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

Knowledge mapping analysis of safety ergonomics: a bibliometric study

Although a significant attention, the field of safety ergonomics has not yet been systematically profiled based on recent studies. To fully understand the current research status, basis, hotspots, and development trends in the field, 533 documents from the Web of Science core database were used for knowledge mapping analysis by the bibliometric method. The study found that the USA is the top country in publications, and Tehran University is the institution with the highest number of publications. Ergonomics and Applied Economics are the authoritative safety ergonomics journals. Through co-occurrence and co-citation analysis, current safety ergonomics research is focussed on healthcare, product design, and occupational health and safety. The keyword timeline view indicates that the main research paths are occupational health and safety, and patient safety research. The analysis of burst keywords shows that safety ergonomics research in management, model design, and system design areas are research frontiers in the field.Practitioner summary: This paper presents a knowledge mapping of safety ergonomics research through bibliometric analysis. The research results show the research status, research hotspots, and research frontiers in the field of safety ergonomics, which provides a direction for other scholars to quickly understand the development of this field.

Evaluation and Improvement of Employee Performance with respect to Health, Safety, and Environment (HSE) Factors: A Case of Complex Transport Construction Project

Risk control in complex transport construction is complicated due to the dangerous nature of high variation and unpredictability. Most of the current research analysis focuses on the health, safety, and environment (HSE) risk assessment and employee performance evaluation, which neglects the impact of HSE risks on employee performance. Consequently, this research develops a framework to evaluate employee performance and identify key factors affecting performance. The employee performance indicators and HSE indicators are established by reviewing related literature. Using data from questionnaires, an artificial neural network- (ANN-) based model of employee activity effectiveness is then developed to evaluate employee performance. Sensitivity analysis is implemented to determine the key factors affecting employee performance. The Hong Kong-Zhuhai-Macau Bridge, a large-scale cross-sea channel project, is taken as a case study for validation. The model results show that the employees are satisfied with the effect of HSE management in general, but the psychological stress they perceive becomes large. The indicators of risk control and employee participation positively impact employee performance, while job satisfaction has a negative impact on performance. These findings indicate that operators should pay more attention to employees' psychological perception of work and form a standardized process management and control plan to prevent cumbersome processes from increasing employees' workload. This study helps construction systems and managers to identify the areas of strengths and weaknesses in their HSE management. The research only focuses on the impact of HSE risks on managers' performance in the complex transport construction project. In the future, further engineering projects and employee performance in composite scenarios can be investigated to improve the overall productivity.

An integrated experiment for identification of best decision styles and teamworks with respect to HSE and ergonomics program: The case of a large oil refinery

Decision making failure is a predominant human error in emergency situations. To demonstrate the subject model, operators of an oil refinery were asked to answer a health, safety and environment HSE-decision styles (DS) questionnaire. In order to achieve this purpose, qualitative indicators in HSE and ergonomics domain have been collected. Decision styles, related to the questions, have been selected based on Driver taxonomy of human decision making approach. Teamwork efficiency has been assessed based on different decision style combinations. The efficiency has been ranked based on HSE performance. Results revealed that efficient decision styles resulted from data envelopment analysis (DEA) optimization model is consistent with the plant's dominant styles. Therefore, improvement in system performance could be achieved using the best operator for critical posts or in team arrangements. This is the first study that identifies the best decision styles with respect to HSE and ergonomics factors.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies

Background

A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented.

Methods

To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data.

Results

The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs.

Conclusion

The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.