Designing and implementation of a fuzzy-dynamic model to evaluate system’s risk and reliability

Journal of System Management

همکاران ، دوره 1، شماره 3، مهر 2015، صفحه 15-30

نویسندگان

Majid VaziriSarashk^{* 1}؛ Sohrab KhanMohammadi²؛ Mahmood Alborzi³؛ Seyed Mohammad Seyed Hoseini⁴

¹Science and Research Branch, Islamic Azad University, Tehran, Iran

²Department of Electronic and Computer, Tabriz University, Tabriz, Iran

³Department of Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

⁴Department of Industrial Engineering, Science and Industry University, Tehran, Iran

چکیده

The purpose of this article is to permit the system safety
and reliability analysts to evaluate the criticality or risk associated with
item failure modes. The factors considered in traditional failure mode
and effect analysis (FMEA) for risk assessment are frequency of occurrence
(O), severity (S) and detectability (D) of an item failure mode.
Because of the subjective, qualitative and dynamic nature of the information
and to make the analysis more consistent and logical, an approach
using fuzzy logic and system dynamics methodology is proposed. In the proposed approach, severity is replaced by dependency parameter
then, these parameters are represented as members of a fuzzy set
fuzzified by using appropriate membership functions and are evaluated
in fuzzy inference engine, which makes use of well-defined rule base and
fuzzy logic operations to determine the value of parameters related to
system’s transfer functions. The fuzzy conclusion is then defuzzified to
get transfer function for risk and failure rate. The applicability of the
proposed approach is investigated with the help of an illustrative case
study from the automotive industry. The results provide an alternate
solution to that obtained by the traditional method. The suggested assessment
model was developed using toolbox platform of MATLAB 6.5
R.13.

کلیدواژه‌ها

Failure Modes and Effects Analysis؛ reliability management؛ systems and control theory؛ fuzzy logic؛ system dynamics approach