Myrto Konstandinidou

A fuzzy modeling application of CREAM methodology for human reliability analysis

Abstract This paper is using a fuzzy classification system for human reliability analysis in order to calculate the probability of erroneous actions according to CREAM in specific contexts e.g. maintenance tasks, in-field actions or control room operations in the running of a chemical plant. The complexities of such a system as well as the appropriate actions that have to be taken into consideration by the developers are analysed in detail. CREAM methodology has been selected among the most known and used methods for Human Reliability Analysis not only for being well-structured and precise, but also because it fits better in the general structure of the fuzzy logic. The first results from the application of the model are very promising and in accordance with CREAM. The numerical values produced by the model can be further used in the ‘classical’ risk assessment methods, such as event trees and fault trees, in order to calculate the overall occurrence frequency of a particular hazardous event. This is a pilot application that demonstrates the successful ‘translation’ of CREAM into a fuzzy logic model. However, the same model could be extended to cover also other industrial fields, like aviation technology and maritime transports.

A compound methodology to assess the impact of human and organizational factors impact on the risk level of hazardous industrial plants

Abstract This paper presents a compound methodology devised to relate Human and Organizational Factors (HOFs) to operators’ response time in critical operations within hazardous industrial plants. The methodology has been based on a sensitivity analysis of the nine “families” of the Common Performance Conditions (CPCs), as defined in the CREAM technique, in order to verify and rank their influence on the operators’ response time. To prove the methodology, a series of pilot experiments have been designed and performed so that human response is evaluated in a Virtual Environment (VE) reproducing the control room and a specific plant section. This environment enables the analyst controlling the simulation to perform the sensitivity analysis acting through a supervisory station and manipulating the control functions in order to vary each CPC rate around its nominal value. Experiments were run with the variation of one CPC at a time aiming at the detection and containment operation of a gas leakage in a pressure-reduction NG terminal. The whole case study has been run within the framework of the VIRTHUALIS EU project.

Safety analysis and risk assessment in a new pesticide production line

Abstract In this work, the safety analysis of a new production line in a pesticide factory in Northern Italy is presented. The analysis was based on four different methods in a way that every part of the new line was investigated. The eventual incidents identified by this analysis were further examined with regard to their consequences using three different simulation models for the release and dispersion of the resultant toxic cloud. This analysis has proven that the risk level for the personnel of the factory and the surroundings is acceptable.

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents.

Accident sequence analysis for sites producing and storing explosives

This paper presents a QRA-based approach for assessing and evaluating the safety of installations handling explosive substances. Comprehensive generic lists of immediate causes and initiating events of detonation and deflagration of explosive substances as well as safety measures preventing these explosions are developed. Initiating events and corresponding measures are grouped under the more general categories of explosion due to shock wave, explosion due to mechanical energy, thermal energy, electrical energy, chemical energy, and electromagnetic radiation. Generic accident sequences are developed using Event Trees. This analysis is adapted to plant-specific conditions and potentially additional protective measures are rank-ordered in terms of the induced reduction in the frequency of explosion, by including also uncertainty. This approach has been applied to 14 plants in Greece with very satisfactory results.

Dynamic failure assessment of incidents reported in the Greek Petrochemical Industry

Abstract This paper presents a Bayesian statistical analysis on real incident data collected from the Greek Petrochemical Industry for a period of 6 years (1997–2003). The analysis provides an assessment of the database to support predictions of dynamically updated incident occurrence frequencies. Results are reported for two different categories of incidents, namely the industrial and the occupational ones.