Enhancing safety management systems practices on construction projects: A proactive data-driven approach for project safety planning and control

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Construction is one of Canada's most significant industrial sectors, and it is a mainstay of the country's economy that significantly affects provincial and regional economies. The number of fatalities in the Canadian construction industry is higher than any other industry, and it is practically constant. According to the Association of Workers' Compensation Boards of Canada, the number of accepted lost-time claims per year in the construction industry increased 9% from 2016 to 2018. The goal of this project is to research and develop a new framework for safety management that enables robust and holistic planning for safety based on historical and project progress data. This framework will facilitate the integration of quantitative and qualitative data from different sources at different time windows and will enable the testing of what-if scenarios to predict and evaluate the impact of different management decisions on safety performance. The development of this framework will utilize advanced machine learning and distributed simulation technologies to enable the modeling and integration of different data sources. Successful development of the proposed framework will assist the decision-making process of construction practitioners and organizations during construction project planning and execution, and can potentially enable the development of more effective policies for improving safety performance. The outcomes of this project are expected to enhance organizations safety performance and therefore related insurance costs (e.g. workers' compensation rates). Reducing the number of accidents can result in improving the productivity and competitiveness of the Canadian Construction industry. The innovations and findings of this research project can also advance Alberta and Canada's reputation as a world leader in worker safety.