Self-X, artificial intelligence for the European industry

The overall objective of s-X-AIPI is to research, develop, test and experiment an innovative toolset of custom trustworthyself-X AI technologies and applications for workers to deal with external and internal influences and enable agile and resilient reaction of European process industry processes and products’ lifecycle for a true integration into the circular economy ecosystem.

The aim is to provide existing process industries and its workers with agility of operation, improvement of performance across different indicators and state of the art AI-based sustainability tools for the design, development, engineering, operation and monitoring of their plants, products and value chains.

Demonstration at four representative industrial use cases will generate a showcase portfolio of trustworthy AI technologies (data sets, AI model and applications) integrated into an innovative toolset available for industry and research as an example of self-X.

All technologies integrated in actual process industries’ value chains:

1. SID steel use case focuses on the optimised use of scrap (affected by disturbing elements like copper which are includes especially in low-quality external scrap) to produce high-quality steel products, avoid downstream surface quality problems and reduce process energy intensity (mainly in scrap melting Electric Arc Furnace EAF).

2. EIFFA asphalt use case focuses on circularity of the value chain (from quarry to road) respect the quality control of feedstock (aggregates, bitumen, recycled asphalt, …) the overall sustainable performance of the process (including asphalt paving) and the quality of final product (asphalt mix).

3. RCPE pharmaceutical use case focuses on the prediction of optimal settings in manufacturing of chemicals and active pharmaceutical ingredients involving solid/liquid suspensions, through ML based control strategy and report to human-in-the-loop.

4. IDALSA aluminium use case focuses on the optimization of recycling processes from (1) optimized scrap processes parameters by scrap and final products properties (quality and alloy contents) and (2) guiding through efficient recycling path (strategy) to reach desired quality and ensure circularity of the Al and the smallest environmental impact.

S-X-AIPI toolset of AI technologies will include an innovative AI data pipeline with autonomic computing capabilities (self-X AI and autonomic manager), architecture realistic datasets together with their respective algorithms derived from the demonstration in four realistic use cases of process industry. s-X-AIPI technologies will consider workers’ heterogeneous skill levels and self-adaptation capabilities to the actual profile of the worker] respecting their human-in-the-loop role.

 Deuser / s-X-AIPI
EIFFA asphalt use case focuses on circularity of the value chain (from quarry to road) respect the quality control of feedstock (aggregates, bitumen, recycled asphalt, …) the overall sustainable performance of the process (including asphalt paving) and the quality of final product (asphalt mix).