A sequential method to identify underlying causes from industrial accidents reported to the MARS database

This paper presents a method designed to identify underlying causes leading to industrial accidents. The method developed intends to facilitate the learning process from accidents by identifying possible causes related to the accidents that were not directly stated in an accident report, but that can be deduced following the description of the event, in particular with regard to the quality of the safety management systems in place at the industrial establishment at the time of the accident. The method has been prepared following a sequential approach, although a combination of the philosophy behind other existing accident models has been taken into consideration. The starting point to develop the model is the causes for accidents included in the MARS database of the European Commission. These causes have been extended by considering typical operational or organisational failures that are normally related to the original reported cause. The extension of causes has been performed by adding three follow-on levels of possible underlying causes. The first level could be considered as a direct cause of the accident and, the last level being more applicable to the foundation of establishing safety: “Safety Management System or the Safety Culture”.In order to check the applicability of the method developed, it has been validated by a group of experts of the European Federation of Chemical Engineering, in order to reinforce the strategy adopted by the authors. Moreover, the method has been used to analyse the total set of accidents reported to the MARS database. The objective is to determine the efficiency of the method in identifying underlying causes, and to establish a link between the results obtained and the actual causes stated in the reports. In this way, it is possible to establish a system to go deeper into the analysis of past accidents, in order to obtain lessons learned, and to avoid recurrence of similar accidental scenarios in the future, as well as to give directions for a better reporting system of industrial accidents.