Occupational accidents data collection and analysis

• Autorzy: Demichela M. , Murè S. , Cigna C. , Monai L. , Patrucco M.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

occupational accidents; fuzzy logic; neural networks; expert systems; data collection

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2010
• Tom: Vol. 1, No. 1
• Strony: 67--74
• Opis fizyczny: Bibliogr. 13 poz., rys., tab., wykr.

Twórcy

autor

Demichela M.

• SAfeR- Centro Studi su Sicurezza, Affidabilità e Rischi - Dip. Scienza dei Materiali e Ingegneria Chimica - Politecnico di Torino, Torino, Italy

autor

Murè S.

• ARIA S.r.l. – Analisi dei Rischi Industriali e Ambientali, Torino, Italy

autor

Cigna C.

• Dip. Ingegneria del Territorio, dell’Ambiente e delle Geotecnologie - Politecnico di Torino, Torino, Italy

autor

Monai L.

• Dip. Ingegneria del Territorio, dell’Ambiente e delle Geotecnologie - Politecnico di Torino, Torino, Italy

autor

Patrucco M.

• Dip. Ingegneria del Territorio, dell’Ambiente e delle Geotecnologie - Politecnico di Torino, Torino, Italy

Bibliografia

• [1] Ariano, P. F., Bersano, D., Cigna, C., Patrucco, M., Pession, J. M., Prato, S., Romano, R. & Scioldo, G. (2009). Extractive activities start up and management: a computer assisted specialty developed “Prevention through Design” approach. International Journal of Mining, Reclamation and Environment.
• [2] Camisassi, A., Cigna, C., Nava, S., Patrucco, M. & Savoca, D. (2006). Load and hauling machinery: an evaluation of the hazard involved as a basis for an effective risk evaluation. In Cardu M., Ciccu R., Lovera E., Michelotti E. (Eds.) Mine Planning and Equipment Selection (MPES), Torino.
• [3] Camisassi, A., Cigna, C. & Patrucco, M. (2004). Sicurezza nei cantieri: analisi di rischio e condizioni di impiego in sicurezza di macchine operatrici e mezzi di sollevamento di materiali. GEAM-Geoingegneria ambientale e mineraria XLI, 3, 19-32.
• [4] Edelstein, H. A. (1999). Introduction to Data Mining and Knowledge Discovery. Two Crows Corporation, third ed.
• [5] Hamming, R. (1950). Error Detecting and Error Correcting Codes. Bell System Technical Journal, 29, 147-160.
• [6] Howard, J. (2008). Prevention through Design: Introduction. Journal of Safety Research, 32, 113.
• [7] Kohonen, T. (1999). Analysis of processes and large data sets by a self-organizing method. 2nd International Conference on Intelligent Processing and Manufacturing of Materials (IPMM'99), Honolulu, Hawaii, July 10-15, IEEE, vol. 1, pp. 27-36.
• [8] Liao, C. W. & Perng, Y. H. (2008). Data mining for occupational injuries in the Taiwan construction industry. Safety Science 46, 1091-1102.
• [9] Lourenço, F., Lobo, V., Bação, F. (2004). Binarybased similarity measures for categorical data and their application in Self-Organizing Maps. Internal Report, Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa.
• [10] Murè, S., Demichela, M., & Piccinini, N. (2006). Assessment of the risk of occupational accidents using a FUZZY approach. Cognition Technology & Work, 8, 103-112.
• [11] NOHSC - National Occupational Health and Safety Commission. Australian Government, The role of design issues in work related injuries In Australia 1997-2002, 2004.
• [12] Palamara, F., Demichela, M. (2007). Occupational accidents risk analysis Rusing clustering algorithms. Proc. of the EuropeanSafety and Reliability Conference, ESREL 2007.
• [13] Zadeh, L. A. (1965). Fuzzy Sets. Inform Control 8: 338-353.