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论文编号：	15604
作者编号：	2320234048
上传时间：	2025/12/8 10:21:38
中文题目：	基于精益思想的T公司安全播出运维管理优化研究
英文题目：	Research on the Optimization of Safety Broadcasting Operation and Maintenance Management of Company T Based on Lean Thinking
指导老师：	林润辉
中文关键字：	精益思想；人工智能；IPTV；安全播出；运维管理
英文关键字：	Lean Thinking;Artificial Intelligence;IPTV;safe broadcasting;operation and maintenance management
中文摘要：	本研究深入探讨了在精益思想的理论框架下，引入人工智能（AI）技术在优化T公司IPTV安全播出运维管理中的融合应用，旨在应对传统运维管理模式普遍存在被动管理、流程复杂、智能化不足和人才匮乏等问题，这些问题不仅导致效率低下和成本高昂，更带来了不确定的安全风险。为解决这些问题，本研究通过精益思想原则和八方面的浪费，以及鱼骨图系统性地剖析了IPTV运维管理问题。深入揭示了这些浪费对运维效率和安全播出的深层影响。 在此基础上，本研究提出了一种引入人工智能技术的IPTV安全播出运维管理优化方案，该方案将精益的系统化方法论与人工智能的先进技术深度融合，强调了数据治理与基础设施建设的重要性，本地化部署以保障数据安全，以及构建IPTV专用RAG知识库和多Agent协同工作流，从而实现以人为中心的人机协同模式，将人类员工从重复性任务中解放出来，形成了一种强大的协同增效机制，旨在实现运维的持续改进管理。 研究结论表明，这种优化方案能够明显提升IPTV安全播出的运维管理效率，大幅降低运维成本。本研究的创新点在于提出了精益思想与人工智能的深度融合应用，细致识别了IPTV运维中的八种浪费并提出了人工智能赋能的消除路径，聚焦广播电视安全播出这一核心领域，并强调了人机协作与文化变革的重要性。为推动IPTV安全播出运维管理的智能化与可持续发展提供了实践路径，为行业的高质量发展提供了有力支撑。
英文摘要：	This thesis delves deeply into the integrated application of artificial intelligence (AI) technology in optimizing the IPTV safe broadcasting operation and maintenance management under the theoretical framework of lean thinking, aiming to address the common problems in traditional operation and maintenance management models, such as passive management, complex processes, insufficient intelligence, and talent shortages. These issues not only lead to low efficiency and high costs but also bring uncertain security risks. To solve these problems, this thesis systematically analyzes the IPTV operation and maintenance management issues through the principles of lean thinking and the eight wastes, as well as the fishbone diagram, revealing the deep impact of these wastes on operation and maintenance efficiency and safe broadcasting. On this basis, this thesis proposes an optimized solution for IPTV safe broadcasting operation and maintenance management by integrating the systematic methodology of lean thinking with the advanced technology of artificial intelligence. It emphasizes the importance of data governance and infrastructure construction, local deployment to ensure data security, and the construction of an IPTV-specific RAG knowledge base and multi-Agent collaborative workflow, thereby achieving a human-centered human-machine collaborative model that liberates human employees from repetitive tasks and forms a powerful synergy mechanism, aiming to achieve continuous improvement in operation and maintenance management. The thesis conclusion indicates that this optimization solution can significantly enhance the efficiency of IPTV safe broadcasting operation and maintenance management and greatly reduce operation and maintenance costs. The innovation of this thesis lies in proposing the deep integration of lean thinking and artificial intelligence, meticulously identifying the eight wastes in IPTV operation and maintenance and proposing AI-enabled elimination paths, focusing on the core area of safe broadcasting in radio and television, and emphasizing the importance of human-machine collaboration and cultural transformation. It provides a practical path for the intelligent and sustainable development of IPTV safe broadcasting operation and maintenance management, offering strong support for the high-quality development of the industry.
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