Venue & metadata

• Journal/Proceedings: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
• Volume: 482 LNICST
• Pages: 133 – 146
• Note: Cited by: 1
• Author keywords: Artificial intelligence; cloud computing; domain specific language; performance evaluation; process engineering

Abstract

Processes in chemical engineering are frequently enacted by one-of-a-kind devices that implement dynamic processes with feedback regulations designed according to experimental studies and empirical tuning of new devices after the experience obtained on similar setups. While application of artificial intelligence based solutions is largely advocated by researchers in several fields of chemical engineering to face the problems deriving from these practices, few actual cases exist in literature and in industrial plants that leverage currently available tools as much as other application fields suggest. One of the factors that is limiting the spread of AI-based solutions in the field is the lack of tools that support the evaluation of the needs of plants, be those existing or to-be settlements. In this paper we provide a Domain Specific Language based approach for the evaluation of the basic performance requirements for cloud-based setups capable of supporting chemical engineering plants, with a metaphor that attempts to bridge the two worlds. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Keywords

Artificial intelligence GS Bridges GS Industrial plants GS Problem oriented languages GS Application fields GS Cloud-computing GS Domains specific languages GS Dynamic process GS Empirical tuning GS Feedback regulation GS New devices GS One of a kind GS Performance requirements GS Performances evaluation GS Process engineering GS

Links & artifacts

DOI Publisher Copy BibTeX Download .bib

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Suggested citation

Campanile, L., Di Bonito, L. P., Gribaudo, M., & Iacono, M. (2023). A Domain Specific Language for the Design of Artificial Intelligence Applications for Process Engineering [Conference paper]. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 482 LNICST, 133–146. https://doi.org/10.1007/978-3-031-31234-2_8