A Modified Method for Risk Evaluation in Failure Mode and Effects Analysis Jun-Li Shi 1,2 *, Ya-Jun Wang 1 , Hai-Hua Jin 1 , Shuang-Jiao Fan 1 , Qin-Yi Ma 1 and Mao-Jun Zhou 1 1 School of Mechanical Engineering and Automation, Dalian Polytechnic University, Dalian 116034, P.R. China 2 Institute of Sustainable Design and Manufacturing, Dalian University of Technology, Dalian 116024, P.R. China Abstract This study proposes a modified failure mode and effects analysis (FMEA) method based on fuzzy set theory and fuzzy analytic hierarchy process (FAHP) by analyzing the limitations of the traditional FMEA. First, the fuzzy language set of severity, occurrence, and detection is set up in this method. Second, the failure mode is evaluated by a triangular fuzzy number based on the fuzzy language set. Then, the weights of severity, occurrence, and detection are determined by the FAHP. Finally, the risk priority of the failure modes is determined by the modified risk priority number (RPN). The efficiency and feasibility of the modified FMEA method are verified by using it to deal with risk evaluation of the failure modes for a compressor crankshaft. Key Words: Failure Mode and Effects Analysis, Fuzzy Language Set, Triangular Fuzzy Number, Fuzzy Analytical Hierarchy Process, Risk Priority Number 1. Introduction The failure mode and effects analysis (FMEA), which was first developed as a formal design methodology in the 1960s, is an extensively used risk assessment tool to define and identify potential failures in products, pro- cesses, designs, and services [1]. The FMEA technique has been extensively used in a wide range of industries, such as in the aerospace, automotive, electronics, me- dical and mechanical technology industries [2-5]. In FMEA, prioritization of the failure modes is generally determined through the risk priority number (RPN), which provides an effective method of ranking the fai- lure modes. The traditional RPN is obtained by multiply- ing the occurrence (O), severity (S), and detection (D) of a failure mode, as expressed in Eq. (1): RPN = S ´ O ´ D (1) where, S is the severity of the failure mode, O is the oc- currence of the failure mode, and D is the probability of not detecting the failure mode. The higher the RPN value of a failure mode, the greater the risk for the product/ system. Three risk factors are evaluated by a numeric scale (rating) from 1 to 10 to obtain the RPN of a poten- tial failure mode. Table 1 shows the proposed criteria of the rating for S of a failure mode in the FMEA. The nu- meric scales for O and D follow the same criteria, be- cause of the length limitation no more tautology here. However, the RPN is criticized in most cases as a crisp value because S, O, and D are crisp numbers [6]. The three main reasons for this are the following: First, experts encounter difficulties in giving a precise number for the three risk parameters in the crisp model because FMEA experts’ opinions are mainly subjective and qual- Journal of Applied Science and Engineering, Vol. 19, No. 2, pp. 177-186 (2016) DOI: 10.6180/jase.2016.19.2.08 *Corresponding author. E-mail: [email protected]
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A Modified Method for Risk Evaluation in Failure
Mode and Effects Analysis
Jun-Li Shi 1,2*, Ya-Jun Wang1, Hai-Hua Jin1, Shuang-Jiao Fan1,Qin-Yi Ma1 and Mao-Jun Zhou1
1School of Mechanical Engineering and Automation, Dalian Polytechnic University,
Dalian 116034, P.R. China2Institute of Sustainable Design and Manufacturing, Dalian University of Technology,
Dalian 116024, P.R. China
Abstract
This study proposes a modified failure mode and effects analysis (FMEA) method based on
fuzzy set theory and fuzzy analytic hierarchy process (FAHP) by analyzing the limitations of the
traditional FMEA. First, the fuzzy language set of severity, occurrence, and detection is set up in this
method. Second, the failure mode is evaluated by a triangular fuzzy number based on the fuzzy
language set. Then, the weights of severity, occurrence, and detection are determined by the FAHP.
Finally, the risk priority of the failure modes is determined by the modified risk priority number (RPN).
The efficiency and feasibility of the modified FMEA method are verified by using it to deal with risk
evaluation of the failure modes for a compressor crankshaft.
Key Words: Failure Mode and Effects Analysis, Fuzzy Language Set, Triangular Fuzzy Number,
Fuzzy Analytical Hierarchy Process, Risk Priority Number
1. Introduction
The failure mode and effects analysis (FMEA), which
was first developed as a formal design methodology in
the 1960s, is an extensively used risk assessment tool to
define and identify potential failures in products, pro-
cesses, designs, and services [1]. The FMEA technique
has been extensively used in a wide range of industries,
such as in the aerospace, automotive, electronics, me-
dical and mechanical technology industries [2�5]. In
FMEA, prioritization of the failure modes is generally
determined through the risk priority number (RPN),
which provides an effective method of ranking the fai-
lure modes. The traditional RPN is obtained by multiply-
ing the occurrence (O), severity (S), and detection (D) of
a failure mode, as expressed in Eq. (1):
RPN = S � O � D (1)
where, S is the severity of the failure mode, O is the oc-
currence of the failure mode, and D is the probability of
not detecting the failure mode. The higher the RPN value
of a failure mode, the greater the risk for the product/
system. Three risk factors are evaluated by a numeric
scale (rating) from 1 to 10 to obtain the RPN of a poten-
tial failure mode. Table 1 shows the proposed criteria of
the rating for S of a failure mode in the FMEA. The nu-
meric scales for O and D follow the same criteria, be-
cause of the length limitation no more tautology here.
However, the RPN is criticized in most cases as a
crisp value because S, O, and D are crisp numbers [6].
The three main reasons for this are the following: First,
experts encounter difficulties in giving a precise number
for the three risk parameters in the crisp model because
FMEA experts’ opinions are mainly subjective and qual-
Journal of Applied Science and Engineering, Vol. 19, No. 2, pp. 177�186 (2016) DOI: 10.6180/jase.2016.19.2.08
The TFN here is the measurement of failure mode getting from experts’ experiences and knowledge, for example, (1.0,2.1, 2.6) is the TFN of ‘VL’ for ‘Bad hardness’ getting from NO. 1 expert, in his opinion, the smallest value is 1.0, thebiggest value is 2.6, and the median value is 2.1. The other TFNs are obtained as the same way.
Table 4. Linguistic terms and fuzzy language sets of five failure modes for compressor crankshaft
Potential failure mode analysis
Potential failure mode Consequences of failures Causes of failures S O D
Bad hardness Unstable working performance Serious abrasion of Jigs and fixtures H M LCoaxiality tolerance Unable to install and connect Bad clamping and positioning L VL MInterleaving burr Unstable working performance Worker’s weak quality awareness M L VLSuper size difference Unable to install the connection Error compensation value of tools VH H MCylindricity error Cause the device to the cutter Top Seriously wear VH L M
sponds to the relative importance of the RPN is deter-
mined using Eq. (12) (Table 7). The weights of S, O, and
D are calculated using the method proposed in section
2.3. Table 8 shows the results. The weights of �S, �O, and
�D for “bad hardness” are calculated as follows:
(18)
The clear weight numbers of ��S, ��O, and ��D and
the normalized clear weights of �S, �O, and �D are ob-
tained using Eqs. (11) and (15), respectively (Table 8).
3.4 Calculating the Modified RPN Value and
Determining the Risk Ranking
Finally, the modified RPN value is calculated using
Eq. (16). The first failure mode “bad hardness” is taken
as an example, as follows:
Modified RPN = s�C � o�o � d�D =7.4 � 0.54 � 4.8
� 0.28 � 3.5 � 0.18 = 3.38
The modified RPN value for all the failure modes is
calculated using the same method (Table 9). The clear
numbers of the modified S, O, and D are obtained from
Tables 4 and 6. The weights are obtained from Table 8.
As is shown in Table 9, the RPN values of “super size
difference” and “bad hardness” are ranked as first and
second, respectively. Therefore, they have the highest risk
and should be well controlled.
3.5 Traditional RPN Value and Risk Ranking
Table 10 shows the risk ranking of the failure modes
according to the traditional FMEA method. The tradi-
tional values of S, O, and D are obtained from the previ-
ous FMEA team of this compressor company. The value
selection criteria are obtained from Table 1, and the RPN
value is calculated using Eq. (1). Table 10 shows that
“super size difference” and “cylindricity error” are the
first and second risk potential failure modes to be con-
trolled.
3.6 Comparison and Discussion
Figure 2 shows the percentage comparison of the two
RPN alternatives for five failure modes. It is clearly that
A Modified Method for Risk Evaluation in Failure Mode and Effects Analysis 183