Lin, P.; Zeng, N.; Yuan, J.; Li, Q. and Nübel, K. (2026) From static factor measurement to ontology-based scenario activation in construction human–robot collaboration for safety risk management. Journal of Construction Engineering and Management, 152(9): 04026139, ISSN 0733-9364
Abstract
Existing safety management paradigms in construction prioritize the completeness and measurability of static factors (e.g., worker attributes, robot characteristics, and site environmental hazards) but fail to account for the scenario-dependent, high interactivity, and inherent dynamic complexity of the emerging human–robot collaboration (HRC) context. These challenges are further compounded by knowledge scarcity and data incompleteness, which limit the applicability of purely data-driven safety approaches. This study aims to distill conventional risk factors, incorporate newly emerging HRC-specific risks, and develop a high-coverage and decomposable safety management approach through a factor-integrated ontology and scenario-activation mechanisms. Following the design science research methodology, a mixed-method approach was employed, integrating a systematic literature review, expert interviews, ontology development, and agent-based simulation. The resulting risk factor–integrated HRC safety ontology (IHRCS-Onto) provides a conceptual, symbolic, and extensible structure for representing HRC entities, activities, and risk relationships. The feasibility and functionality of the ontology and scenario-activation mechanisms were evaluated through expert consultation and demonstrated in a typical bricklaying scenario as a feasibility-oriented pilot test, providing initial, scenario-specific evidence that the proposed workflow can support hazard identification, classification, and scenario-level analysis. The modular ontology and activation mechanisms are designed to support the potential for method-level reusability, establishing a foundation for safety data standardization and scenario-driven information extraction, and providing a basis for the future development of digital safety tools for real-time monitoring, intelligent risk prediction, and data-driven decision-making.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | human–robot collaboration; ontology; safety risk management; scenario |
| Index terms: | collaboration, agent, risk relationship, data-driven decision-making, workflow, hazard identification, methodology, standardization, risk management, design science research, environmental hazard, paradigm, risk factor, interview, ontology, evidence, complexity, systematic literature review, functionality, safety management, monitoring |
| Subjects: | practitioner, control systems, education and knowledge transfer, research methods, performance measurement, decision analysis, management, evaluation and assessment methods, risk assessment, systems engineering, financial risk, design features, data collection methods, environmental hazards, design practice, research evaluation and metrics, occupational health and safety management, environmental health |
| Topics: | Health and Safety, Roles and Professions, Organizational Design, Cost Management, Research Practice, Business Strategy, Engineering Principles, Sustainability, Quality Management, Site Management, Risk Management, Design Practice |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here