Dynamic methodology for risk assessment in industrial processes by using quality control charts

Although several Quantitative Risk Assessment (QRA) methodologies have often proven effective in industry they generally lack for the ability of update on a real-time basis offering a static perspective of industrial risks. In recent years this situation has been treated by the development of the Dynamic Risk Assessment (DRA) methodologies updating the analysis and frequency of the accident precursor events by means of the application of the Bayesian inference method. Additional dynamic methodologies have emerged but in order to obtain an analysis in parallel with the evolution of the process, it is necessary to incorporate the characteristics of prevention, simultaneity and immediacy that allow corrective actions to be carried out sufficiently in advance because the industrial process is showing a risk situation outside control limits. In this work a new methodology based also on the dynamic risk assessment approach and on the application of control charts together with the use of the Monte Carlo Markov Chain (MCMC) methods are used to monitor the causes of accident with a concept of Statistical Risk Control (SRC).