Analytic network process decision-making to assess slicing machine in terms of precision and control wafer quality

Authors:
Che-Wei Chang;Cheng-Ru Wu;Huang-Chu Chen
Affiliations:
Department of Information Management, Yuanpei University, 306 Yuanpei Street, Hsin Chu 30015, Taiwan, Republic of China;Department of Finance, Yuanpei University, 306 Yuanpei Street, Hsin Chu 30015, Taiwan, Republic of China;Department of Business Administration, National Dong Hwa University, 1, Sec. 2, Da Hsueh Road, ShouFeng, Hualien 97401, Taiwan, Republic of China
Venue:
Robotics and Computer-Integrated Manufacturing
Year:
2009

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Abstract

We discuss and develop a manufacturing quality yield model to forecast the 12in silicon wafer slicing based on an analytic network process (ANP) framework. The ANP is a general theory of relative measurement used to derive composite-priority-ratio scales from individual-ratio scales that represent the relative influence of factors that interact with respect to the control criteria. Through its supermatrix, which is composed of matrices of column priorities, the ANP framework captures the outcome of dependence and feedback within and between clusters of factors. Additionally, the proposed algorithm can select the evaluation outcomes to identify the optimal machine of precision. Finally, results of the EWMA control chart and Process Capability Indices demonstrate the feasibility of the proposed ANP-based algorithm in effectively selecting the evaluation outcomes and in evaluating the precision of the optimal performing machines. We illustrate how the ANP model implemented for helping the engineer can find out the manufacturing process yield quickly and effectively.