Smart maintenance uses every information system to manage and schedule routine maintenance in order to make it efficient and effective.
Smart maintenance uses all the sensors and monitoring systems already available in the machine, plus other exclusive MCM equipment, to generate a flow of information that is then processed using sophisticated algorithmic techniques. Once aggregated and synthesised, the information content is stored and compared with statistical data and critical thresholds, in order to identify any trends of system degradation. In this way, it is possible to obtain a prospect of the status of the plant and the process, which allows to plan maintenance with timely interventions, made in already scheduled steps. Typical examples of monitoring strongly suggestive for the detection of system drifts are: the comparison over time in the performance of typical cycles, the check over time of decreases in fluid levels, changes in absorption of the axes, the evolution over time of tool vibration phenomena, etc.
In MCM plants, the information flow crosses the supervision node of the production cell, which provides for data contextualization, and is sent to an exclusive cloud service. Here, automatic learning algorithms train statistical models, calculate synthetic indexes and control charts to which secure access to the customer organization is guaranteed, for the management of diagnostic processes and predictive maintenance.