Affiliations: [a]
Department of Management Sciences, R.O.C. Military Academy, Kaohsiung, Taiwan
| [b]
Department of Industrial Engineering and Management, Fortune Institute of Technology, Kaohsiung, Taiwan
| [c]
Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan
Correspondence:
[*]
Corresponding author. Kuei-Hu Chang, Department of Management Sciences, R.O.C. Military Academy, Kaohsiung 830, Taiwan. Tel./Fax: +886 7 7403060; E-mail: [email protected].
Abstract: Risk assessment is a critical part of reliability engineering and is vital to the success of an enterprise’s performance. Traditionally, risk assessment has used the risk priority number (RPN) to evaluate the risk of failure. Unfortunately, the traditional RPN method has several shortcomings— it loses partially valuable information when some data are missing or nonexistent and does not consider the ordered weight between the severity, occurrence, and detection indicators; further, it does not consider the direct and indirect relationships between failure modes and causes of failure, and it has a high duplication rate. To resolve these issues, this paper integrates the ordered weighted geometric (OWG) operator and hesitant fuzzy linguistic term sets to increase the effectiveness of failure mode and effects analysis (FMEA), named soft FMEA. An empirical case of extreme low-k (ELK) dielectric integration is used to illustrate the proposed method and demonstrate its value. Our results show that the soft FMEA method is applicable to real-world situations and constitutes a more general FMEA method.
Keywords: Soft failure mode and effects analysis, ordered weighted geometric, decision
making trial and evaluation laboratory, extreme low-k dielectric integration, hesitant fuzzy linguistic
term sets
