||Integrated Data Analytics-Simulation Framework for Proactive Assessment of Safety Performance
||Estacio Pereira, Sanguk Han and Simaan Abourizk
||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.
|Year of publication:
||Conceptual Safety Performance, Prediction; Policy Making; Simulation; Historical Data
Estacio Pereira, Sanguk Han and Simaan Abourizk (2017).
Integrated Data Analytics-Simulation Framework for Proactive Assessment of Safety Performance. Lean and Computing in Construction Congress (LC3): Volume I Ð Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 431-438,