Architecture of a Feedback System for Human-Machine Interaction in a Collaborative Environment

We present a methodology for measuring and increasing labor productivity using data collection and its analysis for optimizing production task management. Presented socio-cyber-physical system architecture and its technical implementation comprises a decision-making system that is integrated with a collaborative automated manufacturing system. This novel approach enables the implementation of flexible planning of all processes of an employee's work time by dynamically adjusting the environment and applying individual methods of influencing an employee's physical and psychological condition, as well as maintaining the employee's productive and relaxation phases and ensuring smooth transitions between them, using the collected in real-time data. As a result of this work, a system architecture is designed, enabling real-time task scheduling according to the laborer's condition. A description of the structural elements, components, and protocols used is provided. Early work on a prototype system used in the 'Aalto Factory of the Future' laboratory is presented.