An Adjustment Strategy for Tilted Moiré Fringes via Deep Q-Network

• Published in: Photonics 2024-07, Vol.11 (7), p.666
• Main Authors: Jin, Chuan, Yu, Dajie, Sun, Haifeng, Liu, Junbo, Zhou, Ji, Wang, Jian
• Format: Article
• Language: English
• Subjects: Accuracy; Adaptive algorithms; Algorithms; Alignment; Artificial neural networks; Attitude (inclination); Deep learning; deep reinforcement learning; Deviation; Environment models; Environmental modeling; Leveling; Light; lithography; Methods; Misalignment; Moire fringes; Moiré fringe; Motion perception; Neural networks; Optimization; Position measurement
• ISSN: 2304-6732; 2304-6732
• DOI: 10.3390/photonics11070666

Overlay accuracy, one of the three fundamental indicators of lithography, is directly influenced by alignment precision. During the alignment process based on the Moiré fringe method, a slight angular misalignment between the mask and wafer will cause the Moiré fringes to tilt, thereby affecting the alignment accuracy. This paper proposes a leveling strategy based on the DQN (Deep Q-Network) algorithm. This strategy involves using four consecutive frames of wafer tilt images as the input values for a convolutional neural network (CNN), which serves as the environment model. The environment model is divided into two groups: the horizontal plane tilt environment model and the vertical plane tilt environment model. After convolution through the CNN and training with the pooling operation, the Q-value consisting of n discrete actions is output. In the DQN algorithm, the main contributions of this paper lie in three points: the adaptive application of environmental model input, parameter optimization of the loss function, and the possibility of application in the actual environment to provide some ideas. The environment model input interface can be applied to different tilt models and more complex scenes. The optimization of the loss function can match the leveling of different tilt models. Considering the application of this strategy in actual scenarios, motion calibration and detection between the mask and the wafer provide some ideas. To verify the reliability of the algorithm, simulations were conducted to generate tilted Moiré fringes resulting from tilt angles of the wafer plate, and the phase of the tilted Moiré fringes was subsequently calculated. The angle of the wafer was automatically adjusted using the DQN algorithm, and then various angles were measured. Repeated measurements were also conducted at the same angle. The angle deviation accuracy of the horizontal plane tilt environment model reached 0.0011 degrees, and the accuracy of repeated measurements reached 0.00025 degrees. The angle deviation accuracy of the vertical plane tilt environment model reached 0.0043 degrees, and repeated measurements achieved a precision of 0.00027 degrees. Moreover, in practical applications, it also provides corresponding ideas to ensure the determination of the relative position between the mask and wafer and the detection of movement, offering the potential for its application in the industry.