Utilizing LLMs for Industrial Process Automation

Fuente: arXiv
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Main Author: Fares, Salim
Format: Preprint
Published: 2026
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author Fares, Salim
author_facet Fares, Salim
contents A growing number of publications address the best practices to use Large Language Models (LLMs) for software engineering in recent years. However, most of this work focuses on widely-used general purpose programming languages like Python due to their widespread usage training data. The utility of LLMs for software within the industrial process automation domain, with highly-specialized languages that are typically only used in proprietary contexts, remains underexplored. This research aims to utilize and integrate LLMs in the industrial development process, solving real-life programming tasks (e.g., generating a movement routine for a robotic arm) and accelerating the development cycles of manufacturing systems.
format Preprint
id arxiv_https___arxiv_org_abs_2602_23331
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Utilizing LLMs for Industrial Process Automation
Fares, Salim
Software Engineering
Artificial Intelligence
A growing number of publications address the best practices to use Large Language Models (LLMs) for software engineering in recent years. However, most of this work focuses on widely-used general purpose programming languages like Python due to their widespread usage training data. The utility of LLMs for software within the industrial process automation domain, with highly-specialized languages that are typically only used in proprietary contexts, remains underexplored. This research aims to utilize and integrate LLMs in the industrial development process, solving real-life programming tasks (e.g., generating a movement routine for a robotic arm) and accelerating the development cycles of manufacturing systems.
title Utilizing LLMs for Industrial Process Automation
topic Software Engineering
Artificial Intelligence
url https://arxiv.org/abs/2602.23331