An application of AHP and sensitivity analysis for selecting the best slicing machine
Computers and Industrial Engineering
Using AHP and TOPSIS approaches in customer-driven product design process
Computers in Industry
Mathematics and Computers in Simulation
Measuring relative performance of wafer fabrication operations: a case study
Journal of Intelligent Manufacturing
Review: A state-of the-art survey of TOPSIS applications
Expert Systems with Applications: An International Journal
Journal of Intelligent Manufacturing
A SCOR based approach for measuring a benchmarkable supply chain performance
Journal of Intelligent Manufacturing
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The yield of the wafer slicing process has the greatest impact on manufacturing costs in the fabrication of photovoltaic (PV) cells. Hence, it is critical to identify the correct type of wire saw for this process. This paper employs the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS) to construct a collaborative decision model for predicting the yield of a wire saw. The evaluation criteria for establishing the model are derived on the basis of a literature review and the opinions of experts with experience in PV wafer manufacturing. The evaluation weights are determined by the AHP and the optimal machine is identified by the TOPSIS. Finally, process capability indices are presented to demonstrate and verify the feasibility and effectiveness of the proposed method.