Process yield analysis for autocorrelation between linear profiles

In many industrial applications, the quality of a process or product can be characterized by a function or profile. Autocorrelation between profiles is becoming increasingly common due to, for example, on-line data collection with high-frequency sampling. Therefore, the basic assumption of independent profiles for process capability analysis is not valid. This paper aims at evaluating the process yield for autocorrelated linear profiles. We present an approximate lower confidence bound for the process-yield index S_{pkA ;AR(1)} when linear profiles follow an autoregressive model AR(1). A simulation study is conducted to assess the performance of the proposed method. The simulation results confirm that the proposed method performs well regarding bias, standard deviation and coverage rate. One simulated example is used to demonstrate the performance of the proposed approach.