Research Project

i4Q: Industrial Data Services for Quality Control in Smart Manufacturing

ABSTRACT
A suite of solutions to manage the huge amount of industrial data coming from interconnected factory devices for supporting manufacturing monitoring and control.

Where: international
Challenge
Manufacturing companies are continuously facing the challenge of redesigning and adjusting their systems to produce goods adapted to specific requirements and produced under the minimum required production rate, guaranteeing high quality and limiting the use of resources. Therefore, reducing waste, scraps and defects, as well as production costs and lead times is crucial to increase productivity.
Approach
Moreover, a successful smart factory needs to manage data-related processes along the entire data life cycle, including data collection, storage, distribution, analysis, use, and deletion, to ensure high data quality at all times. The i4Q aims to provide a complete solution able to manage the huge amount of industrial data for supporting manufacturing online monitoring and control.
Digital Ecosystem
Solution
Digital Ecosystem
The i4Q Project's response consists of an IoT-based Reliable Industrial Data Services (RIDS), a complete suite composed of 22 i4Q Solutions, founded on a modular Framework, rooted in a Reference Architecture. The i4Q RIDS supports the complete flow of industrial data, starting from data collection to data analysis, simulation and prediction. It provides solutions to ensure data quality, security and trustworthiness. Engineering is responsible of the design of the Reference Framework which incorporates the business, usage, functional and implementation viewpoints and supports the validation actvities in the WHIRLPOOL and BIESSE pilots. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 958205.
Results
Technologies

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