Health, Safety, Environment and Ergonomic Improvement in Energy Sector Using an Integrated Fuzzy Cognitive Map–Bayesian Network Model

被引:1
作者
P. Pourreza
M. Saberi
A. Azadeh
Elizabeth Chang
Omar Hussain
机构
[1] University of Tehran,School of Industrial Engineering, College of Engineering
[2] UNSW Canberra,School of Business
来源
International Journal of Fuzzy Systems | 2018年 / 20卷
关键词
Power plant; Health; Safety; Environment; Ergonomics; Bayesian network (BN); Fuzzy cognitive map; Noisy-OR; Expectation–maximization (EM);
D O I
暂无
中图分类号
学科分类号
摘要
Health, safety, environment and ergonomics (HSEE) are important factors for any organization. In fact, organizations always have to assess their compliance in these factors to the required benchmarks and take proactive actions to improve them if required. In this paper, we propose a fuzzy cognitive map–Bayesian network (BN) model in order to assist organizations in undertaking this process. The fuzzy cognitive map (FCM) method is used for constructing graphical models of BN to ascertain the relationships between the inputs and the impact which they will have on the quantified HSEE. Using the notion of Fuzzy logic assists us to work with humans and their linguistic inputs in the process of experts’ opinion solicitation. The noisy-OR method and the EM are used to ascertain the conditional probability between the inputs and quantifying the HSEE value. Using this, we find out that the most influential input factor on HSEE quantification which can then be managed for improving an organization’s compliance to HSEE. Finding the same influential input factor in both BN models which are based on the noisy-OR method and EM demonstrate how FCM is useful in constructing a reliable BN model. Leveraging the power of Bayesian network in modelling HSEE and augmenting it with FCM is the main contribution of this research work which opens the new line of research in the area of HSE management.
引用
收藏
页码:1346 / 1356
页数:10
相关论文
共 69 条
[1]  
Akhtar MJ(2014)Human fatigue’s effect on the risk of maritime groundings: a Bayesian network modelling approach Saf. Sci. 62 427-440
[2]  
Utne IB(2013)Assessment and improvement of integrated HSEE and macro-ergonomics factors by fuzzy cognitive maps: the case of a large gas refinery J. Loss Prev. Process Ind. 26 1015-1026
[3]  
Asadzadeh S(2016)Impact of integrated HSEE management system on power generation in Iran by a unique mathematical programming approach World J. Eng. 13 82-90
[4]  
Azadeh A(2011)An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: the case of a gas refinery J. Loss Prev. Process Ind. 24 361-370
[5]  
Negahban A(2008)Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSEE) and ergonomics system: the case of a gas refinery Inf. Sci. 178 4280-4300
[6]  
Sotoudeh A(2013)Improved prediction of mental workload versus HSE and ergonomics factors by an adaptive intelligent algorithm Saf. Sci. 58 59-75
[7]  
Azadeh A(2014)An adaptive algorithm for assessment of operators with job security and HSEE indicators J. Loss Prev. Process Ind. 31 26-40
[8]  
Motevali Haghighi S(2010)Health, environment, safety culture and climate–analysing the relationships to occupational accidents J. Risk Res. 13 445-477
[9]  
Hosseinabadi Farahani M(1951)Coefficient alpha and the internal structure of tests Psychometrika 16 297-334
[10]  
Yazdanparast R(2009)An explorative study of health, safety and environment culture in a Norwegian petroleum company Saf. Sci. 47 992-1001