Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
A hybrid fuzzy adaptive sampling - Run rules for Shewhart control charts
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Selecting the preferable bancassurance alliance strategic by using expert group decision technique
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Applying fuzzy hierarchy multiple attributes to construct an expert decision making process
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Computers and Industrial Engineering
The coupled method fuzzy-AHP applys to solve multi-criteria decision making problems
WSEAS Transactions on Mathematics
Fuzzy hierarchy sensitive with Delphi method to evaluate hospital organization performance
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Application of analytic hierarchy process in just-in-time manufacturing systems: a review
International Journal of Data Analysis Techniques and Strategies
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Selection of Concrete Production Facility Location Integrating Fuzzy AHP with TOPSIS Method
International Journal of Productivity Management and Assessment Technologies
Hi-index | 12.06 |
Silicon wafer slicing is an increasingly complex manufacturing process. This involves high purity levels, crystallographic perfection and precise mechanical tolerances, thus 12in. 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 why yields decline. The criteria for establishing the proposed algorithm are derived from literature review and modified Delphi method in semiconductor manufacturing. The main objective of this paper is to propose a new approach within the AHP framework for tackling the uncertainty and imprecision of silicon wafer slicing evaluations during manufacturing process stages, where the decision-maker's comparison judgments are represented as fuzzy triangular numbers. Additionally, the proposed algorithm can select the evaluation outcomes to identify the worst machine of precision. Finally, results of EWMA control chart demonstrate the feasibility of the proposed fuzzy 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 fuzzy AHP, it will the key to help the engineer can find out the manufacturing process yield quickly effectively.