Forest & Wildlife Research Center Publications and Scholarship
Abstract
It is vital to have an exclusive modification in semiconductor production process because of meeting differentiated customer demands in dynamic and competitive global minuscule semiconductor technology market and the highly complex fabrication process. In this paper, we propose a control system based on the dynamic mixed-effect least-square support vector regression (LS-SVR) control system for overlay error compensation with stochastic metrology delay to minimize the misalignment of the patterning process. Moreover, for the stability of the control system in the presence of metrology delay and to deal with nonlinearity among the overlay factors, the novel Lyapunov-based kernel function is merged with the LS-SVR controller. The proposed controller's operation has been validated and implemented by a major semiconductor manufacturer in Taiwan. The experiments are verified that mixed-effect LS-SVR controller has the higher validity and higher efficiency in comparison with the exponentially weighted moving average (EWMA) and threaded EWMA controllers which had been previously implemented at the company or applied in similar studies. Note to Practitioners—Due to high production complexity in semiconductor manufacturing process, a meticulous and intelligent process control is needed to achieve higher throughput and customer satisfaction. Monitoring a complex system is challenging because the process components and variables operate autonomously and interoperate with other manufacturing segments. This paper proposes a novel run-to-run (R2R) control system to compensate the overlay error during the photolithography process that efficiently deals with the high-mixed manufacturing environment and metrology delay.
Publisher
IEEE Transactions on Automation Science and Engineering
DOI
10.1109/TASE.2019.2894668
Publication Date
2-19-2019
College
James Worth Bagley College of Engineering
Department
Department of Industrial and Systems Engineering
Keywords
high-mixed process, intelligent manufacturing, Lyapunov stability, metrology delay, overlay error, photolithography process, recipe-based system, support vector regression (SVR)
Recommended Citation
Khakifirooz, Marzieh; Chien, Chen-Fu; and Fathi, Mahdi, "Compensating Misalignment Using Dynamic Random-Effect Control System: A Case of High-Mixed Wafer Fabrication" (2019). Forest & Wildlife Research Center Publications and Scholarship. 1.
https://scholarsjunction.msstate.edu/fwrc-publications/1