Today the industrial ecosystem is experiencing a real transformation. With Industry 4.0 and its enabling technologies we are facing a transition from the old factory model to the new Smart Factory. In this context, quality standards (e.g. ISO 9001:2015) promote the application of predictive maintenance systems in Companies, to the point this has become a certification criterion. Predicting and consequently scheduling the appropriate maintenance action, through online or offline condition monitoring, is crucial, not only in terms of cost-savings over routine preventive maintenance but also for ensuring higher quality products. In this frame, one wonders whether it is possible to highlight a deviation of process quality using the same information and data collected for predictive maintenance purpose.