标题： 大型语言模型在制造服务任务自动化中的影响 显示英文标题

标题： The Impact of Large Language Models on Task Automation in Manufacturing Services

摘要： 本文探讨了大型语言模型（LLMs）在生产机械行业提供技术服务中的任务自动化潜力。通过专注于文本校正、摘要生成和问答，研究展示了LLMs如何提高运营效率和客户支持质量。通过原型设计和分析真实客户数据，研究表明LLMs能够可靠地纠正错误，生成复杂通信的简洁摘要，并提供准确且具有上下文感知的客户查询响应。研究还将检索增强生成（RAG）集成进来，以结合LLM输出与领域特定知识，从而提高精确度和相关性。尽管研究结果突显了显著的效率提升，但诸如知识幻觉和与人类工作流程的整合等挑战仍然是大规模采用的障碍。本研究有助于理论理解和实际应用LLMs在制造业中的作用，为可扩展的、特定领域的实施铺平了道路。 显示英文摘要

摘要： This paper explores the potential of large language models (LLMs) for task automation in the provision of technical services in the production machinery sector. By focusing on text correction, summarization, and question answering, the study demonstrates how LLMs can enhance operational efficiency and customer support quality. Through prototyping and the analysis of real-life customer data, LLMs are shown to reliably correct errors, generate concise summaries of complex communication, and provide accurate, context-aware responses to customer inquiries. The research also integrates Retrieval Augmented Generation (RAG) to combine LLM outputs with domain-specific knowledge, enhancing precision and relevance. While the findings highlight significant efficiency gains, challenges such as knowledge hallucination and integration with human workflows remain barriers to large-scale adoption. This study contributes to the theoretical understanding and practical application of LLMs in manufacturing, paving the way for further research into scalable, domain-specific implementations.