Including time dependency and ANOVA in decision-making using the revised fuzzy AHP: A case study on wafer fabrication process selection

Authors:
Harish C. Rajput;Abbas S. Milani;Andrew Labun
Affiliations:
School of Engineering, University of British Columbia, Okanagan Campus, BC, Canada;School of Engineering, University of British Columbia, Okanagan Campus, BC, Canada;School of Engineering, University of British Columbia, Okanagan Campus, BC, Canada
Venue:
Applied Soft Computing
Year:
2011

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Abstract

In the process of decision-making, sometimes analysts are given a sub-set of criteria for which statistical data are available from experiments, whereas for some other criteria, only qualitative judgments can be made. In such situations, it is important to consider the weights of experimental criteria along with the decision maker's qualitative weights. Furthermore, in complex decision scenarios, one may need to consider the time notion and evaluate the behavior of alternatives over time, before making a final decision. This article using the revised fuzzy analytic hierarchy process (AHP) introduces a new decision process to include (1) time dependency of decisions and (2) statistical weighting from the standard analysis of variance (ANOVA). The application of the method is shown via a case study in the selection of wafer slicing and coating process for a three-year operation time. A signal-to-noise metric has been adapted to differentiate among alternatives that swap ranks over time. The method is straightforward and can be adapted to other multiple criteria decision making (MCDM) models.