TY  - JOUR
AB  - This study describes a novel algorithm for optimizing the quality yield of silicon wafer slicing. 12 inch wafer slicing is the most difficult in terms of semiconductor manufacturing yield. As silicon wafer slicing directly impacts production costs, semiconductor manufacturers are especially concerned with increasing and maintaining the yield, as well as identifying whey yeilds decline. The criteria for establishing the proposed algorithm are derived from a literature review and interviews with a group of experts in semiconductor manufacturing. The modified Delphi method is then adopted to analyze those results. The proposed algorithm also incorporates the analytic hierarchy process (AHP) to determine the weights of evaluation. Additionally, the proposed algorithm can select the evaluation outcomes to identify the worst machine of precision. Finally, results of the exponential weighted moving average (EWMA) control chart demonstrate the feasibility of the proposed AHP‐based algorithm in effectively selecting the evaluation outcomes and evaluating the precision of the worst performing machines. So, through collect data (the quality and quantity) to judge the result by AHP, it is the key to help the engineer can find out the manufacturing process yield quickly effectively.
VL  - 7
IS  - 2
SN  - 1598-2688
DO  - 10.1108/15982688200600021
UR  - https://doi.org/10.1108/15982688200600021
AU  - Lin Chin‐Tsai
AU  - Chang Che‐Wei
AU  - Wu Cheng‐Ru
AU  - Chen Huang‐Chu
PY  - 2006
Y1  - 2006/01/01
TI  - Online Experts Screening the Worst Slicing Machine to Control Wafer Yield via the Analytic Hierarchy Process
T2  - Asian Journal on Quality
PB  - Emerald Group Publishing Limited
SP  - 141
EP  - 156
Y2  - 2024/04/26
ER  -