A widely accepted definition of resilience is the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances so that it can sustain required operational safety under both expected and unexpected conditions. These concepts have been applied in the process or manufacturing industry with different attempts in switching from the traditional risk management approach to a resilience one, still finding a lack of clarity in the definitions and in the objectives and, consequently, a lack in the methodologies and tools to support those efforts. The attempts and the need for further research or clarification is discussed in this paper.
Despite of the always growing attention to safety related topics, the enforcement of directives, regulations and technical standards and the improvement of technical solutions aimed to minimize the occupational risks, the number of people dying every day at workplaces is still excessively high. The overall number of injuries is recently decreasing, but both the frequency and the total yearly number of fatalities still remain fundamentalny unchanged in the last years. The main problem with accidental data, as officially reported, is that very often, no evaluation is possible in terms of root causes, e.g. standard violations. Since the target of the analysis is the determination of the causal chain of events that lead to the accident to understand how it happened and how to avoid the occurrence of similar situations, the lack of detailed information lead to many difficulties in the definition of the suitable prevention measures. This paper shows three different, but integrated. methods able to collect, manage and analyze the information related to occurred accidents for preventive purposes.
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