Abstract

Job Hazard Analysis (JHA) is a process of identifying potential hazards for each step of an activity and proposing safety rules to prevent potential incidents related to these hazards. In the US, the Occupational Safety and Health Administration (OSHA) recommends performing JHA for construction activities to highlight and react to potential hazards. JHA commonly requires having brainstorming sessions to identify steps and associated hazards within construction activities. A company's personnel involved in JHAs relies on their experience - and often also on the company's internal knowledge represented in the form of safety rules. However, the complexity and time consuming nature of JHA prevent safety personnel from adjusting JHAs quickly when changes in the construction methods and the schedule are made. This paper presents a framework aiming to improve access to a company's JHA knowledge. The framework uses ontologies for structuring knowledge about activities, job steps and hazards. It also includes an ontological reasoning mechanism for identifying safety rules applicable to given activities. The framework has been validated through several test cases using real JHA documents. The results of the validations are discussed in this paper and conclusions for future research are drawn.

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