The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant.
10.1016/j.shaw.2016.04.009
- Author:
Ali AZADEH
1
;
Vahid SALEHI
;
Mahsa MIRZAYI
Author Information
1. School of Industrial and Systems Engineering and Center of Excellence for Intelligent Based Experimental Mechanic, College of Engineering, University of Tehran, Iran. aazadeh@ut.ac.ir
- Publication Type:Original Article
- Keywords:
fuzzy data envelopment analysis;
petrochemical plant;
redundancy;
resilience engineering;
teamwork
- MeSH:
Analysis of Variance*;
Plants*;
Surveys and Questionnaires
- From:Safety and Health at Work
2016;7(4):307-316
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: Resilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors—self-organization, teamwork, redundancy, and fault-tolerance—in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment. METHODS: The required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different α-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four above-mentioned factors. RESULTS: The results showed that as α approached 0 and the system became fuzzier (α = 0.3 and α = 0.1), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as α approached 1 and the fuzzy system went toward a certain mode (α = 0.9 and α = 1), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors. CONCLUSION: The approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.
