Abstract

The selection of welding process is one of the most significant decision making problems and it requires a wide range of information in accordance with the type of product. Hence, the automation of knowledge through a knowledge-based system will greatly enhance the decision-making process. A combined fuzzy data envelopment analysis (DEA) and TOPSIS is proposed to investigate the relative welding process selection factors and it can compare and evaluate different welding processes. The proposed approach compares each decision making unit (DMU) with the worst and the ideal virtual DMU and it ranks them via the relative closeness index. The proposed approach is used for ranking eleven welding processes which are commonly used for repairing nodular cast iron engine block in four cases and it is shown that the approach is sensitive to changes in dataset.

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