The experiment host (POLYCOM) is mid-cap company specialized for moulding processes whose manufacturing floor consists of more than 110 moulding machines along with a range of moulding tools. To maximize their availability and hence production quality and efficiency, these highly distributed assets need to be continuously supervised.
To support these business objectives thorough the increase utilization of production data, this experiment will explore the possibilities to integrate the data using interoperability standards, exploit the data for predictive maintenance and zero defect production while employing novel AI and local edge processing solutions. The experiment aims to validate and demonstrate the adoption of the smart production monitoring solution for injection moulding processes.
Use-Case is a small-scale demo/experiment (for one production cell/process) of predictive maintenance scenario in POLYCOM. The scenario, within AI REDGIO 5.0 project, will consist of data infrastructure, edge device and algorithms that will detect and measure the condition of the moulding tools. Demonstrated system will enable operators to continuously monitor the condition of machines and tools and general process operations (changes/events on daily base). Predictive maintenance will be based on active monitoring the production process, where several data sources will be gathered from the production set-up (material, production parameters and signals, end-quality measurements). Deviations in the performance of specific asset (tool and machine) will be monitored using AI technologies deployed on the local edge device.