In the mask data preparation (MDP) flow, it is necessary to verify that layout structures are correctly placed and that specific critical dimensions (CDs) are correct. Certain layout versions of Electrical Test (ETest) structures are placed throughout various locations of the frame data which will be sent for fracture and mask production. Within each ETest structure, there are many sub-structures and gauge points where we want to verify dimensions and locations in the post fractured data. The current preparation flow being employed is error-prone and time-consuming, considering that the entire verification process is done manually. To address this issue, we have utilized a novel pattern search methodology that can measure and report gauge locations relative to unique identifier pattern locations which can all be reviewed graphically on the actual mask data. A full inspection point kit is first generated by a developer using automation scripts which allow graphical gauge definitions relative to a unique identifier pattern per ETest location. A revision-controlled pattern library is created to define the test patterns to be measured based on the technology product. A user can then take this kit and run all post-fracture reporting of ETest structures per tape-out. Correspondence with the mask shop is also simplified and discrepancies are easily verified. In this paper, we will discuss in greater detail how this pattern-based approach and the utilization of pattern libraries help us in significantly reducing the possible errors and verification time. We will also review how the entire process which includes the location measurement and the reporting structure to the mask shop can be fully automated, hence, improving the productivity and the turn-around-time for the mask manufacturing process.
The goal of a foundry partner is to deliver high quality silicon product to its customers on time. There is an assumed trust that the silicon will yield, function and perform as expected when the design fits all the sign-off criteria. The use of Intellectual Property (IP) blocks is very common today and provides the customer with pre-qualified and optimized functions for their design thus shortening the design cycle. There are many methods by which an IP Block can be generated and placed within layout. Even with the most careful methods and following of guidelines comes the responsibility of sign-off checking. A foundry needs to detect where these IP Blocks have been placed and look for any violations. This includes DRC clean modifications to the IP Block which may or may not be intentional.
Using a pattern-based approach to detect all IP Blocks used provides the foundry advanced capabilities to analyze them further for any kind of changes which could void the OPC and process window optimizations. Having any changes in an IP Block could cause functionality changes or even failures. This also opens the foundry to legal and cost issues while at the same time forcing re-spins of the design.
In this publication, we discuss the methodology we have employed to avoid process issues and tape-out errors while at the same time reduce our manual work and improve the turnaround time. We are also able to use our pattern analysis to improve our OPC optimizations when modifications are encountered which have not been seen before.
Mask inspection is a critical step in the mask manufacturing process in order to ensure all dimensions printed are within the needed tolerances. This becomes even more challenging as the device nodes shrink and the complexity of the tapeout increases. Thus, the amount of measurement points and their critical dimension (CD) types are increasing to ensure the quality of the mask. In addition to the mask quality, there is a significant amount of manpower needed when the preparation and debugging of this process are not automated. By utilizing a novel pattern search technology with the ability to measure and report match region scan-line (edge) measurements, we can create a flow to find, measure and mark all metrology locations of interest and provide this automated report to the mask shop for inspection. A digital library is created based on the technology product and node which contains the test patterns to be measured. This paper will discuss how these digital libraries will be generated and then utilized. As a time-critical part of the manufacturing process, this can also reduce the data preparation cycle time, minimize the amount of manual/human error in naming and measuring the various locations, reduce the risk of wrong/missing CD locations, and reduce the amount of manpower needed overall. We will also review an example pattern and how the reporting structure to the mask shop can be processed. This entire process can now be fully automated.
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