scholarly journals Risk Assessment of Gas Leakage from School Laboratories Based on the Bayesian Network

2020 ◽  
Vol 17 (2) ◽  
pp. 426 ◽  
Author(s):  
Xiao Zhang ◽  
Xiaofeng Hu ◽  
Yiping Bai ◽  
Jiansong Wu
Keyword(s):  
Bayesian Network ◽  
Safety Management ◽  
Personal Safety ◽  
Factors Affecting ◽  
Management Level ◽  
Gas Leakage ◽  
Quantitative Calculation ◽  
Unsafe Behavior ◽  
School Laboratory ◽  
Gas Leaks

In recent years, concerns about the safety of laboratories have been caused by several serious accidents in school laboratories. Gas leaks in the laboratory are often difficult to detect and cause serious consequences. In this study, a comprehensive model based on the Bayesian network is established for the assessment of the gas leaks evolution process and consequences in school laboratories. The model can quantitatively evaluate the factors affecting the probability and consequences of gas leakage. The results show that a model is an effective tool for assessing the risk of gas leakage. Among the various factors, the unsafe behavior of personnel has the greatest impact on the probability of gas leakage, and the concentration of toxic and harmful gases is the main factor affecting the consequences of accidents. Since the probability distribution of each node is obtained based on the experience of experts, there is a deviation in the quantitative calculation of the probability of gas leakage and consequences, but does not affect the risk analysis. This study could quantitatively assess the probability and consequences of gas leakage in the laboratory, and identify vulnerabilities, which helps improve the safety management level of gas in the school laboratory and reducing the possibility of gas leakage posing a threat to personal safety.

Facilities maintenance employees’ priority of safety management practices

Facilities ◽  
2017 ◽  
Vol 35 (5/6) ◽  
pp. 319-334
Author(s):  
Saharani bin Jaafar ◽  
Weng Wai Choong ◽  
Abdul Hakim bin Mohamed
Keyword(s):  
Management Practices ◽  
Safety Management ◽  
Pearson Correlation ◽  
Safety Performance ◽  
Safety Communication ◽  
Content Type ◽  
Factors Affecting ◽  
Management Level ◽  
Promotion Policies ◽  
Level Of Satisfaction

Purpose The purpose of this paper is to identify the facilities maintenance employees’ priority on safety management practices and relationship to safety performance. The study aims to increase the safety performance among the facilities maintenance contractor by implementing safety management practices. Design/methodology/approach The data were collected by distributing questionnaire forms to the employees of selected facilities maintenance contractors representing general workers, technicians and executive- and the management-level employees. Data were analysed using descriptive statistics, t-test, one-way analysis of variance, Pearson correlation and multiple regressions. Findings The descriptive results revealed that the employee priority on safety management practices is fairly “low”. The correlation and regression analyses tested and satisfied that management commitment, workers involvement in safety, safety training, safety communication and feedback, safety rules and procedures, and safety promotion policies significantly and strongly correlate with the degree and level of satisfaction to the safety performance. Research limitations/implications This research focuses only on facilities maintenance contractors working in the Klang Valley, Malaysia. It is possible that respondents from other areas or states may allow comparisons across different locations. Practical implications There are many factors affecting safety performance. By implementing safety management practices, high safety performance can be achieved in the facilities maintenance organisations in Malaysia. Originality/value This paper presents empirical findings on the relationship between employee priority on safety management practices elements and safety performance.

Development of a time-variant causal model of human error in construction with dynamic Bayesian network

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhangming Ma ◽  
Heap-Yih Chong ◽  
Pin-Chao Liao
Keyword(s):  
Bayesian Network ◽  
Human Error ◽  
Causal Model ◽  
Safety Management ◽  
Dynamic Bayesian Network ◽  
Human Errors ◽  
Content Type ◽  
Factors Affecting ◽  
Dynamic Causal Model

Purpose Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study. Design/methodology/approach First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment. Findings The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments. Originality/value This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

Analysis of Risk Factors Affecting Safety of Supercritical Steam Generator

2017 ◽  
Author(s):  
Chang Che ◽  
Yuanliang Guo ◽  
Gong Qian ◽  
Xinzhong Chen ◽  
Linfeng Qian
Keyword(s):  
Risk Factors ◽  
Steam Generator ◽  
Safety Management ◽  
Level Structure ◽  
Safety Evaluation ◽  
Scientific Basis ◽  
Operating Conditions ◽  
Factors Affecting ◽  
Management Level ◽  
Technical Management

Supercritical steam generator is a complex system, many factors affect its safety. According to relevant laws, regulations and standards, from three aspects including equipment conditions, operating conditions and technical management, the risk factors of supercritical steam generator are comprehensively analyzed. And a multi-level structure model is developed on the basis of above analysis. The results improve the safety management level of supercritical steam generator, and provide an important and scientific basis for the safety evaluation of supercritical steam generator.

scholarly journals The Mediating Role of Job Competence between Safety Participation and Behavioral Compliance

2021 ◽  
Vol 18 (11) ◽  
pp. 5783
Author(s):  
Jia-Ming Wang ◽  
Pin-Chao Liao ◽  
Guan-Biao Yu
Keyword(s):  
Structural Equation ◽  
Safety Management ◽  
Positive Impact ◽  
Equation Model ◽  
The Sustainable Development ◽  
Factors Affecting ◽  
Behavioral Compliance ◽  
Mediating Role ◽  
Chinese Company ◽  
Job Competence

The effective improvement of employee behavioral compliance and safety performance is an important subject related to the sustainable development of the construction industry. Based on data from a Chinese company (n = 290), this study used a partial least squares-structural equation model to clarify the relationship among safety participation, job competence, and behavioral compliance. Empirical analysis found that: (1) safety participation had a significant positive impact on employees’ behavioral compliance; and (2) job competence played a partial mediating role between safety participation and behavioral compliance. By selecting two new perspectives of safety participation and job competence, this study derived new factors affecting behavioral compliance, constructed a new theory about safety management, and conducted an in-depth discussion on improving behavioral compliance theoretically. Practically, the research put forward a new decision-making model, deconstructed the mechanism between safety participation and behavioral compliance, and provided new guiding strategies for improving employee behavioral compliance.

scholarly journals Fuzzy Bayesian Network-Bow-Tie Analysis of Gas Leakage during Biomass Gasification

PLoS ONE ◽  
2016 ◽  
Vol 11 (7) ◽  
pp. e0160045 ◽  
Author(s):  
Fang Yan ◽  
Kaili Xu ◽  
Xiwen Yao ◽  
Yang Li
Keyword(s):  
Bayesian Network ◽  
Biomass Gasification ◽  
Gas Leakage ◽  
Bow Tie
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