MdM 4.0 – Machine-driven Maintenance: machine-driven maintenance in the Engineering Industry

Project Description

Within the context of predictive maintenance, this project develops a dialogue system to detect anomalies, showing graphically on the 3D model ongoing problems and the necessary maintenance. This system captures information by connecting working machines and DIGITAL ADVANCED VISUALIZATION (DAV – Sygest product). Indeed, this is a predictive maintenance system capable of improving productivity through early identification of problems and capable of estimate when the maintenance should be performed. All data generated during the interaction between machines and the DAV software are transmitted and stored on the cloud in order to effectively and efficiently support future strategic and operational decisions.


The market analysis conducted by Sygest through meetings with its customers or mechanical engineering companies within Sygest’s target customer base suggests that the topic of ‘Industry 4.0’ is of a great interest. As a matter of fact, in the context of Industry 4.0, preventive maintenance software is not only a necessity but also a gradual evolution towards increasingly efficient production processes with a view to reducing waste and increasing margins. Our solution is innovative for the target (machine suppliers with medium-sized turnover) and our goal is to be among the first to propose this cutting-edge solution of predictive maintenance.


The fulfillment of this project will allow Sygest to gain a position of absolute advantage over other competitors (we are talking about those who make documentation software for machine servicing) thanks to a predictive maintenance product with extremely advanced machine learning, which creates a highly collaborative relationship with machine and plant suppliers. This should lead to a considerable increase in turnover and continuity overtime on software and related project maintenance. Project co-financed by the European Regional Development Fund

Project co-financed by the European Regional Development Fund