Cost-effective multisensory Diagnostic-Prognostic system integrated in mechanical drives of Industry 4.0


Maintenance advanced systems of the Industry 4.0 are based on predictive maintenance that guarantees remarkable benefits in terms of reliability and safety, and allows the implementation of e-maintenance systems and the development of new business models.
The main characteristic of a predictive maintenance system is the way in which it collects and elaborates signals with the use of advanced diagnostic and prognostic algorithms.
In this sense, the DiaPro4.0 project aims to develop a competitive cost system, integrated in electromechanical drives, able to diagnose faults in rotors, gears, bearings and electric motors, to predict the Remaining Useful Life and to update the models used in the design phase on the basis of the data acquired on the machines in exercise.

The project involves regional laboratories with experience and competence in the field of mechanical transmissions, Diagnostics and Prognostics.
Also two companies take an active part in the project: Bonfiglioli S.p.A and Marposs S.p.A.


– the development of an innovative torque/speed sensor enabling indirect torque measurement from shaft angular positions
(Bonfiglioli patent);
– the integration of several sensors (torque, speed, temperature, vibration) in a single device, totally wireless and equipped with an energy harvesting system (Bonfiglioli patent);
– the development of diagnostic and algorithms, enabling Remaining Useful Life evaluation on the basis of the actual operational history (torque/ speed);
– the development of decisional algorithms;
– data transfer to the cloud.


1. High diagnostic reliability
identification of pitting in gears with an advance of 100h from machine downtime and bearing defects with an advance of 150h respect to catastrophic damage;

2. High prognostic accuracy
estimate of Remaining Useful Life with a confidence range of ± 5%;

3. Cost of the industrialized system
less than 30 to 50% of the systems on the market with performance inclusive of prognostics.