Processes, Vol. 13, Pages 3206: Smart Risk Assessment and Adaptive Control Strategy Selection for Human–Robot Collaboration in Industry 5.0: An Intelligent Multi-Criteria Decision-Making Approach

Processes doi: 10.3390/pr13103206

Authors:
Ertugrul Ayyildiz
Tolga Kudret Karaca
Melike Cari
Bahar Yalcin Kavus
Nezir Aydin

The emergence of Industry 5.0 brings a paradigm shift towards collaborative environments where humans and intelligent robots work side-by-side, enabling personalized, flexible, and resilient manufacturing. However, integrating humans and robots introduces new operational and safety risks that require proactive and adaptive control strategies. This study proposes an intelligent multi-criteria decision-making framework for smart risk assessment and the selection of optimal adaptive control strategies in human–robot collaborative manufacturing settings. The proposed framework integrates advanced risk analytics, real-time data processing, and expert knowledge to evaluate alternative control strategies, such as real-time wearable sensor integration, vision-based dynamic safety zones, AI-driven behavior prediction models, haptic feedback, and self-learning adaptive robot algorithms. A cross-disciplinary panel of ten experts structures six main and eighteen sub-criteria spanning safety, adaptability, ergonomics, reliability, performance, and cost, with response time and implementation/maintenance costs modeled as cost types. Safety receives the most significant weight; the most influential sub-criteria are collision avoidance efficiency, return on investment (ROI), and emergency response capability. The framework preserves linguistic semantics from elicitation to aggregation and provides a transparent, uncertainty-aware tool for selecting and phasing adaptive control strategies in Industry 5.0 collaborative cells.

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Ertugrul Ayyildiz www.mdpi.com