Comparison of the RAFSI and PIV method in multi-criteria decision making: application to turning processes

Multi-criteria decision-making (MCDM) methods are used in many fields so as to rank alternatives and find the best one. However, rank reversal after adding or removing an alternative can occur in using some of the methods. In this study, two methods RAFSI and PIV were compared for application of mak...

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Bibliographic Details
Main Authors: Trung Do Duc, Thinh Hoang Xuan, Ha Le Dang
Format: Article
Language:English
Published: EDP Sciences 2022-01-01
Series:International Journal of Metrology and Quality Engineering
Subjects:
Online Access:https://www.metrology-journal.org/articles/ijmqe/full_html/2022/01/ijmqe220020/ijmqe220020.html
Description
Summary:Multi-criteria decision-making (MCDM) methods are used in many fields so as to rank alternatives and find the best one. However, rank reversal after adding or removing an alternative can occur in using some of the methods. In this study, two methods RAFSI and PIV were compared for application of making multi-criteria decisions. They are known to be capable of avoiding rank reversal problems. Sixteen 9XC steel turning tests were performed for the experiment. Tool holder length, spindle speed, feed rate and depth of cut are parameters that vary in each test. Three criteria for evaluating the turning process consist of MRR, RE and Ra. Four methods including MEREC, ROC, RS and EQUAL were used for determining weights of the criteria. The blend of two multi-criteria decision making methods (RAFSI and PIV) with four weight-determining methods resulted in eight ranking options. This is a new approach of the study. A positive outcome was reached that all eight ranking options identified the same best test. The best experiment must ensure to have maximum MRR and minimum RE and Ra simultaneously. A detailed discussion of the ranking results in each case was also carried out. Finally, the directions and issues that need to be studied further were pointed out in this paper as well.
ISSN:2107-6847