An application of analytic hierarchy process and sensitivity analysis for selecting the best slicing machine

Wafer slicing is a complex manufacturing process, complicating efforts to monitor process stability and quality control effectively. This study discusses and develops a manufacturing quality yield model for forecasting 12 in. silicon wafer slicing based on the Analytic Hierarchy Process (AHP) framework. Decision makers can select evaluation outcomes to identify the most precise machine. Additionally, EWMA control chart is presented to demonstrate and verify the feasibility and effectiveness of the proposed AHP-based algorithm. Finally, sensitivity analysis is performed to test the stability of the priority ranking. Therefore, this work illustrates how the AHP model would be implemented to help engineers determine the manufacturing process yield quickly and effectively.