Quality of Experience and Mental Energy Use of Cobot Workers in Manufacturing Enterprises

Integrating information on the subjective experience reported by workers operating in collaborative human-machine environments with objective data, collected with wearable sensors capable of monitoring participants’ physiological responses, may lead to novel findings regarding the recognition and handling of potentially stressful work situations. To this aim, data were collected from seven participants working in production lines of manufactory companies employing collaborative robots. The experience associated with daily activities by cobot-workers in manufacturing enterprises was investigated for one week through the Experience Sampling Method. Data were analyzed through the Experience Fluctuation Model, relying on the relationship between perceived task related challenges and personal skills to identify eight experiential profiles: arousal, flow or optimal experience, control, relaxation, boredom, apathy, worry and anxiety. Physiological data were continuously collected throughout the same week using a smartwatch and processed to obtain real-time estimation of the mental energy use and recovery. Results showed that flow experience was predominant in tasks involving cobots; production line activities without cobot were instead mostly associated with relaxation. The real-time monitoring of the mental energy levels associated with work corroborated these results by showing that participants were, on average, 2.5 times longer in the focus zone when working with the cobot than when working without it. These findings suggest the heuristic potential of combining psychological and physiological assessment procedures to identify both advantages and areas of implementation emerging from the employment of cobots in industrial settings.