A maintenance worker in a remote factory, can pull up to a job site with a pair of AR glasses (or a tablet), and have at his disposal every piece of information necessary to perform their task (operating and maintenance tutorials and procedures, schematics, documentation, logs, alerts from sensors, etc.).
Moreover, a Predictive Maintenance application can forecast the increase of defect rates beyond a given quality threshold and trigger early warnings also visible through the AR application.
We apply anomaly detection algorithms and machine models for predicting and optimizing machine runtime windows.
Requirements gathering and mock-up design
Development of the AR application
Create ML models and develop Predictive Maintenance applications
Survey the acceptance by users on the field
Fine tune the application usability