The worst ill-conditioned silicon wafer slicing machine detected by using grey relational analysis

In the silicon slicing process, machine vibrations and the unstable wire knife motion cause the slicing precision to drift, or other ill-conditions. This process involves several synchronously occurring multiple quality characteristics, such as thickness (THK), bow, warp, total indicator reading (TIR), and total thickness variation (TTV), which must be closely monitored and controlled. In this research, grey relational analysis (GRA) is applied to prevent an ill-conditioned wire saw machine from producing an unconfirmed product that is screened from the synchronously occurring multiple quality characteristics. Five weights of those characteristics are determined by an entropy method. Finally, a case study and the exponential weighted moving average (EWMA) control chart are presented to demonstrate and verify the feasibility and effectiveness of the proposed method.