Towards Operator 5.0: human-centered methods and tools to enhance worker psychophysical well-being

The work environment significantly influences workers’ well-being and shapes their personal experiences. Working in an unhealthy workplace can lead to stress, frustration, and anxiety. Therefore, companies must prioritize workers’ well-being in the work environment, making the management of human factors a crucial aspect. In recent years, there has been a growing focus on worker well-being in manufacturing industries, with many managers expressing concerns about work-related risks. However, despite this, many European companies lack adequate procedures. This absence of measures results in work-related illnesses affecting millions of workers, leading to significant social and economic costs. These include a high prevalence of musculoskeletal disorders and emerging psychosocial risks that are challenging to manage. In this context, the introduction of Industry 4.0 technologies can support workplace monitoring and improvement. To achieve these objectives, tools supporting data collection, processing, and correlation are necessary. The traditional approach to physical and cognitive ergonomics assessment relies on on-site observation and manual compilation of standard analyses by experts. However, Industry 4.0 enabling technologies can facilitate the development of integrated platforms for monitoring the physical and psychological well-being of workers. Existing research predominantly focused on physical ergonomic risks, with limited attention given to structured methods that encompass multiple ergonomic domains simultaneously. There is a pressing need for further research and the development of integrated tools to holistically address work-related risks across various ergonomic domains and prioritize enhancements in these areas. The present work aims to bridge this gap by proposing a structured methodology for ergonomic assessment that integrates both objective and subjective analyses to ensure optimal working conditions. The implementation of this approach has been achieved through the Human Tool, which supports the monitoring of operators’ activities and data analysis to enhance working conditions. This approach prioritizes workers' psychophysical well-being, satisfaction, and collaborative synergy while also considering production goals such as productivity. Through the integration of inertial sensors and wearable devices, the physical and cognitive ergonomics of operators can be assessed, enabling precise and objective analysis of work-related risks. Specific algorithms have been developed to assess physical ergonomic risks automatically and objectively. These algorithms analyze data collected from inertial sensors to calculate the risk index and identify risk factors, offering insights to mitigate the likelihood of musculoskeletal disorders and injuries. Moreover, Advanced machine learning algorithms have been developed to identify and manage moments of stress during work based on various physiological and behavioral data collected from the sensors. The usability and effectiveness of this tool have been evaluated in collaboration with various companies, highlighting its utility and potential in improving working conditions and productivity efficiency. This study represents a first step towards the creation of a human-centric industrial environment, where operators are at the center of the production process, and their well-being is prioritized for business success.