Safety, Reliability and Risk Analysis: Beyond the Horizon - Proceedings of the European Safety and Reliability Conference, ESREL 2013 2014, Pages 1595-1600 European Safety and Reliability Conference, ESREL 2013; Amsterdam; Netherlands; 29 September 2013 through 2 October 2013; Code 105005 Advances tools for occupational accidents data analysis for prevention purposes (Conference Paper) Demichela, M.a, Baldissone, G.a, Luzzi, R.b a Politecnico di Torino, Torino, Italy b INAIL, Direzione Regionale del Piemonte, Torino, Italy View references (11) Abstract Data on occupational accidents are collected in large national databases for compensation authorities, but analysis of this data is hard to do. In fact this data are little used to develop a prevention policy. To avoid loosing the relevant information that could be embedded within this data we used an approach base on two levels. First level use Self-Organizing Map, methodology based on neural network, this algorithm analyzes multidimensional data and gives bidimensional results. To validate this methodology, identifying more critical events, hidden relations between root causes and prevention lessons, the proposed method has been applied to data collected by INAIL in Piemonte in years 2003/04/05 in metallurgical industry. The obtained results are shown in this paper.

Advances tools for occupational accidents data analysis for prevention purposes / Demichela, Micaela; Baldissone, Gabriele; Luzzi, R.. - STAMPA. - (2014), pp. 1595-1600. ((Intervento presentato al convegno European Safety and Reliability Conference, ESREL 2013 tenutosi a Amsterdam; Netherlands nel 29 September 2013 through 2 October 2013.

Advances tools for occupational accidents data analysis for prevention purposes

DEMICHELA, Micaela;BALDISSONE, GABRIELE;
2014

Abstract

Safety, Reliability and Risk Analysis: Beyond the Horizon - Proceedings of the European Safety and Reliability Conference, ESREL 2013 2014, Pages 1595-1600 European Safety and Reliability Conference, ESREL 2013; Amsterdam; Netherlands; 29 September 2013 through 2 October 2013; Code 105005 Advances tools for occupational accidents data analysis for prevention purposes (Conference Paper) Demichela, M.a, Baldissone, G.a, Luzzi, R.b a Politecnico di Torino, Torino, Italy b INAIL, Direzione Regionale del Piemonte, Torino, Italy View references (11) Abstract Data on occupational accidents are collected in large national databases for compensation authorities, but analysis of this data is hard to do. In fact this data are little used to develop a prevention policy. To avoid loosing the relevant information that could be embedded within this data we used an approach base on two levels. First level use Self-Organizing Map, methodology based on neural network, this algorithm analyzes multidimensional data and gives bidimensional results. To validate this methodology, identifying more critical events, hidden relations between root causes and prevention lessons, the proposed method has been applied to data collected by INAIL in Piemonte in years 2003/04/05 in metallurgical industry. The obtained results are shown in this paper.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2588492
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo