Predictive modeling for the management of consumable optics in a lithographic system

Christopher Conley

doi:10.1117/12.659117

15 March 2006 Predictive modeling for the management of consumable optics in a lithographic system

Christopher Conley

Proceedings Volume 6155, Data Analysis and Modeling for Process Control III; 61550N (2006) https://doi.org/10.1117/12.659117
Event: SPIE 31st International Symposium on Advanced Lithography, 2006, San Jose, California, United States

Abstract

High Volume Manufacturing (HVM) environments require that equipment have high availability, low cost of ownership, and minimizes events that can cause product defects. With a scheduled proactive maintenance program for consumables, the impact to manufacturing schedules is minimized while maintaining the ability of the tool to create "good" product, and down time due to troubleshooting is reduced. In photolithography, consumable optics provide a large opportunity for instituting this type of program, since optical degradation is very well understood having known causes such as chemical contamination, manufacturing defects and physical effects. These effects can either be reversed or compensated for via optics cleaning, parts replacement or counter-measures such as optical adjustments, optical filters, or tool modifications. Traditionally the lifetime of optics in described in terms of the number of pulses through the optic. This pulse limit is based on modeling and reflects the usage of the machine. There are several disadvantages to using this method, including unnecessarily changing parts prior to failure, or alternately, premature parts failure. Performance-based modeling can solve most issues associated with usage-based models; however, there are also challenges related to performance-based modeling that must be overcome to make the model useful. These include forecasting usage rates, degradation mode signature, and determining thresholds to allow for efficient parts ordering. Nikon has developed a preliminary model to automate performance-based forecasting that takes all of these challenges into account, and with further optimization this model can be implemented successfully providing a reduction in consumables related Cost of Ownership.

Citation Download Citation

Christopher Conley "Predictive modeling for the management of consumable optics in a lithographic system", Proc. SPIE 6155, Data Analysis and Modeling for Process Control III, 61550N (15 March 2006); https://doi.org/10.1117/12.659117

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KEYWORDS

Optics manufacturing

Performance modeling

Contamination

Manufacturing

Data modeling

Lithography

Lead

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