PROGRAMS mapped on Significant innovations and lessons learned, training aspects

PROGRAMS aims at developing a HW/SW suite of solutions capable of:

1. Managing data relative to all maintenance strategies (including PdM) 
2. Evaluating the cost associated to different maintenance strategies and policies
3. Select and allocate the optimal maintenance Strategies (considering PdM) and Policies for each factory/machine assets (that minimise the overall cost)
4. Allowing the seamless transfer of information from all factory levels
5. Allowing easy PdM solutions deployment and exploitation
6. Optimizing integration of PdM based maintenance with production activities
7. Gathering and sharing maintenance information at all factory levels

PROGRAMS solution will allow SMEs to access the benefits of Predicitive Maintenance wilth limited costs.

Several challenges limit the succesfull application of Predictive Maintenance in factories:

1. Lack of pre-existing maintenance data: Industry 4.0 is only slightly improving the deployment of tools for collecting data
2. Difficult data synchronization: existing data is saved into tens of different formats and with different sampling frequencies
3. Lack of sensors data relative to equipment fault status: equipment is never purposefully left to reach such a degraded status and, even then, faults happens only few times a year (so there is an high chance of never seeing faults during project duration).

Predictive maintenance requires different skills and thus new professional figures will have to to be trained:

• Production equipment operators
• Maintenance operators
• Data scientists
• Maintenance managers
• Software developers