Engineering: leader della Digital Transformation

Engineering Innovation in

Digital Industry


OK-INSAID: data and technologies for the factory of the future

A research project aimed at developing an advanced and integrated platform that leverages the value of data to improve products, processes and maintenance policies.

Approach & Solution



New technologies have paved the way for the 4th industrial revolution, a phenomenon that is transforming the factory into a veritable laboratory of technological innovation.

The project we are coordinating is riding this wave. It was created with the aim of developing a smart factory platform that allows greater integration between ever more advanced production lines.

The entire system is based on the effective deployment of networks, communication protocols and cloud, as a virtual site for storing and processing data. In addition, particular attention is given to issues of data security and to the usage of the “Digital Twin” as a virtual copy of the factory on which “experiments” can be carried out and alternative scenarios predicted.


The solution is based on the integration of various technologies, including:
  • IoT, which provides sensors for production lines and generates big data (which are then collected and processed).
  • Artificial Intelligence, which defines models and algorithms (such as analytics libraries) that can be applied in production line maintenance for analysing product quality and making production processes more efficient.

Project outcomes will be validated in four tests coordinated by leading global manufacturers:
  • Zero Defect Manufacturing (ZDM) by Centro Ricerche Fiat/FCA.
  • Predictive maintenance by AVIO.
  • Models for cyber-physical system (CPS) factories by AVIO.
  • Process control cycles: diagnostics and predictive analytics by SACMI.

The project is funded with PON Research and Innovation 2014-2020 and FSC funds. .


Support for product and process improvement

Improved maintenance policies

Greater business competitiveness

Project value

Process performance

Enabling Technologies

AI & Advanced Analytics
Digital Twin

Project Team

Research & Innovation