caa a22 4500 605469946 CHVBK 20210128100325.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00500-014-1321-x doi (NATIONALLICENCE)springer-10.1007/s00500-014-1321-x Failure mode and effects analysis using intuitionistic fuzzy hybrid TOPSIS approach [Elektronische Daten] [Hu-Chen Liu, Jian-Xin You, Meng-Meng Shan, Lu-Ning Shao] Failure mode and effects analysis (FMEA) is an effective reliability analysis technique used to identify and evaluate potential failures in systems, products, processes, and/or designs. In traditional FMEA, prioritization of failure modes is carried out by utilizing risk priority numbers (RPNs), which can be acquired by the multiplication of three risk factors: occurrence (O), severity (S) and detection (D). However, there are some inherent deficiencies in the conventional RPN method, which affect its effectiveness and thus limit its applications. In response, this paper introduces a new modified TOPSIS method, named intuitionistic fuzzy hybrid TOPSIS approach, to determine the risk priorities of failure modes identified in FMEA. Moreover, both the subjective and objective weights of risk factors are taken into consideration in the process of risk and failure analysis. A product example of the color super twisted nematic is presented at last to demonstrate the potential applications of the proposed approach, and the merits are highlighted by comparing with some existing methods. Springer-Verlag Berlin Heidelberg, 2014 Failure mode and effects analysis nationallicence Intuitionistic fuzzy set nationallicence OWA operator nationallicence Modified TOPSIS nationallicence Liu Hu-Chen School of Economics and Management, Tongji University, 1239 Siping Road, 200092, Shanghai, People's Republic of China aut You Jian-Xin School of Economics and Management, Tongji University, 1239 Siping Road, 200092, Shanghai, People's Republic of China aut Shan Meng-Meng School of Management, Shanghai University, 200444, Shanghai, People's Republic of China aut Shao Lu-Ning School of Economics and Management, Tongji University, 1239 Siping Road, 200092, Shanghai, People's Republic of China aut Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 1085-1098 1432-7643 19:4<1085 2015 19 500 https://doi.org/10.1007/s00500-014-1321-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1321-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Liu Hu-Chen School of Economics and Management, Tongji University, 1239 Siping Road, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- You Jian-Xin School of Economics and Management, Tongji University, 1239 Siping Road, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Shan Meng-Meng School of Management, Shanghai University, 200444, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Shao Lu-Ning School of Economics and Management, Tongji University, 1239 Siping Road, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 1085-1098 1432-7643 19:4<1085 2015 19 500