This study aims to perform the micro-/nano-machining with an atomic force microscopy (AFM) tip in a scanning electron microscope (SEM) via run-to-run (R2R) controller and digital image feedbacks. The R2R is assisted by the technique of exponentially weighted moving average (EWMA). This "EWMA feedback" controller is a popular R2R control scheme, which primarily uses data from past process runs to adjust settings for the next run. On the other hand, the digital images are obtained by using the wavelet transform and binarization in order to recognize machining results, and then return feedback of the digital image information to the controller; finally obtain the next input data for the actuating controller to achieve the targeted machining precision. The experimental results for preliminary machining in micro-level indicate that the EWMA controller based on image feedbacks performs with satisfactory results at reducing the process variation, particularly at the first few production runs, thereby making it possible to further reduce the bias and bring the process output closer to its target as soon as the process begins to operate. It is seen that the proposed EWMA controller with digital image feedbacks is easy to implement and provides a good approximation to the optimal variable discount factor, which can reduce the error of the machining process from initial 40% without control to 0.7% with the proposed R2R. More importantly, such a reduction can be achieved at no loss of long-term stability. With sure precision of AFM, the aforementioned resulted micro-machining precision can easily be extended to nano-levels. Therefore, this study demonstrates a successful micro-/nano-machining operation in the environment of a SEM, by employing the designed R2R controller with digital image feedbacks.
- Image recognition
- Run-to-run (R2R) control
- Scanning electron microscope (SEM)