A Simulation-Based Framework for Fatigue-Aware Task Reallocation in Human–Robot Collaboration: Software Verification With 1000-Episode Digital Twin

Collaborative robotics in Industry 4.0 manufacturing faces persistent challenges in balancing productivity with operator safety, particularly when human fatigue accumulates during extended work shifts. While physical validation remains the gold standard, computational simulation offers advantages for systematic algorithm development: perfect ground truth unavailable from self-reported fatigue measures, parameter sweeps across physiological ranges infeasible with human subjects, and controlled testing of extreme scenarios unsafe for physical trials. A simulation framework is presented for developing fatigue-aware task reallocation algorithms before deployment on actual collaborative robots. The framework implements a tricolor semaphore system (Green/Orange/Red thresholds at 30%/40% fatigue) with dynamic sampling rates (5.0 min baseline, 0.1 min critical monitoring) and automated robotic intervention when operator fatigue exceeds safe thresholds. Software verification across 1000 simulated episodes demonstrates 99.30% collision-free operation—approaching but not yet achieving the ISO/TS 15066:2016 safety target of 99.85%, with a 0.55 percentage point gap for future algorithm refinement. Friedman analysis confirms statistically significant fatigue progression (chi-squared=3000.0, p