Improving Machinery-Related Risk Identification and Estimation with Accident Reporting and Logical Analysis of Data

Autor:	Sabrina Jocelyn, Mohamed-Salah Ouali, Yuvin Chinniah
Rok vydání:	2017
Předmět:	Medical Terminology Estimation Accident (fallacy) Logical analysis of data Risk analysis (engineering) Computer science Risk identification Medical Assisting and Transcription Reliability engineering
Zdroj:	Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 61:1659-1663
ISSN:	1071-1813 2169-5067
DOI:	10.1177/1541931213601903
Popis:	Continually managing occupational risks is the cornerstone of any prevention program. ISO 12100:2010 defines risk in the field of safety of machinery as the combination of the probability of occurrence of harm and the severity of that harm. The means available to help with risk identification present the hazards isolated from one another. Moreover, estimation of probability is a recurrent problem. To overcome these issues, this paper proposes a method using logical analysis of data to generate patterns from belt-conveyorrelated accident investigation reports. The patterns represent accident scenarios involving combinations of hazards and risk factors. The probabilities of the patterns are estimated to establish a hierarchy of prevention measures that will be part of a prevention action plan. Updating data from accident reports impacts risk estimation, thus entailing adjustment of the prevention action plan.
Databáze:	OpenAIRE
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