Online Experts Screening the Worst Slicing Machine to Control Wafer Yield via the Analytic Hierarchy Process

Online Experts Screening the Worst Slicing Machine to Control Wafer Yield via the Analytic... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Journal on Quality Emerald Publishing

Online Experts Screening the Worst Slicing Machine to Control Wafer Yield via the Analytic Hierarchy Process

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Publisher
Emerald Publishing
Copyright
Copyright © 2006 Emerald Group Publishing Limited. All rights reserved.
ISSN
1598-2688
DOI
10.1108/15982688200600021
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Asian Journal on QualityEmerald Publishing

Published: Aug 21, 2006

Keywords: Silicon wafer slicing; Modified Delphi method; Analytical hierarchy process; EWMA control chart

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