Automation of Automation: Mapping LLM Capabilities to the Modular Plant Engineering Workflow

Publikation: Beitrag zu KonferenzenPaperBeigetragenBegutachtung

Abstract

Large Language Models (LLMs) have shown promising capabilities in supporting and automating a variety of clearly defined, structured tasks. The engineering of modular plants also follows standardized workflow structures and uses standardized artifacts such as P&IDs, flow diagrams or HAZOPs. Therefore, the engineering of modular plants has the potential to be significantly supported or automated by AI tools. The articles objective is to determine which aspects of the modular plant engineering workflow could be supported or automated by LLMs. This is done by reviewing the current state of the art and combining the modular plant engineering workflow which LLM-based capabilities for engineering support. This leads to two results. First, a mapping of current LLM capabilities to the steps within the modular plant engineering workflow. Second, a theoretical assessment of the general LLM capabilities in terms of their usefulness for the tasks within the modular plant engineering workflow. All in all, the proposed mapping of LLMs to the modular plant engineering workflow provides an overview of the ways in which LLMs can support engineers. In addition, the LLM capability assessment provides insights into the current state of the LLMs abilities and highlights where further research and development is needed.

Details

OriginalspracheEnglisch
Seiten1-8
Seitenumfang8
PublikationsstatusVeröffentlicht - 9 Sept. 2025
Peer-Review-StatusJa

Konferenz

Titel30th IEEE International Conference on Emerging Technologies and Factory Automation
KurztitelETFA 2025
Veranstaltungsnummer30
Dauer9 - 12 September 2025
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtUniversity of Porto
StadtPorto
LandPortugal

Externe IDs

ORCID /0000-0001-5165-4459/work/191533914
ORCID /0000-0003-3368-4130/work/191534640
Scopus 105021812534

Schlagworte

Schlagwörter

  • modular plant, process control systems, large language model, artificial intelligence