Abstract: Aiming at the wafer thinning process in memory card products' stacked package in its quality control and efficiency improvement, a basic problem in the wafer thinning process is presented by the variation for the measurement of the wafer thinning process. It is critical to monitor the process to detect process changes and further diagnose the process to determine the root causes of the changes. Firstly, a time series ARMA(autoregressive moving average)model has been built on analyzing the equipment productive throughput and operation time between failures data from the factory. The analysis is useful in problem prediction and maintenance. Then, through multiscale estimation theory, the detail coefficients of the data model have been derived. At last, the use of the method is discussed and an example is given. The experimental results reveal that the standard deviation changes of this manufacturing process have been detected in the 95% by CUSUM(cumulative sum)control chart on the detail coefficients of the model, which means the measurement of the wafer thinning process will be worse in the near future.

Key words: wafer thinning process, ARMA(autoregressive moving average model), multiscale estimation theory, CUSUM(cumulative sum), standard deviation change