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919,1920],"订单数据","预测数据","库存数据","价格数据",[1900,1922,1913,1915],"市场研究",{"scenario_code":1924,"scenario_name":1925,"rating":691,"pain_text":1926,"tools":1927,"knowledge_models":1933,"data_elements":1937,"talent_skills":1942},"SH01-ABCD-5-2","电子商务数字化","1.外部市场环境高度波动；2.线上竞争激烈应对挑战大",[1928,1929,1930,1931,1932],"电子商务销售","招标","采购","结算平台（如阿里巴巴","招标采购网等）",[1934,1935,1936],"销售模型","招标模型","采购模型",[1938,1939,1940,1920,1941],"商品数据","招标数据","合同数据","过程记录",[1943],"电子商务系统集成",{"scenario_code":1945,"scenario_name":1946,"rating":691,"pain_text":1947,"tools":1948,"knowledge_models":1954,"data_elements":1959,"talent_skills":1971},"SH01-ABCD-5-3","物流数字化","1.系统间接口协议不统一；2.订单数据输入准确性差；3.市场定价规则适应挑战；4.混合能源站点管理复杂；5.新能源利用集成需求；6.客户分析深度不足",[1949,1950,1951,1952,1953],"物流优化","收发货自动化","物流跟踪","化工品库存管理","智能加油站套件，客户评价，油品非油品贸易软件",[1955,1956,1957,1958],"物流管理","收发货规程","化工品销售定价模型","智能加油站模型，客户画像模型",[1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970],"物流计划","物流工具数据","物流作业状态","物流状态与定位数据","市场信息","化工品库存数据","加油站信息","油料数据","智能加油枪运行参数","客户信息","贸易数据",[1955,1972],"机械工程，化工工艺，大数据分析，贸易管理",{"scenario_code":1974,"scenario_name":1975,"rating":681,"pain_text":1976,"tools":1977,"knowledge_models":1979,"data_elements":1983,"talent_skills":1994},"SH01-ABCD-5-4","化工园区管理增效研、产、管、服数字化集成","1.跨组织协调困难；2.整体资源优化难度高",[1978],"化工园区管理套件",[1980,1981,1982],"涉及以上各个专业的模型如地图，安全预警，环境监测，安防及应急处置","物流","降本",[1984,1985,1986,1987,1988,1989,1990,1991,1992,1993],"园区地图","安全生产","环境","应急","安防","运输","能源","办公","运维","公共服务等",[1995],"涉及以上各个专业的基础专业知识，重点兼顾园区统筹全局性管理和协调",{"scenario_code":1997,"scenario_name":1998,"rating":686,"pain_text":1999,"tools":2000,"knowledge_models":2005,"data_elements":2012,"talent_skills":2028},"SH01-ABCD-1-10","催化剂电镜图像智能识别","1.标准化特征量化算法开发难​；2.跨学科人员协同的工具与沟通机制建立难；3.电镜特征与性能关联的知识图谱构建难",[2001,2002,2003,2004],"HPC可视化引擎","AI视觉感知","半导体AI质量检测","AI工业视觉检测",[2006,2007,2008,2009,2010,2011],"图像分割模型--U-Net++分割催化剂颗粒边界，支持晶粒尺寸统计","特征关联模型--图卷积网络（GCN）关联电镜形貌（如孔隙结构）与催化活性","异常监测模型--自编码器（VAE）识别制备缺陷（如团聚","裂纹），准确率大于95%","多模态融合模型--融合电镜图像与XRD\u002FXPS数据，预测催化剂稳定性","生成式模型--StyleGAN3生成虚拟电镜图像，扩充小样本训练集",[2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025,2026,2027],"电镜图像数据：类型--SEM（表面形貌）","TEM（晶体结构）","STEM-紧急泄压系统（元素分布）","分辨率1nm级高清图像","标注数据：人工标注--颗粒位置","尺寸","形状","自动标准--预训练模型辅助标注","元数据：实验条件--催化剂合成参数（温度","前驱体比例）","电镜设备型号","时间戳与版本--数据生成时间","标准修改记录","外部数据：文献库--关联Nature\u002FScience中相似催化剂的图像特征","专利数据--提取专利要求中的结构与图像对照",[2029,2030,2031,2032,1775],"数据科学家","材料科学家","软件工程师","AI算法工程师",{"scenario_code":2034,"scenario_name":2035,"rating":691,"pain_text":2036,"tools":2037,"knowledge_models":2043,"data_elements":2054,"talent_skills":2072},"SH01-ABCD-1-11","实验数据电子化存储提质增效n现状评级：\u002Fn工具链：进销存管理系统、ERP管理系统、CRM管理系统、工业互联网平台、低代码平台、智能工厂系统、智能生产系统、数据分析工具、数据可视化工具n数据链：包括生产运营数据（如生产计划、设备运维、能源消耗）、供应链数据（库存、物流、供应商信息）、市场与销售数据（市场需求、销售价格、销售渠道）、质量与安全数据（产品质量检测、安全生产记录）、研发与创新数据（研发项目进展、专利信息）以及人力资源与环境社会责任数据等","1.跨系统数据格式不统一，整合接口适配难​；2.多角色协作权限划分难，版本控制机制缺失​；3.数据结构化程度不足，智能分析模型落地难",[2038,2039,2040,2041,2042,2039],"流程管理工具","实验室信息管理系统","数据流程管理工具","数据记录与管理工具","科学数据管理系统",[2044,2045,2046,2047,2048,2049,2050,2051,2052,2053],"知识图谱：实体（试剂","设备）-关系（反应","依赖）网络，支持智能推理）","机器学习模型：分类模型--自动过渡实验类型（如合成","分析）","回归模型--预测试验结果（如收率","纯度）","流程模型：BPMN规范试验审批流程Petri网模拟资源冲突场景","语义模型：NLP工具解析实验记录中的关键结论","模板引擎：预置GLP\u002FGMP合规模板，减少人工填写错误",[2055,2056,2057,2058,2059,2060,2061,2062,2063,2064,2065,2066,2067,2068,2069,2070,2071],"核心数据：试验参数（温度","pH值）","样本信息（批次","来源）","原始数据（仪器输出文件）","元数据：操作人员","时间戳","设备ID\\环境条件（温湿）","衍生数据：统计分析结果","AI模型预测报告","合规审核日志","非结构化数据：实验室图像（显微镜照片）","手写笔记扫描件","语音备忘录","关联数据：参考文献（DOI链接）","化学品安全数据表（SDS）","实验SOP（标准操作规程）",[2073,2074,2075,2076],"软件开发能力","数据分析能力","领域专家，精通实验室操作规程和行业法规","平台运维和安全管理",{"scenario_code":2078,"scenario_name":2079,"rating":686,"pain_text":2080,"tools":2081,"knowledge_models":2084,"data_elements":2089,"talent_skills":2096},"SH01-ABCD-1-12","工艺装置智能专家远程诊断优化","1.远程协作系统搭建与专家资源整合难​；2.多源异构数据整合与标准化适配难​；3.隐性知识数字化沉淀与传承机制缺失​；4.实时数据驱动的动态优化模型构建适配难",[1864,2082,2083],"化工流程模拟软件","工艺模拟与优化软件",[2085,2086,2087,2088],"故障诊断图谱","动态优化模型","数字孪生体-机理模型与实时数据融合","语音-数据关联模型",[2090,2091,2092,2093,2094,2095],"装置操作实时数据","LIMS数据","设备历史数据","设备振动数据","工艺知识库","多模态数据",[2097,2098,2032,2099],"工艺诊断专家","工业数据工程师","远程协作架构师",{"scenario_code":2101,"scenario_name":2102,"rating":681,"pain_text":2103,"tools":2104,"knowledge_models":2109,"data_elements":2114,"talent_skills":2129},"SH01-ABCD-1-13","新工艺中试与工业试验装置数字孪生反演增效提质降本新模式石化行业数字化转型场景图谱（2025版）（3\u002F5）A石油炼制环节B基础有机化学品生产环节C高分子材料生产环节D高分子合成与成型环节","1.数字孪生系统对反应器等核心单元模拟的技术适配难；2.小试与工业级实验数据量有限，数理建模精度难突破；3.数字孪生全流程与运行工况灵活配置应用技术难落地",[2105,2106,2107,2108],"流程工业动态模拟软件","数字孪生仿真","分布式控制系统","智能制造",[2110,2111,2112,2113],"机理-数据融合模型","故障模式库","材料性能图谱","经济优化模型",[2115,2116,2117,2118,2119,2120,2121,2122,2123,2124,2125,2126,2127,2128],"试验原始数据，包括温度","压力","流量的实时数据","在线光谱等监测浓度数据","化验分析数据","设备状态数据，包括反应器振动频率","腐蚀速率","密封泄漏监测","材料特性数据，包括催化剂比表面积","机械强度","抗积碳性能","原料价格数据","专利数据","国际标准等",[2130,2029,2131,2132,2133],"精通反应工程的工艺工程师","建模专家","工业软件架构师","安全合规专家",{"scenario_code":2135,"scenario_name":2136,"rating":681,"pain_text":2137,"tools":2138,"knowledge_models":2140,"data_elements":21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