Operator 5.0: Enhancing the Physical Resilience of Workers in Assembly Lines

The human factor represents the most fragile and valuable resource in modern and low-standardized manufacturing environments. Indeed, the Operator 5.0 concept aims at achieving socially-inclusive workplaces by monitoring the well-being of workers during production cycles. To accomplish this challenging aim, this manuscript proposes a digital industrial Internet-of-Things architecture to monitor the physical resilience of Operator 5.0 in assembly lines. While a markerless motion capture camera is adopted to evaluate the ergonomic exposure, a superficial electromyography wearable acquires muscular contractions of upper limbs to perform a machine learning-based recognition of fatigue status. In this preliminary investigation, the main focus of the analysis is to digitize the European Assembly Worksheet to evaluate the worker’s postures during the assembly of home furniture. Exploiting such ergonomic measurements, a Monte Carlo-based sensitivity analysis is leveraged to evaluate the noise in bending scenarios. Finally, a reference system is leveraged to assess the measurement error of the motion capture camera.