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Paper lc3-2017-029:
Integrated Data Analytics-Simulation Framework for Proactive Assessment of Safety Performance

Facilitated by the SciX project

Estacio Pereira, Sanguk Han and Simaan Abourizk

Integrated Data Analytics-Simulation Framework for Proactive Assessment of Safety Performance

Abstract: Although considerable advances in the proactive control of construction project risks have been reported, identification and assessment of safety-related measures on safety performance remains challenging. This has been attributed to (1) difficulties in data collection; in particular, establishing the number of safety-related measures required to assess their influence on safety performance and (2) difficulties addressing the dynamic nature of projects; in particular, how measures affect safety performance over time. This papers aims to address these issues by implementing a framework that integrates existing departmental data with simulation models to proactively assess and predict safety performance. The framework is composed of three main components. First, safety-related measures available in various departmental databases are identified; second, the relationship between safety performance and measures is analysed and indicators with significant influence are incorporated into the assessment model; and third, a simulation model that reproduces the behaviour of these measures is used to test various scenarios. As evidenced by the results of a case study, the framework proposed here can assist companies with the proactive development of risk-avoidance strategies, thereby improving safety performance.

Keywords: Conceptual Safety Performance, Prediction; Policy Making; Simulation; Historical Data

DOI: https://doi.org/10.24928/JC3-2017/0029

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Series: jc3:2017 (browse)
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