Digital Industry
Approach & Solution
Approach
However, that information is not directly useful for process planners to improve the productivity or the quality of the manufactured products. The main limitations of current implementations are: large amounts of data with little information, lack of information about the product quality, unreliable data, reactive (instead of proactive) product quality optimization, lack of data exchange between the supply chain actors, lack of product traceability.
InterQ develops a platform to increase the quality of European smart manufacturing, exploiting its full potential.
Solution
- InterQ-Process: monitors the quality of manufacturing processes, producing Process-level Quality Hallmarks
- InterQ-Product: controls the quality of finished products/parts, producing Product-level Quality Hallmarks
- InterQ-Data: evaluates the quality of collected data, producing Data-level Quality Hallmarks
- InterQ-TrustedFramework: ensures the trustworthy traceability of PPD Quality Hallmarks across the entire supply chain, in which Engineering gave its main contribution
- InterQ-ZeroDefect: leverages on PPD Quality Hallmarks to improve the overall manufacturing quality
Results
Estimate process variables close to processing point
Measure final product quality in-process using digital twins
Ensure data reliability
Optimize the product quality based on AI
Ensure security and traceability
Project value
Innovation
Process performance
Enabling Technologies
Digital Twin
IoT
Blockchain
AI Advanced Analytics
Project Team
Research & Innovation