A Data-Driven Approach for Deploying Safety Policies for Schedule Planning in Industrial Construction Projects: A Case Study

Taghaddos, Maedeh; Pereira, Estacio; Osorio-Sandoval, Carlos; Hermann, Ulrich; AbouRizk, Simaan

Abstract

Construction, by the nature of the work, is more accident-prone than other industries despite advancements in improving safety performance. Proactive mitigation and assessment of the safety performance of construction projects remain challenging due to the difficulty of acquiring, storing, and using data to produce accurate predictive models. This research focused on devising methods that allow decision makers to leverage existing data in the planning phase to streamline the development of predictive models. A data-driven approach to predict the probability of a safety incident occurring in a given construction project and within a novel discipline-level schedule is presented. By implementing the proposed model, decision makers can evaluate and mitigate the risk of a given project incident occurring by deploying discipline-level safety policies in the planning phase and modifying the schedule accordingly. A predictive model was developed based on selected safety-related metrics extracted from a data set comprising daily payroll data and incident reports, which represent 28 million working hours within eight different industrial construction projects in Canada. The model was implemented in a case study based on an industrial project to demonstrate the framework’s functionality and practical utility during the project planning phase. The results show that the revised safe plan can be achieved by incorporating safety considerations in the planning phase.

Citation

Taghaddos, M., Pereira, E., Osorio-Sandoval, C., Hermann, U., & AbouRizk, S. (2023). A Data-Driven Approach for Deploying Safety Policies for Schedule Planning in Industrial Construction Projects: A Case Study. Journal of Construction Engineering and Management, 149(12), Article 05023013. https://doi.org/10.1061/JCEMD4.COENG-13690

• Journal Article Type: Article
• Acceptance Date: Aug 18, 2023
• Online Publication Date: Oct 12, 2023
• Publication Date: 2023-12
• Deposit Date: Oct 16, 2023
• Publicly Available Date: Oct 19, 2023
• Journal: Journal of Construction Engineering and Management
• Print ISSN: 0733-9364
• Electronic ISSN: 1943-7862
• Publisher: American Society of Civil Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 149
• Issue: 12
• Article Number: 05023013
• DOI: https://doi.org/10.1061/JCEMD4.COENG-13690
• Keywords: Business management; Case studies; Construction engineering; Construction industry; Construction management; Engineering fundamentals; Management methods; Methodology (by type); Mitigation and remediation; Occupational safety; Practice and Profession; Pro
• Public URL: https://nottingham-repository.worktribe.com/output/25956470
• Publisher URL: https://ascelibrary.org/doi/10.1061/JCEMD4.COENG-13690
• Additional Information: Received: 2023-02-21; Accepted: 2023-08-18; Published: 2023-10-12