Evaluating and controlling silicon wafer slicing quality using fuzzy analytical hierarchy and sensitivity analysis

Twelve-inch wafer slicing is the most challenging process in semiconductor manufacturing yield. This study applies the fuzzy analytic hierarchy process (FAHP) not only to construct the multi-criteria decision problem and determine criteria weights, but also to assess the expected contributions of alternatives to previously defined objectives. Therefore, the fuzzy AHP-based proposed algorithm is applied to select evaluation outcomes and evaluate the precision of optimal performing machines. Additionally, 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. Finally, sensitivity analysis is conducted to test the stability of the priority ranking and help online engineers understand multi-criteria decision scenarios that reflect alternative future developments or different perspectives regarding the relative importance of the criteria.

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