopy (AFM) or thin film tools. The challenges associated with monitoring toolsets that damage the sample such as the CD-SEMs will also be discussed. This paper also explores improving the monitoring strategy through better sampling and monitor selection. The industry also needs to converge regarding the metrics used to describe the matching component of measurement uncertainty so that a unified approach is reached regarding how to best drive the much needed improvements. In conclusion, there will be a discussion on automating these new methods3,4 so they can complement the existing methods to provide a better method and system for controlling and driving matching improvements in the fleet. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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