Development of smart sensors with a view to Industry 5.0 and Human Manufacturing

Azienda: TSM Sensors

Tutor: Daniele Regazzoni, Gianluca Traversi

The research project is part of the new Industry 5.0 paradigm that is becoming increasingly vibrant within the international industrial landscape.

Human-machine interaction, human-centeredness and sustainability are the cornerstones that are emerging in break with a purely profit-driven approach.

The concept of Human Manufacturing introduces a significant change in the role of the worker: the worker should not be considered as a “cost” but rather as an “investment” that enables the development of both the company and the worker himself through the greater enhancement and appreciation of human capital.

A well-being, therefore, that also becomes an economic choice for companies given that an employee who experiences the work environment well improves production and lowers the possibility of errors.

In addition to the fundamental fact that through new technologies we are able to lower the incidence of occupational diseases and accidents at work, which, among other things, represent a major expense for companies.

Psychological stress and physical problems are the cause of the most critical issues that are detected at work; however, they can be monitored, predicted and solved, before they can become a problem, thanks mainly to the use of wearable devices: by monitoring people’s physical conditions and through processing done with artificial intelligence algorithms, it is possible to predict the onset of such problems.

Thus, the goal of the project is the development and implementation of sensor and microcontroller platforms for monitoring the environment, people and industrial plants, connected to the development of artificial intelligence algorithms in order to achieve intelligent cooperation between humans and machines that leads the worker to be the guide and the model on which performance, layout and modes of use of industrial plants and operating machines are adapted.