Integrating smart glasses and smart gloves in hybrid assembly/disassembly systems: an STPA-driven semi-automated risk management tool
Year: 2026
Type: article
Abstract: With the rise of Industry 5.0, wearables have become increasingly common in manufacturing, making effective risk management more critical than ever. Despite this trend, there remains a significant gap in research regarding the risks associated with the simultaneous use of multiple wearables, particularly in complex systems. This study addresses this gap by using an improved Systems-Theoretic Process Analysis combined with Particle Swarm Optimization (STPA-PSO) methodology. This method can systematically identify, analyze, quantify, and mitigate risks, including those arising from human error, in the integration of multiple wearables, serving as a valuable decision-making tool for risk mitigation. Three case studies, two assembly lines and one disassembly line, were tested to check the effectiveness of this method. The findings indicate that increased interactions among system components can lead to elevated risk levels. It demonstrates that highlighting the hazardous areas, calibration regulations, and training of workers are the high-risk control action scenarios which needs to be reduced. By offering a circular methodology for decision-making, this study provides a structured approach to systematically mitigate these identified risks, ensuring safer and more efficient integration of wearable technologies in manufacturing environments.
Authors: Ali Karevan, Sylvie Nadeau
Institution: École de Technologie Supérieure
Language: English
Topic: Risk and Safety Analysis
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,540
OpenAlex ID: W7126204854