We developed a statistical method that can be applied to overlay metrology tools to improve performance and time-to-results (TTR) of multi-cycle optimization based on the brute force method. First, we evaluated full response surfaces for each combination of the discrete equipment settings and calculated desirability scores using a normalization function. Second, we combined gradient optimization techniques and response surface methodologies to find the important local maxima (center of the islands in quadratic contour) and stationary response points. Once all the stationary response points have been identified, users can choose to rank the solutions by quality or can choose to use analysis of variance (ANOVA) methods to determine which main effects and/or interactions are of interest. Two separate layers were evaluated and compared to the process of reference (POR) brute force method of optimization. Results showed that the best residuals values from recipes optimized using 1-cycle SPOC-based automatic recipe optimization (ARO) and ARO based on the 2- cycle Brute-Force strategy were comparable to known residuals values from the POR recipes. Moreover, SPOC-based ARO was performed with a TTR of under 2 hours, while a 2-cycle Brute-Force ARO typically took 6~ 20 hours depending on specific configurations. The vast reduction in optimization time is primarily attributed to the elimination of multi-cycle refinement, whose data collection dominated the previously observed TTR. In conclusion, we demonstrated the ability to reduce time to solution by a factor of 3 while maintaining or improving on overlay residuals compared to existing brute force methodologies.
As semiconductor technology nodes keep shrinking, ever-tightening on-product overlay (OPO) budgets coupled with continuous process development and improvement make it critical to have a robust and accurate metrology setup. Process monitoring and control is becoming increasingly important to achieve high yield production. In recently introduced advanced overlay (OVL) systems, a supercontinuum laser source is applied to facilitate the collection of overlay spectra to increase measurement stability. In this paper, an analysis methodology has been proposed to couple the measured overlay spectra with overlay simulation to extract exact process information from overlay spectra. This paper demonstrates the ability to use overlay spectra to capture and quantify process variation, which in turn can be used to calibrate the simulation stacks used to create the SCOL (scatterometry-based overlay) and AIM overlay metrology targets, and can be fed into the fab for process monitoring and improvement.
Shrinking on-product overlay (OPO) budgets in advanced technology nodes require more accurate overlay measurement and better measurement robustness to process variability. Pupil-based accuracy flags have been introduced to the scatterometry-based overlay (SCOL) system to evaluate the performance of a SCOL measurement setup. Wavelength Homing is a new robustness feature enabled by the continuous tunability of advanced SCOL systems using a supercontinuum laser light source in combination with a flexible bandpass filter. Inline process monitoring using accuracy flags allows for detection, quantification and correction of shifts in the optimal measurement wavelength. This work demonstrates the benefit of Wavelength Homing in overcoming overlay inaccuracy caused by process changes and restoring the OPO and residual levels in the original recipe.
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