Strategies and Predictive Maintenance models wrapped around physical systems for Zero-unexpected-Breakdowns and increased operating life of Factories

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Realtime optimisation

A real-time adaptive simulator with high fidelity will be a demonstrator (remote or local) of the machine’s state, in which a fast-forward simulation mechanism (prognostic models) predicts the potential events of breakdown of components and machines. What-if capabilities will allow the maintenance planners to find the most effective and cost-efficient schedules for component replacement and maintenance plans.

Autonomous /online/realtime Manufacturing Process Optimisation on factory level

Strategies to improve maintainability and increase operating life of production will be applied to update the existing and to develop a set of new strategies based on real data in order to improve maintainability and operating life of production systems. This approach will use a method to translate optimization objectives defined at production and factory levels, into optimized maintenance policies at asset/production process levels.

Autonomous /online/realtime Manufacturing Process Optimisation on machine level

At the asset and machine level, the Z-BR3AK solution will perform a condition monitoring and generate health status reports. Attention will be given to the faults detection through FMEA analysis (FMECA) to allow remedial actions and synchronise the manufacturing process. The proposed engine will perform monitoring, inspection and control at component, machine, system and product level to issue warnings, alerts (e.g. about deviations from production and quality requirements), reports on (potential) failures or failure prone situations and pass related information to a higher-level Z-Bre4k DSS (for decision support at manufacturing and enterprise level).