Industrial Data Platforms For Real-Time Artificial Intelligence In The Chemical Industry

The DAP2CHEM project aims to stimulate the transition of chemical and life science companies towards I4.0. The project will generate generic knowledge for real-time data usage by these companies through AI systems for improved process development, optimisation and manufacturing excellence.

Challenges and hurdles

Industry 4.0 (I4.0), Artificial Intelligence (AI) and digitalisation are revolutionising industries across the globe. As underlined by Catalisti’s 2019 DIGICHEM study, chemical, pharmaceutical, and plastics-producing and -processing companies are interested in implementing Big Data Analysis and AI in their production processes in order to generate business value. Yet, implementation of these technologies within the sector remains rather limited due to a range of sector-specific challenges and hurdles.

DAP2CHEM

To overcome some of these hurdles, DAP2CHEM aims to stimulate the transition of chemical and life science companies towards I4.0. The project will generate the necessary generic knowledge for real-time data usage by these companies through AI systems for improved process development, optimisation, and manufacturing excellence in the chemical and life science industry. It will also expand the knowledge base at Flemish research institutes concerning (hyperspectral) image processing and analysis, advanced analytics and hybrid AI, thereby bridging the gap between academic fundamental knowledge and applicability in an industrial context (explainability and integratability).

Achieving these project goals requires expertise in both Operational Technologies (OT) and Information Technologies (IT) for the process and discrete manufacturing industry. Cronos, an early actor in the I4.0 space, will provide this expertise.

At Convolve we worked on creating the architecture and technological implementation to run the AI models for Janssen Pharmaceutics and Ajinomoto Biopharma Systems. This combines a deep knowledge of cloud, IoT and IT/OT integration!

This work is part of the DAP2CHEM Catalisti project