#4 Predictive maintenance and production optimization for closure manufacturing
In complex closures manufacturing (spirits closures can have up to 15 different components) several
production phases occur and different technologies and machinery are used. The objective of this testbed
is to establish an overall production management optimization and predictive maintenance.
Main foreseen activities for this testbed are:
1. to design and install redundant IoT modules able to log data at high sample rates, with best in
class security for transferring data to the backend where data is stored;
2. to fuse data coming from a first pilot series of machines;
3. to install a new module of the industrial IoT platform ThingWorx for predictive maintenance
and analytical solutions for performance improvement;
4. to integrate a data-driven anomaly detection system
Objectives
Remote monitoring to improve troubleshooting, allowing maintenance teams to remotely monitor and detect anomalies across all assets
Real-time asset performance and status visualization to provide production managers remote insight into production line performance, test connectivity, data access, scalability, company- wide device-to-cloud connectivity
Provision of analytical insight into industrial data, providing the ability to rapidly develop applications and data visualizations. This allow an increased visibility into the processes of GCL closures manufacturing units
Improved scheduling process leveraging real-time data from the production floor, properly linking it to the scheduling ERP system for optimizing the scheduling of production
Involved Partners
