Paper
2 June 2000 Modular monitoring for the photolithography environment
Author Affiliations +
Abstract
The following paper describes a modular monitoring approach for the photolithography environment, which takes individual measurements and generates three-level monitor. This method is aiming to simplify the process monitoring activity and make it more constructive. The basic monitoring level consists of Normalized indexes for each cell (cluster) -- each raw measurement is transformed into a value between 0 and 1. Second level is Cell index that unites all the Normalized indexes of each cell into one index. The upper level is the Photo index, which combine all the Cell indexes into one parameter. The concept that underlies this approach has few levels. The process engineers that monitor the equipment and process can use the Cell index as a qualitative tool for viewing the current general state of each cell and follow trends. When degradation is observed the Normalized indexes will be used for targeting the source of the degradation. The Photo index and the Cell index will also allow the management personnel to easily track the overall performance of the photolithography equipment and process, and achieve long term improvement by defining goals for the Cell and Photo indexes. The paper describes different options for generating each index in order to manipulate its sensitivity to the characteristic behavior of each individual measured parameter. Additionally, experimental data is presented to demonstrate the performance of the suggested methodology. The raw data is based on more than 120 individual parameters obtained from eight clusters.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amir Wachs "Modular monitoring for the photolithography environment", Proc. SPIE 3998, Metrology, Inspection, and Process Control for Microlithography XIV, (2 June 2000); https://doi.org/10.1117/12.386509
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KEYWORDS
Optical lithography

Environmental monitoring

Contamination

Semiconductors

Statistical analysis

Tolerancing

Environmental sensing

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