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[2602.23331] Utilizing LLMs for Industrial Process Automation
Summary
This article explores the application of Large Language Models (LLMs) in industrial process automation, focusing on their potential to enhance software engineering practices in specialized programming contexts.
Why It Matters
As industries increasingly adopt automation, understanding how LLMs can be integrated into specialized programming tasks is crucial for improving efficiency and innovation. This research highlights a gap in existing literature, emphasizing the need for tailored approaches in industrial settings.
Key Takeaways
- LLMs have potential applications in specialized industrial programming languages.
- The research addresses a gap in the literature regarding LLMs in industrial automation.
- Integrating LLMs can accelerate development cycles in manufacturing systems.
- Real-life programming tasks, such as robotic arm movement, can benefit from LLMs.
- The study encourages further exploration of LLMs in proprietary contexts.
Computer Science > Software Engineering arXiv:2602.23331 (cs) [Submitted on 26 Feb 2026] Title:Utilizing LLMs for Industrial Process Automation Authors:Salim Fares View a PDF of the paper titled Utilizing LLMs for Industrial Process Automation, by Salim Fares View PDF HTML (experimental) Abstract: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. Subjects: Software Engineering (cs.SE); Artificial Intelligence (cs.AI) Cite as: arXiv:2602.23331 [cs.SE] (or arXiv:2602.23331v1 [cs.SE] for this version) https://doi.org/10.48550/arXiv.2602.23331 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Salim Fares [view email] [v1] Thu, 26 Feb 2026 18:38:00 UTC (55 KB) Full-text links: Access Paper: View a PDF of the paper titled Utilizing LLMs for Industrial Process Automation...
