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论文编号：	15018
作者编号：	2320224286
上传时间：	2024/12/9 15:36:11
中文题目：	X公司智能视觉检测设备开发项目进度管理优化研究
英文题目：	Research on the development progress of intelligent visual inspection equipment of X Company
指导老师：	李凯
中文关键字：	AI人工智能；视觉检测；项目进度管理
英文关键字：	Artificial intelligence; Vision inspection; Schedule management
中文摘要：	摘 要 智能视觉检测设备作为智能制造环节中的重要一环，已成为稳定生产运行、保障产品质量、提升制造效率的核心手段，对加快制造业高端化、智能化、绿色化发展，提升产业链供应链韧性和安全水平，支撑制造强国、质量强国和数字中国建设具有重要意义。当前，国外智能视觉检测设备的研究已经取得了很大的进展，基于人工智能、大数据、3D成像和机器人过程自动化等领域的发展，其技术应用在不断扩展，有效地推动了行业的前进。国内起步较晚，正处于快速发展期。目前政府高度重视智能检测装备产业的发展，2023年2月，七部门联合印发《智能检测装备产业发展行动计划（2023—2025年）》，旨在推动智能检测技术满足制造工艺需求，提升核心零部件和整机装备供给能力，提出到2025年，将培育30家以上智能检测装备专精特新“小巨人”企业，打造10个以上产业领军创新团队。尽管前景广阔，但是国内的智能检测装备产业仍然面临基础薄弱，创新能力不强，专业人才缺乏，上游供应系统不健全，市场认可度不高等问题。其中，AI算法可解释性差，设备的表现未达预期，缺乏数据输入标准且开发成本高成为困扰行业发展的三大难题。 X公司作为行业内智能视觉检测设备的头部研发和制造企业，专注于人工智能算法、大数据应用、机器视觉、数智工厂等前沿技术研发与创新，其主要产品为智能视觉检测设备。在设备开发过程中由于人员素质问题，项目管理问题，专业技术问题等多种因素导致多个项目在交付过程中存在延期情况。本文基于专家访谈与案例分析法首先找到智能视觉检测设备在开发交付过程中的主要问题，然后通过对于问题的深度分析归纳出能够影响或解决问题的关键要素。基于关键要素结合科学的项目管理方法给出智能视觉检测设备在开发过程中的管理优化方案。其中用到研究方法包括案例分析法，定性分析法，专家访谈法。涉及的管理工具有WBS工作结构，RAM项目责任矩阵，基于PERT及专家预测的项目活动持续时间预测。通过运用科学的项目管理方法，结合X公司实际情况，在给出具体优化解决方案。最后通过全面细致的人员培训，标准化设计方案及建立专家评审制度等方式保障优化方案的顺利实施。 本研究通过对于智能视觉检测设备开发的研究，能够丰富学术资源，为研究人员提供更多的研究思路和方法。于此同时，通过进一步的研究和学术交流，可以为该领域提供更多的思路与方法，推动技术的创新和应用。本文的解决策略在项目实践中已得到验证，通过实施这些策略，可以显著提高智能视觉检测设备的开发效率，缩短开发周期，保障项目按时交付。这些研究成果也为相关领域的研究和实践提供了新的视角和方法论。 关键词： AI人工智能；视觉检测；项目进度管理
英文摘要：	Abstract Intelligent visual inspection equipment, as an important part of the intelligent manufacturing link, has become a core means to stabilize production operation, ensure product quality and improve manufacturing efficiency, which is of great significance to accelerate the high-end, intelligent and green development of the manufacturing industry, improve the resilience and safety level of the industrial chain and supply chain, and support the construction of Chinese industry as a strong manufacturing, a strong quality and a digital country. At present, the research of foreign intelligent vision inspection equipment has made great progress, based on the development of artificial intelligence, big data, 3D imaging and robot process automation and other fields, its technical application is constantly expanding, effectively promoting the industry forward. China started late and is in a period of rapid development. At present, the government attaches great importance to the development of intelligent testing equipment industry, in February 2023, seven departments jointly issued the "Intelligent testing equipment Industry Development Action Plan (2023-2025)", aimed at promoting intelligent testing technology to meet the needs of manufacturing processes, improve the supply capacity of core components and complete equipment, proposed that by 2025, It will cultivate more than 30 intelligent testing equipment specialized new "little giant" enterprises, and create more than 10 industry leading innovation teams. Despite the broad prospects, the domestic intelligent testing equipment industry still faces weak foundation, weak innovation ability, lack of professionals, upstream supply system is not perfect, and market recognition is not high. Among them, the poor interpretability of AI algorithms, the performance of equipment has not met expectations, the lack of data input standards and the high development cost have become the three major problems plaguing the development of the industry. As the leading R&D and manufacturing enterprise of intelligent vision inspection equipment in the industry, X company focuses on the R&D and innovation of cutting-edge technologies such as artificial intelligence algorithm, big data application, machine vision, and digital intelligence factory. Its main products are AI intelligent vision inspection equipment. In the process of equipment development, many factors such as personnel quality problems, project management problems, professional and technical problems lead to delays in the delivery of many projects. Based on expert interviews and case analysis, this thesis first finds the main problems in the development and delivery process of AI intelligent vision inspection equipment, and then concludes the key elements that can affect or solve the problems through in-depth analysis of the problems. Based on the key elements and scientific project management method, the management optimization scheme of AI intelligent visual inspection equipment in the development process is presented. The research methods used include case analysis, qualitative analysis and expert interview. The management tools involved are WBS work structure, RAM project responsibility Matrix, project activity duration prediction based on PERT and expert prediction. Through the use of scientific project management methods, combined with the actual situation of X company, specific optimization solutions are given. Finally, through comprehensive and detailed personnel training, standardized design scheme and the establishment of expert review system to ensure the smooth implementation of the optimization scheme. Through the research on the development of intelligent detection equipment, this thesis can enrich academic resources and provide more research ideas and methods for researchers. At the same time, through further research and academic exchanges, more ideas and methods can be provided for this field to promote the innovation and application of technology. The solution strategies in this paper have been verified in the project practice. By implementing these strategies, the development efficiency of AI intelligent visual inspection equipment can be significantly improved, the development cycle can be shortened, and the project can be delivered on time. These thesis results also provide a new perspective and methodology for research and practice in related fields. Key words：Artificial intelligence; Vision inspection; Schedule management
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