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LLM-Powered Operator Advisor for Human-Robot Collaboration in Sustainable Assembly-Disassembly Cells

Mahboobe Kheirabadi, Elham Ghorbani, Samira Keivanpour

发表年份
2025
引用次数
2

摘要

In response to the manufacturing shift toward customization and human-centered approaches in Industry 5.0, this paper presents a conceptual framework for a virtual operator advisor based on the Large Language Model (LLM). The LLM-powered advisor processes real-time data from the assembly or disassembly line, classifying it into operational efficiency, ergonomics, and sustainability metrics to deliver context-aware, adaptive guidance tailored to each task. It is achieved by cross-referencing these data with domain knowledge stored in the database and LLM capabilities. The Advisor recommends actions toward operations optimization, potential cognitive and physical strains, and environmental responsibility. As a framework that promotes workflow adaptability, sustainability, and worker well-being, it can contribute to the evolution of human-robot collaboration in modern manufacturing.

关键词

WorkflowPersonalizationDomain (mathematical analysis)Operator (biology)SustainabilityFlexibility (engineering)Conceptual modelConceptual framework

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