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市场调查报告书
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1363526

供应链数位孪生市场规模、份额、趋势分析报告：按组件、按部署模式、按公司规模、按行业、按地区、细分市场趋势，2023-2030 年

Supply Chain Digital Twin Market Size, Share & Trends Analysis Report By Component, By Deployment Mode (On-premise, Cloud), By Enterprise Size, By Industry Vertical, By Region, And Segment Forecasts, 2023 - 2030
出版日期: | 出版商: Grand View Research | 英文 110 Pages | 商品交期: 2-10个工作天内

价格

供应链数位孪生市场成长与趋势：

Grand View Research, Inc.最新报告显示，到2030年，全球供应链数位孪生市场规模预计将达到59.8亿美元，2023年至2030年年复合成长率为12.0%。

数位孪生的采用是由行业的快速成长和对最尖端科技的需求所推动的。该技术透过提供整个供应链的完整即时影像，实现更好的监控、分析和营运最佳化。

数位孪生是创建整个供应链或其中特定组件的数位副本。该副本包括实体资产，例如製造设施、储存设施、运输车辆、流程、资料流以及不同结构要素之间的关係。此外，数位孪生还包含物联网设备、感测器和其他资料来源。这些设备在供应链的各个点即时收集温度、湿度、位置和生产参数。该资讯被输入数位孪生以实现动态和准确的模拟。

意外停工给工业製造商造成了严重的干扰和财务负担，甚至在疫情爆发之前，每週损失的时间就超过 15 个小时，年度损失的损失超过 500 亿美元。这些中断的很大一部分（大约一半）是由于设备故障造成的。为了应对这些挑战，一种称为预测性维护的策略已成为一种引人注目的方法，该策略可以预测故障并抢先修復故障。实施数位孪生有望显着节省成本并提高生产力，使製造商和物流提供者受益。

数位孪生可以即时洞察实体物件的状况，是预测性维护的完美解决方案。例如，2022 年，卡夫亨氏与微软合作，为北美所有 34 个製造厂开发数位位孪生。其主要目标之一是减少每个站点的机械停机时间。

除了综合仓库之外，数位孪生还可以有效部署到较小的个别资产。先进的物流公司和设备服务提供者正在创建机器人、卡车、工具等的数位复製品。这种模拟方法可以持续监控其状况并识别需要及时关注以避免故障的磨损。采用数位孪生来促进预测性维护为物流提供者带来了显着的好处。这不仅提高了营运吞吐量，还显着降低了营运支出。

供应链数位孪生市场报告亮点

  • 按组成部分来看，硬体细分市场在整个市场中占据主导地位，2022 年市场占有率为 42.0%。该细分市场预计将由现实世界资料的收集、传输和处理来驱动，以产生准确和动态的虚拟表示。
  • 按部署型态，本地部署模型主导了整个市场，2022 年市场占有率为 52.1%。本地部署使公司能够完全控制资料，并能够实施安全措施来保护敏感的供应链资讯。
  • 根据公司规模，预计2023年至2030年大型企业细分市场的年复合成长率将超过12.5%。大型企业可以使用供应链数位孪生来提高整个供应链的业务效率、降低成本并改善决策。
  • 按行业划分，在即时需求波动、生产计画和考虑到销售线索的存量基准最佳化的推动下，汽车领域预计将在预测期内实现强劲增长，年复合成长率接近 13.3%。
  • 北美在该行业占据主导地位，2022 年占全球销售额的 29.3% 以上。该地区拥有许多领先的科技公司、研究机构和大学，它们正在积极开发和推进供应链数位孪生技术。

目录

第1章调查方法和范围

第2章执行摘要

第3章市场变数、趋势与范围预测

  • 市场体系预测
  • 供应链数位孪生市场-价值链分析
  • 供应链数位孪生市场动态
  • 产业分析-波特五力分析
  • 产业分析-PESTEL分析
  • COVID-19感染疾病的影响分析

第4章供应链数位孪生市场、组件预测

  • 供应链数位孪生市场，按成分分析和市场占有率，2022 年和 2030 年
  • 硬体
  • 软体
  • 服务

第5章供应链数位市场、部署模式预测

  • 供应链数位位孪生市场，按部署模式分析和市场占有率，2022 年和 2030 年
  • 本地
  • 云

第6章供应链数位孪生市场、企业规模预测

  • 供应链数位位孪生市场，按公司规模分析和市场占有率，2022 年和 2030 年
  • 大公司
  • 中小企业

第7章供应链数位孪生市场、产业预测

  • 2022 年和 2030 年供应链数位孪生市场、产业分析和市场占有率
  • 製造业
  • 汽车
  • 航太和国防
  • 零售
  • 药品
  • 消费品
  • 其他的

第8章供应链数位孪生市场：依地区估算及趋势分析

  • 2022 年及 2030 年供应链数位孪生市场占有率（按地区）
  • 北美洲
    • 按组成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司规模划分，2017-2030
    • 按行业划分，2017-2030
    • 美国
    • 加拿大
  • 欧洲
    • 按组成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司规模划分，2017-2030
    • 按行业划分，2017-2030
    • 德国
    • 英国
    • 法国
  • 亚太地区
    • 按组成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司规模划分，2017-2030
    • 按行业划分，2017-2030
    • 中国
    • 日本
    • 印度
  • 拉丁美洲
    • 按组成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司规模划分，2017-2030
    • 按行业划分，2017-2030
    • 巴西
    • 墨西哥
  • 中东和非洲
    • 按组成部分，2017-2030
    • 依部署模式，2017-2030
    • 按公司规模划分，2017-2030
    • 按行业划分，2017-2030
    • 阿拉伯联合大公国 (UAE)
    • 沙乌地阿拉伯王国 (KSA)
    • 南非

第9章供应链数位孪生市场竞争形势

  • 主要市场参与企业
    • IBM
    • Oracle
    • SAP
    • Dassault Systemes
    • AVEVA
    • Siemens Digital Industries Software
    • Kinaxis
    • The AnyLogic Company
    • Simio
    • Logivations
  • 2022年主要企业市场占有率分析
  • 2022 年公司分类/定位分析
  • 策略规划
    • 扩张
    • 併购
    • 伙伴关係与协作
    • 产品/服务发布
    • 其他的
Product Code: GVR-4-68040-128-5

Supply Chain Digital Twin Market Growth & Trends:

The global supply chain digital twin market size is expected to reach USD 5.98 billion by 2030, registering a CAGR of 12.0% from 2023 to 2030, according to a new report by Grand View Research, Inc.. Digital twin adoption has been fueled by the industry's rapid growth and the demand for cutting-edge technology. This technology enables better monitoring, analysis, and operation optimization by providing a complete and real-time picture of the whole supply chain.

A digital twin is the creation of a digital replica of the complete supply chain or certain components within it. This replica contains physical assets such as manufacturing facilities, storage facilities, transportation vehicles, processes, data flows, and relationships between different pieces. Furthermore, the digital twin incorporates IoT devices, sensors, and other data sources. Temperature, humidity, location, and production parameters are all collected in real time by these devices at various points in the supply chain. This information is then input into the digital twin, which allows for a dynamic and accurate simulation.

Unforeseen operational halts pose significant disruptions and financial burdens for industrial manufacturers, amounting to more than 15 hours of lost time per week and exceeding USD 50 billion annually, even before the pandemic. A substantial portion of these interruptions, nearly half, stem from equipment malfunctions. To counteract these challenges, the strategy of predictive maintenance, involving the anticipation and preemptive repair of assets before they malfunction, has emerged as a compelling approach. Its implementation promises substantial cost reductions and heightened productivity, benefiting both manufacturers and logistics providers.

The potency of digital twins in furnishing real-time insights into the status of physical objects positions them as an optimal solution for predictive maintenance. For instance, in 2022, Kraft Heinz joined forces with Microsoft to develop digital twins for all 34 manufacturing facilities in North America. Among the primary aims was the curtailment of mechanical downtime across each establishment.

Beyond just comprehensive warehouses, digital twins can also be effectively deployed for individual assets, even on a smaller scale. Forward-thinking logistics entities and equipment service providers are crafting digital replicas of items such as singular robots, trucks, and tools. This emulation approach enables consistent monitoring of their conditions, identifying wear and tear that necessitates timely attention to avert breakdowns. Employing digital twins to facilitate predictive maintenance yields substantial benefits for logistics providers, including the potential to diminish reactive maintenance by around 40% within a given year. This not only amplifies operational throughput but also substantially reduces operational expenditure.

Supply Chain Digital Twin Market Report Highlights:

  • Based on component, the hardware segment dominated the overall market, accounting for a market share of 42.0% in 2022. The segment is expected to be driven by the gathering, transfer, and processing of real-world data to produce accurate and dynamic virtual representations
  • Based on deployment mode, the on-premise segment dominated the overall market, accounting for a market share of 52.1% in 2022. With on-premises implementation, the firm keeps full control of its data and can install its security measures to protect sensitive supply chain information
  • Based on enterprise size, the large enterprises segment is anticipated to grow at a CAGR of over 12.5% from 2023 to 2030. Large corporations can use supply chain digital twins to improve operational efficiency, lower costs, and improve decision-making across the whole supply chain
  • Based on industrial vertical, the automotive segment is anticipated to witness strong growth with a CAGR of nearly 13.3% over the forecast period, owing to the optimization of inventory levels by taking into account real-time demand variations, production plans, and lead
  • North America dominated the industry, contributing to over 29.3% of the global revenue in 2022. The region is home to many leading technology companies, research institutions, and universities that have been actively developing and advancing digital twin technology for supply chain

Table of Contents

Chapter 1. Methodology and Scope

  • 1.1. Market Segmentation & Scope
  • 1.2. Market Definitions
  • 1.3. Information Procurement
    • 1.3.1. Information analysis
    • 1.3.2. Market formulation & data visualization
    • 1.3.3. Data validation & publishing
  • 1.4. Research Scope and Assumptions
    • 1.4.1. List of Data Sources

Chapter 2. Executive Summary

  • 2.1. Market Summary
  • 2.2. Market Snapshot
  • 2.3. Segment Snapshot
  • 2.4. Competitive Landscape Snapshot

Chapter 3. Market Variables, Trends, & Scope Outlook

  • 3.1. Market Lineage Outlook
  • 3.2. Supply Chain Digital Twin Market - Value Chain Analysis
  • 3.3. Supply Chain Digital Twin Market Dynamics
    • 3.3.1. Market Driver Analysis
    • 3.3.2. Market Restraint Analysis
    • 3.3.3. Market Opportunity Analysis
  • 3.4. Industry Analysis - Porter's Five Forces Analysis
    • 3.4.1. Supplier power
    • 3.4.2. Buyer power
    • 3.4.3. Substitution threat
    • 3.4.4. Threat from new entrant
    • 3.4.5. Competitive rivalry
  • 3.5. Industry Analysis - PESTEL Analysis
    • 3.5.1. Political landscape
    • 3.5.2. Economic landscape
    • 3.5.3. Social landscape
    • 3.5.4. Technology landscape
    • 3.5.5. Environmental landscape
    • 3.5.6. Legal landscape
  • 3.6. COVID-19 Impact Analysis

Chapter 4. Supply Chain Digital Twin Market Component Outlook

  • 4.1. Supply Chain Digital Twin market, By Component Analysis & Market Share, 2022 & 2030
  • 4.2. Hardware
    • 4.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 4.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 4.3. Software
    • 4.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 4.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 4.4. Services
    • 4.4.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 4.4.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 5. Supply Chain Digital Twin Market Deployment Mode Outlook

  • 5.1. Supply Chain Digital Twin market, By Deployment Mode Analysis & Market Share, 2022 & 2030
  • 5.2. On-premise
    • 5.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 5.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 5.3. Cloud
    • 5.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 5.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 6. Supply Chain Digital Twin Market Enterprise Size Outlook

  • 6.1. Supply Chain Digital Twin market, By Enterprise Size Analysis & Market Share, 2022 & 2030
  • 6.2. Large Enterprise
    • 6.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 6.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 6.3. Small and medium enterprises
    • 6.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 6.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 7. Supply Chain Digital Twin Market Industry Vertical Outlook

  • 7.1. Supply Chain Digital Twin market, By Industry Vertical Analysis & Market Share, 2022 & 2030
  • 7.2. Manufacturing
    • 7.2.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.2.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.3. Automotive
    • 7.3.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.3.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.4. Aerospace & Defense
    • 7.4.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.4.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.5. Retail
    • 7.5.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.5.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.6. Pharmaceuticals
    • 7.6.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.6.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.7. Consumer Goods
    • 7.7.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.7.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)
  • 7.8. Others
    • 7.8.1. Market estimates and forecasts, 2017 - 2030 (USD Million)
    • 7.8.2. Market estimates and forecasts, By Region, 2017 - 2030 (USD Million)

Chapter 8. Supply Chain Digital Twin market: Regional Estimates & Trend Analysis

  • 8.1. Supply Chain Digital Twin Market Share by Region, 2022 & 2030
  • 8.2. North America
    • 8.2.1. Market estimates and forecasts, 2017 - 2030
    • 8.2.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.2.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.2.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.2.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.2.6. U.S.
      • 8.2.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.2.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.2.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.2.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.2.7. Canada
      • 8.2.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.2.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.2.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.2.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.3. Europe
    • 8.3.1. Market estimates and forecasts, 2017 - 2030
    • 8.3.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.3.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.3.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.3.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.3.6. Germany
      • 8.3.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.3.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.3.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.3.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.3.7. UK
      • 8.3.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.3.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.3.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.3.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.3.8. France
      • 8.3.8.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.3.8.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.3.8.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.3.8.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.4. Asia-Pacific
    • 8.4.1. Market estimates and forecasts, 2017 - 2030
    • 8.4.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.4.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.4.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.4.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.4.6. China
      • 8.4.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.4.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.4.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.4.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.4.7. Japan
      • 8.4.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.4.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.4.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.4.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.4.8. India
      • 8.4.8.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.4.8.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.4.8.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.4.8.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.5. Latin America
    • 8.5.1. Market estimates and forecasts, 2017 - 2030
    • 8.5.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.5.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.5.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.5.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.5.6. Brazil
      • 8.5.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.5.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.5.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.5.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.5.7. Mexico
      • 8.5.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.5.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.5.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.5.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
  • 8.6. Middle East & Africa
    • 8.6.1. Market estimates and forecasts, 2017 - 2030
    • 8.6.2. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
    • 8.6.3. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
    • 8.6.4. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
    • 8.6.5. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.6.6. United Arab Emirates (UAE)
      • 8.6.6.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.6.6.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.6.6.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.6.6.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.6.7. Kingdom of Saudi Arabia(KSA)
      • 8.6.7.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.6.7.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.6.7.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.6.7.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)
    • 8.6.8. South Africa
      • 8.6.8.1. Market estimates and forecasts, By Component, 2017 - 2030 (USD Million)
      • 8.6.8.2. Market estimates and forecasts, By Deployment Mode, 2017 - 2030 (USD Million)
      • 8.6.8.3. Market estimates and forecasts, By Enterprise Size, 2017 - 2030 (USD Million)
      • 8.6.8.4. Market estimates and forecasts, By Industry Vertical, 2017 - 2030 (USD Million)

Chapter 9. Supply Chain Digital Twin Market Competitive Landscape

  • 9.1. Key Market Participants
    • 9.1.1. IBM
    • 9.1.2. Oracle
    • 9.1.3. SAP
    • 9.1.4. Dassault Systemes
    • 9.1.5. AVEVA
    • 9.1.6. Siemens Digital Industries Software
    • 9.1.7. Kinaxis
    • 9.1.8. The AnyLogic Company
    • 9.1.9. Simio
    • 9.1.10. Logivations
  • 9.2. Key Company Market Share Analysis, 2022
  • 9.3. Company Categorization/Position Analysis, 2022
  • 9.4. Strategic Mapping
    • 9.4.1. Expansion
    • 9.4.2. Mergers & Acquisition
    • 9.4.3. Partnership & Collaborations
    • 9.4.4. Product/service launch
    • 9.4.5. Others 

List of Tables

  • Table 1 Supply Chain Digital Twin market, by component, 2017 - 2030 (USD Million)
  • Table 2 Supply Chain Digital Twin market, by deployment mode, 2017 - 2030 (USD Million)
  • Table 3 Supply Chain Digital Twin market, by enterprise size, 2017 - 2030 (USD Million)
  • Table 4 Supply Chain Digital Twin market, by industry vertical, 2017 - 2030 (USD Million)
  • Table 5 Participant's Overview
  • Table 6 Financial Performance
  • Table 7 Product benchmarking
  • Table 8 Company Heat Map Analysis
  • Table 9 Key Companies undergoing expansions.
  • Table 10 Key Companies involved in M&As
  • Table 11 Key Companies undergoing partnerships & collaborations.

List of Figures

  • Fig. 1 Supply Chain Digital Twin Market Segmentation
  • Fig. 2 Supply Chain Digital Twin Market - Regional Scope
  • Fig. 3 Information Procurement
  • Fig. 4 Data Analysis Models
  • Fig. 5 Market Formulation and Validation
  • Fig. 6 Data Validating & Publishing
  • Fig. 7 Supply Chain Digital Twin Market Snapshot, 2022 & 2030
  • Fig. 8 Supply Chain Digital Twin Market -Segment Snapshot, by Enterprise Size & Industry Vertical, 2022 & 2030
  • Fig. 9 Supply Chain Digital Twin Market - Competitive Landscape Snapshot
  • Fig. 10 Supply Chain Digital Twin Market Value, 2022 (USD Billion)
  • Fig. 11 Value chain analysis
  • Fig. 12 Supply Chain Digital Twin Market Trends
  • Fig. 13 Supply Chain Digital Twin market - Porter's five forces analysis
  • Fig. 14 Supply Chain Digital Twin market - PESTEL analysis
  • Fig. 15 Supply Chain Digital Twin Market, by Component: Key Takeaways
  • Fig. 16 Supply Chain Digital Twin Market, by Component: Market Share, 2022 & 2030
  • Fig. 17 Supply Chain Digital Twin Market Estimates and Forecasts, by Hardware, 2017 - 2030 (USD Million)
  • Fig. 18 Supply Chain Digital Twin Market Estimates and Forecasts, by Software, 2017 - 2030 (USD Million)
  • Fig. 19 Supply Chain Digital Twin Market Estimates and Forecasts, by Services, 2017 - 2030 (USD Million)
  • Fig. 20 Supply Chain Digital Twin Market, by Deployment Mode: Key Takeaways
  • Fig. 21 Supply Chain Digital Twin Market, by Deployment Mode: Market Share, 2022 & 2030
  • Fig. 22 Supply Chain Digital Twin Market Estimates and Forecasts, by On-premise, 2017 - 2030 (USD Million)
  • Fig. 23 Supply Chain Digital Twin Market Estimates and Forecasts, by Cloud, 2017 - 2030 (USD Million)
  • Fig. 24 Supply Chain Digital Twin Market, by Enterprise Size: Key Takeaways
  • Fig. 25 Supply Chain Digital Twin Market, by Enterprise Size: Market Share, 2022 & 2030
  • Fig. 26 Supply Chain Digital Twin Market Estimates and Forecasts, by Large Enterprises, 2017 - 2030 (USD Million)
  • Fig. 27 Supply Chain Digital Twin Market Estimates and Forecasts, by Small and medium enterprises, 2017 - 2030 (USD Million)
  • Fig. 28 Supply Chain Digital Twin Market, by Industry Vertical: Key Takeaways
  • Fig. 29 Supply Chain Digital Twin Market, by Industry Vertical: Market Share, 2022 & 2030
  • Fig. 30 Supply Chain Digital Twin Market Estimates and Forecasts, By Manufacturing, 2017 - 2030 (USD Million)
  • Fig. 31 Supply Chain Digital Twin Market Estimates and Forecasts, by Automotive, 2017 - 2030 (USD Million)
  • Fig. 32 Supply Chain Digital Twin Market Estimates and Forecasts, by Aerospace & Defense, 2017 - 2030 (USD Million)
  • Fig. 33 Supply Chain Digital Twin Market Estimates and Forecasts, by Retail, 2017 - 2030 (USD Million)
  • Fig. 34 Supply Chain Digital Twin Market Estimates and Forecasts, By Pharmaceuticals, 2017 - 2030 (USD Million)
  • Fig. 35 Supply Chain Digital Twin Market Estimates and Forecasts, by Consumer Goods, 2017 - 2030 (USD Million)
  • Fig. 36 Supply Chain Digital Twin Market Estimates and Forecasts, by Others, 2017 - 2030 (USD Million)
  • Fig. 37 Supply Chain Digital Twin Market revenue- by region, 2022 & 2030 (USD Million)
  • Fig. 38 Regional Marketplace (North America & Europe)- Key Takeaways
  • Fig. 39 Regional Marketplace (Asia Pacific and Latin America) - Key Takeaways
  • Fig. 40 Regional Marketplace (MEA)- Key Takeaways
  • Fig. 41 North America Supply Chain Digital Twin Market estimates & forecast, 2017 - 2030 (USD Million)
  • Fig. 42 U.S. Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 43 Canada Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 44 Europe Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 45 UK Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 46 Germany Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 47 France Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 48 Asia Pacific Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 49 China Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 50 India Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 51 Japan Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 52 Latin America Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 53 Brazil Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 54 Mexico Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 55 Middle East & Africa (MEA) Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 56 United Arab Emirates (UAE) Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 57 Kingdom of Saudi Arabia (KSA) Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 58 South Africa Supply Chain Digital Twin Market Estimates & Forecast, 2017 - 2030 (USD Million)
  • Fig. 59 Key Company Categorization
  • Fig. 60 Company Market Share Analysis, 2022
  • Fig. 61 Strategic framework