THE CONCEPT OF IDENTIFICATION OF LAYERS OF SAFETY SYSTEM MODELS THROUGH CLASSIFICATION OF RISK REDUCTION MEASURES

Adrian Gill, Adam Kadziński
2015 Journal of KONES Powertrain and Transport  
The article is an introduction to the analysis of the functioning of the safety systems with the use of layered models. The idea behind these models is the classification of elements of safety systems into independent groups referred to as the layers of protection. It seems that the functioning of the safety systems is usually based on the concept of multi-layer securities. Modern technological installations of high-risk industrial facilities are fitted with multi layer security systems. The
more » ... inition of the safety systems and a review of the definitions of hazard risk reduction measures as part of those systems are presented. A layer of the model of a safety system comprises the measure of risk reduction in terms of the stage of classification. It has been assumed that the safety system model will depend on the adopted classification of these measures. The classification of risk reduction measures used in safety systems of technical objects depending on the form of these measures is presented. Assuming that the form of the safety system model depends on the adopted classification of the risk reduction measures we can perform an identification of the layers of this model. The concept of identification of protection layers in multi-layers safety systems based on classifications is developed. The notation used in the classification of types of risk reduction measures is also presented. Schematic of safety system identification of transport systems objects according to the adopted classification of types of risk reduction measures is developed. According to these schematics, we can describe the safety system models of object other than those related to transport. An example of such an adaptation has been developed for a multi-layer safety system model of objects in the processing industry.
doi:10.5604/12314005.1137326 fatcat:m7hiqw3or5gtbodcsgqjpwni5a