Industry Process Safety

This chapter deals with the issue of process safety in industrial companies and major accident prevention. In the present-day technologically advanced world, industrial accidents appear ever more frequently, and the field of major accident prevention has become a dynamically developing discipline. With accelerating technical progress, risks of industrial accidents are to be reduced. In the first part, possible approaches to quantitative risk assessment are presented; and continuing it focuses on the system of risk management in industrial establishments. This chapter aims at providing experiences, knowledge, as well as new approaches to the prevention of major accidents caused by the implementation of the Seveso III Directive.

The effects of electronic navigation devices on marine accident occurrences

In recent years, maritime-related organizations and companies have moved to a risk-based approach. To determine the risks, it is necessary to understand comprehensively why accidents occur and how it develops. The most effective measures need to be identified to implement the accident prevention measures successfully. According to the results of scientific studies conducted in the past, 80% of human factors risks were effective in marine accidents. Nowadays, maritime technologies are the most effective method for reducing the risks of human factors. However, the use of electronic navigation devices has not eliminated accidents. In this study, the accident reports for collision and grounding due to the electronic navigation devices' risk was evaluated using Human Factors Analysis and Classification System (HFACS) method. As a result of the study, more than half of the visible (active) causes of accidents have been identified as operating failure factors in electronic navigation equipment. Recommendations to prevent the occurrence of accident factors have been made.

Effect of educational intervention based on health belief model on accident prevention behaviours in mothers of children under 5-years

Background As the public health problems, accidents are the most important causes of child mortality. The present study aimed to determine the effect of educational intervention based on health belief model on accident prevention behaviors in mothers of children under 5-years of age. Methods This quasi-experimental study was conducted on 200 mothers in Fasa city who were purposefully selected and randomly divided into two groups of intervention and control. Data collection tools were demographic characteristics and health belief model questionnaire. Questionnaires were completed twice before and 3 months after the intervention. After the pre-test, the educational intervention was performed through 6 sessions of 30–35 min in a WhatsApp group. Data were analyzed using SPSS 22 through Chi-square test, independent t-test and paired t-test (p = 0.05). Results The mean age of mothers in the experimental and control groups was 30.14 ± 4.35 and 31.08 ± 4.31 years. Mean score of awareness, perceived sensitivity, perceived severity, perceived benefits, perceived self-efficacy, cues to action, and accident prevention behaviors significantly increased 3 months after the intervention. Conclusion This study showed the effectiveness of educational intervention based on health belief model on accident prevention behaviors in mothers of children under 5-years of age.

Appropriate Smart Factory : Demonstration of Applicability to Industrial Safety

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.