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GCRI · 先进产业与机器人

材料与制造

New materials and manufacturing methods, from advanced alloys and composites to additive manufacturing and precision processes, change what can be made and where. They also bring new quality, safety and supply questions. This page sets out how materials and manufacturing innovation reaches production, how quality and capacity are measured, and what evidence serves the manufacturers, standards bodies and agencies involved.

01登记

Materials and manufacturing on the record.

02问题

Materials and manufacturing: how the risk develops.

Advanced materials, additive processes and circularity. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.

机制

Qualification takes longer than invention

A new material or process must be qualified for each application, with testing and certification by customers and regulators. This often takes years.

机制

Additive manufacturing changes supply

3D printing allows local, on-demand production of complex parts, but quality varies with machine, material and process settings.

机制

Quality depends on process control

Variability in raw materials and processes leads to defects. Statistical process control and inspection keep quality within limits.

机制

Inputs can be scarce

Speciality materials, powders and alloys may come from few suppliers, exposing manufacturers to shortages and price swings.

03地理

德国的基础设施暴露。

德国的夜间灯光、人口密度和洪水水体,来自 NASA GIBS。每个图层均标有各自日期。

交互式地图需要JavaScript;图层列表和来源见下文。

图层 3

本页面的基础设施暴露

关于本图层
证据
观测
来源
VIIRS Black Marble(VNP46A2)(NASA LAADS DAAC)
提供方
NASA LAADS DAAC
许可协议
NASA 开放数据
年份版本
每日;卫星辐射亮度,已校正月光和大气影响
构建时的最新内容
2026-10-12
处理结果
约 500 米网格
不确定性
所示日期的卫星夜间辐射亮度;灯光是用电和停电的替代指标,并非对供应或获得电力情况的测量。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
估计值
来源
世界网格化人口 v4.11(NASA SEDAC(哥伦比亚大学 CIESIN))
提供方
NASA SEDAC(哥伦比亚大学 CIESIN)
许可协议
CC BY 4.0
年份版本
null;基于人口普查的估算,静态(2020)
处理结果
约 1 公里网格
不确定性
基于人口普查的 2020 年每平方公里人口估算,作为风险暴露背景展示;不是受任何危害影响的人数。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
观测(云层造成缺口)
来源
VIIRS 全球洪水产品(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星探测;云层造成缺口
构建时的最新内容
2026-10-14
处理结果
约 250 米网格
不确定性
卫星探测;云层造成缺口。卫星或模型栅格数据,按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声;数值是指标,而非某地的测量值。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
观测
来源
VIIRS NOAA-20 校正反射率(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星图像
构建时的最新内容
2026-10-14
处理结果
约 250 米网格
不确定性
卫星图像。卫星或模型栅格数据,按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声;数值是指标,而非某地的测量值。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
模型生成(GIBS 发布的最新年份)
来源
MODIS Terra 和 Aqua 土地覆盖(MCD12Q1)(NASA LP DAAC)
提供方
NASA LP DAAC
许可协议
NASA 开放数据
年份版本
每年;卫星分类;GIBS 发布的最新年份
构建时的最新内容
2024-01-01
处理结果
约 500 米网格
不确定性
所示年份的卫星土地覆盖类别,含农田;该分类存在已知误差,并非农场登记册。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问
关于本图层
证据
观测(云层造成缺口)
来源
MODIS Terra EVI(NASA LANCE)
提供方
NASA LANCE
许可协议
NASA 开放数据
年份版本
每日;卫星指数;云层造成缺口
构建时的最新内容
2026-10-13
处理结果
约 250 米网格
不确定性
截至所示日期 8 天的卫星植被指数,是栖息地状况指标;不衡量物种或生物多样性。
经由以下途径到达
gibs.earthdata.nasa.gov,仅在您允许实时地图后访问

最新可用

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth

正在加载最新的NASA影像。

拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。

基础设施风险暴露,以德国为取景。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。

数据:NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap 贡献者 · Natural Earth · NASA EONET · 美国地质调查局 · NASA JPL OPERA DIST-ALERT来源与许可

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
  • VIIRS Black Marble 夜间灯光,NASA 戈达德航天中心;由 NASA Level-1 与大气档案和分发系统(LAADS DAAC)分发;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). 采用 CC BY 4.0 许可。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS 近实时产品(洪水、地表温度、积雪覆盖、校正反射率),NASA LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • MODIS 陆地产品(植被指数、总初级生产力、土地覆盖),NASA LP DAAC 和 LANCE;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • ASTER GDEM 是 METI 和 NASA 的产品(ASTER Global Digital Elevation Model V003,NASA LP DAAC);影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。引用格式:NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA 开放数据
  • 使用 Natural Earth 制作。免费矢量和栅格地图数据,见 naturalearthdata.com。 公有领域
  • © OpenStreetMap 贡献者(ODbL),经由 NASA GIBS(海岸线、边界、道路和地名)。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 ODbL
  • Blue Marble,NASA Earth Observatory;影像来自 NASA GIBS。颜色依据已发布的色标重绘;显示处的数值已按六边形网格平均(经修改)。 NASA 开放数据
  • 地球仪和平面地图上的背景信息:海岸线、边界、道路和地名来自 NASA GIBS 参考图层(OpenStreetMap 数据,ODbL,© OpenStreetMap contributors);Blue Marble 影像可作为可选底图;3D 地形和高程读数来自 ASTER GDEM 高程色彩指数(5 m 至 200 m 分级,为便于辨识而作了夸张处理)。边界按已发布的样式绘制,不代表对任何领土的立场。
  • 实时事件:NASA Earth Observatory Natural Event Tracker(EONET);事件仅供参考,并保留其原始来源链接。
  • 实时:NASA EONET。事件仅供参考,不是主管机构的预警。
  • 实时:美国地质调查局。事件仅供参考,不是主管机构的预警。
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • 河流流量预报,30天及区间(GloFAS,经Open-Meteo):包含经修改的Copernicus Emergency Management Service 2026年信息;非洪水警报。
  • 天气数据来自 Open-Meteo.com (https://open-meteo.com/), 依据 CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). 授权。
  • 可选图层(图层列表中有 12 个来源:实时、预报、观测和背景)开启时会在地图上和此处显示其提供方署名;预报是模型输出,派生指数是估计值。

图层与日期

  • 夜间灯光,每日:VIIRS Black Marble(VNP46A2),NASA LAADS DAAC · 2026年10月12日
  • 人口密度,2020 年:人口:哥伦比亚大学 CIESIN,世界网格化人口 v4.11(2018),NASA SEDAC, CC BY 4.0 · 静态
  • 洪水水体,3 日合成:VIIRS 全球洪水产品,NASA LANCE · 2026年10月14日
  • 真彩色:VIIRS NOAA-20 校正反射率,NASA LANCE · 2026年10月13日
  • 土地覆盖类型(IGBP),年度:MODIS Terra 和 Aqua 土地覆盖(MCD12Q1),NASA LP DAAC · 2024
  • 增强型植被指数,滚动 8 天:MODIS Terra EVI,NASA LANCE · 2026年10月13日

04跨领域

New materials and methods change supply and safety across domains.

05模拟器

冲击在投入产出经济中的传播。

一个部门的产出损失通过技术系数传导到其供应方和客户,并按你设定的速率恢复;这些系数是教学用值,不是国民账户。这是使用明示示例数值的教学模型,不是预测。本页地图显示的是德国;模型本身并不局限于某一地点。

控制措施

最先受冲击的部门(在列表中的位置)
0
冲击规模
其产出的 30%
冲击持续时间
30 days
恢复速率
每天 0.08
模拟天数
180 days

读数

运行期间损失的产出
0.65% of a year’s output
总量与直接量之比(乘数)
1.80 times
受影响最大的其他部门
服务
其峰值不可运行性
4.2%
数字、方法与来源
部门峰值不可运行性(%)产出权重(%)
农业30.2013.1
能源2.8025.4
制造业0.4711.2
交通与港口0.3720.1
贸易3.9018.4
服务4.1711.8

方法

  1. 投入产出分析 Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
  2. 不可运行性投入产出模型 Haimes and Jiang (2001), Journal of Infrastructure Systems 7
  3. 动态不可运行性与恢复 Lian and Haimes (2006), Systems Engineering 9
  4. 不确定性扇形图(参数蒙特卡罗) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  5. 单因素敏感性(龙卷风图) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

数据

The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:

  • 海港 Natural Earth
  • 海上咽喉要道 Nexus(按公布坐标标注的指定海峡和运河)
  • 铁路 Natural Earth
  • 主要道路 Natural Earth
冲击在投入产出经济中的传导。示意性教学模型:它依据控件设定的数值运行,而非实测数据。方法:Input-output analysis (Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press);Inoperability input-output model (Haimes and Jiang (2001), Journal of Infrastructure Systems 7);Dynamic inoperability and recovery (Lian and Haimes (2006), Systems Engineering 9)。
06指标

衡量什么,以及衡量得如何。

每个指标都注明其单位、频率、背后的来源类型以及数值将附带的证据标签。此处不显示数值:数值由计划依据其自身权限提供。

指标单位节奏来源类型标签
Manufacturing value addedshare of gross domestic product年度国民账户已发布统计
Additive manufacturing adoptionpercent of firmsper surveyBusiness surveys已报告
Defect rateparts per million每月Quality records观测
Process capabilitycapability indexper processStatistical process control观测
Materials R&D expenditurecurrency units年度R&D statistics已发布统计
Product recalls for manufacturing defects计数年度Regulator recall databases已发布统计
07孪生与级联模拟器

Model materials and manufacturing as a system. Run the cascade.

Assembled from the Nexus Standards area profile 工业与制造业: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

灾害

  • Natech event
  • 溃坝
  • 河流洪水 (在下游引发)
  • Flash flood (set off downstream)
  • 大规模流离失所(在下游引发)
  • Chemical spill or leak (set off downstream)
  • Emergency-response overload (set off downstream)
  • 大范围停电(在下游引发)
  • 供水短缺(在下游引发)
  • Toxic gas release (set off downstream)
  • Industrial fire (set off downstream)

控制措施

  • NS-0 章程与原则
  • NS-9 情境 UNI(部署、实例、计划实例)
  • NS-11 验证与监测(证据、证明、零信任符合性观测)
  • NS-12 软件、模型和 AI/ML 制品(供应链、模型卡、数据集说明)
  • NRS-H60 危害类别:供应链与流动中断(NHS-1 sys.supply-chain)
  • NRS-H50 危害类别:工业与过程事故(NHS-1 infra.industrial)
  • NRS-H109 危害类别:能源转型技术故障(NHS-1 tech.energy-transition)
  • NRS-X10 化学、工业、核与辐射安全
  • NRS-H54 危害类别:信号与平台中断(NHS-1 cyber.platform)
  • NRS-K14 领域包概况:制造业与工业(DOMAIN-014)

观测

  • eMARS Major Accident Reporting System (listed for reference)
  • World Development Indicators (listed for reference)
  • ILOSTAT (listed for reference)
  • Manufacturing value added as a proportion of GDP and per capita
  • CO2 emission per unit of value added
  • Manufacturing, value added (% of GDP)
  • Direct economic loss to all other damaged or destroyed productive assets attributed to disasters

示例地理范围

  • The Strait of Malacca: 227 hexagonal cells
  • 今夜夜间灯光与停电(VIIRS 昼夜波段),NASA GIBS
  • 穿透云层的地表水,30 m(OPERA DSWx-S1 雷达),NASA GIBS
  • 过去半小时降雨率(IMERG),NASA GIBS
  • 地表土壤湿度(SMAP),NASA GIBS
08来源

证据来自何处。

具名公共数据集与机构记录,各自注明许可类别。依协议获得的来源仅按其条款使用,绝不再次发布。

来源它提供什么许可类别
UNIDO industrial statisticsManufacturing value added and production by sectorPublic, UNIDO terms
OECD Main Science and Technology IndicatorsR&D spending by sectorPublic, OECD terms
NIST additive manufacturing resourcesMeasurement science and standards for additive processesPublic domain, US government
ISO/ASTM 52900 seriesTerminology and standards for additive manufacturingLicensed standards, purchase required
Regulator recall databasesRecalls by product and cause公共记录,条款因监管机构而异
09方法与证据

How materials and manufacturing is modelled, measured and tested.

模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。

系统模型

The couplings between the systems in materials and manufacturing: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−++产业工作贸易社区经济R 增强B 平衡
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR 指导原则 · GO FAIR 和 FORCE11W3C PROV · 万维网联盟关于一致处理不确定性的指南 · IPCCCEOS 分析就绪数据 · 地球观测卫星委员会
10决定

由谁决定,以及证据服务于什么。

Advanced Industry and Robotics prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.

谁来决定问题本页面服务的证据
ManufacturersWhich materials and processes to adopt and how to qualify themQualification reviews; quality data
Standards bodies and regulatorsWhat testing and certification to requireQuality and recall evidence
Industry ministriesWhere to support manufacturing capabilityValue added and R&D evidence

该主题产生的产出

  • Qualification pathway reviews for new materials and processes
  • Quality and recall trend analyses
  • Speciality input supply assessments
  • Evidence notes for manufacturing policy
11核心问题

专家提出的问题。

  1. 01

    How do new materials behave over time?

    Fatigue, ageing, fire behaviour and failure modes that differ from familiar materials.

  2. 02

    Is additive manufacturing reliable?

    How defects arise in printed parts and how quality is assured.

  3. 03

    What hazards do new materials pose?

    Exposure to fine particles, reactive substances and fumes during production and recycling.

  4. 04

    Where do materials come from and go?

    Supply of critical inputs and recovery at end of life.

12机制

What drives the risk.

Advanced materials often outperform traditional ones in strength, weight or conductivity, but their long-term behaviour is less well documented. Composites can fail without visible warning; some battery chemistries carry thermal runaway risk.

Additive manufacturing enables complex parts and distributed production. Its quality depends on process parameters, powder quality and post-processing, and internal defects may be hard to detect without specialised inspection.

Many advanced materials depend on concentrated supplies of critical minerals, exposing manufacturers to geopolitical and trade disruption.

Circularity is harder for complex materials. Composites, multi-material products and nanomaterials are difficult to separate and recycle, so design for recovery matters from the outset.

Digital production adds a further layer. Additive manufacturing relies on design files and process parameters that can be copied, altered or corrupted, so the integrity of digital inputs becomes part of product quality.

13方法与局限

证据如何收集,以及止于何处。

方法或数据显示内容其局限
Materials testingMechanical and fire performanceLaboratory conditions differ from service
Non-destructive inspectionInternal defects in partsDetection limits vary by method
Life-cycle assessmentEnvironmental burdens across stagesSensitive to boundaries and data
Supply-chain mappingSources of critical inputsOpaque beyond first-tier suppliers
14方法

如何研究,以及方法无法说明的内容。

15Where this page’s references

Where this page’s references lead.

阅读本页时所对照的机构和文件。状态和版本会变化;每个链接都指向发布机构。

16问题

问题与解答。

What is additive manufacturing?
Building parts layer by layer from digital designs, often called 3D printing, using polymers, metals or other materials.
Why does qualifying new materials take so long?
Because each use must show the material performs reliably under its conditions, through testing and certification by customers and regulators.
What is statistical process control?
Monitoring a production process with statistical methods to detect unusual variation before it causes defects in products.
Are printed parts as strong as conventional ones?
They can be, when process and inspection are well controlled. Performance depends heavily on parameters and post-processing.
Does the platform qualify materials?
No. It publishes research. Qualification is the work of manufacturers, standards bodies and regulators.
Why link materials with circularity?
Because design decisions about materials largely decide whether a product can be repaired, reused or recycled.
报告贡献

从本页贡献证据。

报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRI先进产业与机器人指数级技术全球部门风险与韧性
先进产业与机器人

带来一种方法、一个数据集或一个问题。

信息和咨询现已开放。每项咨询都会获得一个编号,并告知下一步;申请、付款、算力分配和注册只有在相应团队、条款和审查能力就绪时才会开放。