數位孿生市場:2023-2027
市場調查報告書
商品編碼
1226986

數位孿生市場:2023-2027

Digital Twin Market Report 2023-2027

出版日期: | 出版商: IoT Analytics GmbH | 英文 233 Pages | 商品交期: 最快1-2個工作天內

價格
簡介目錄

本報告調查了數位孿生市場,總結了數位孿生技術的定義和概述、標準化工作、市場規模和前景、競爭格局、促進採用的因素、案例研究以及主要趨勢和發展。我來了。

涵蓋公司

  • ABB
  • AWS
  • Alibaba Cloud
  • Ansys
  • Autodesk
  • Bentley
  • Bosch
  • Dassault Systemes
  • Emerson
  • GE
  • Google
  • IBM
  • Microsoft
  • Oracle
  • PTC
  • Rockwell Automation
  • Schneider Electric
  • Siemens

內容

第 1 章執行摘要

第二章介紹

第 3 章技術概述

  • 了解數位孿生架構的關鍵概念
  • 用於創建和操作數位孿生的關鍵技術組件
  • 數位孿生參考架構簡介
  • 創建數位孿生模型
  • 數位孿生的技術實現

第四章主要機構及標準化工作

  • 概覽:主要機構
  • Dive Dive 1:資產管理外殼 (AAS)
  • Dive Dive 2:數位孿生聯盟 (DTC)
  • 深入探討 3:採用 AAS 和 DTC

第五章市場規模與前景

  • 簡介:IoT Analytics 考慮的數位孿生軟件市場是什麼?
  • 查看數位孿生市場:廣義和狹義定義
  • 各種宏觀因素對數位孿生市場的預期影響
  • 全球數位孿生市場的規模
  • 製造數位孿生市場:離散混合過程
  • 全球數位孿生市場:按地區和國家分佈

第六章競爭格局

  • 競爭格局:我從 110 多家供應商的觀察中學到的東西
  • 通過在財報電話會議中提及來衡量數位孿生的戰略重點
  • 用於創建和操作數位孿生的關鍵技術組件
  • 數位孿生生態系統
  • 數位孿生供應商簡介
  • 數位孿生平台價格

第七章數位孿生項目及熱點現狀

  • 基於 100 個近期數位孿生項目的分析
  • 數位孿生項目的現狀:基於頻率的熱點
  • AR 軟件採購途徑
  • 最終用戶意見

第 8 章案例研究

第 9 章最終用戶洞察

  • 最終用戶洞察:3 項研究概覽
  • 最終用戶通常使用數位孿生做什麼
  • 實施不同的工業 4.0 戰略:按資產類型
  • 採用智能製造:用例
  • 工廠數位孿生模型的部署:按地區和行業
  • 未來三年的智能製造投資計劃:用例
  • 在工廠中實施數位孿生的主要挑戰:集成、時間和復雜性
  • 與數位孿生軟件相關的支出模式
  • 數位孿生世界調查報告

第十章趨勢與發展

第11章投資/併購活動

  • 數位孿生公司資金
  • 近期與數位孿生相關的主要收購

第 12 章研究方法和市場定義

第 13 章關於物聯網分析

簡介目錄

A 233-page report detailing the market for digital twins, including definition & disambiguation, standardization efforts, market size & outlook, competitive landscape, market hotspots, case studies, trends & developments.

The ‘Digital Twin Market Report 2023-2027’ is part of IoT Analytics' ongoing coverage of IoT software and platforms. The information presented in this report is based on the results of multiple surveys, secondary research, and qualitative research, i.e., interviews with 20+ digital twin experts such as vendors and end users between April 2022 and December 2022. The document includes definitions for digital twins, market projections, adoption drivers, competitive landscapes, key trends and developments, and case studies.

Questions answered:

  • What are digital twins (i.e., a digital twin definition)?
  • Which capabilities are used for digital twins (including a deep dive into reference architectures)?
  • Who are the leading digital twin vendors?
  • What are the most common use cases of digital twins today?
  • What are some notable digital twin case studies?
  • How much is being spent on digital twin software by regions and industries?
  • What is the share of companies that have deployed digital twins? How many are planning to invest in it?
  • Who is adopting digital twins?
  • How much is being invested into digital twin-related start-ups?
  • What are some of the main trends and challenges in the digital twin space?

Companies mentioned:

A selection of companies mentioned in the report.

  • ABB
  • AWS
  • Alibaba Cloud
  • Ansys
  • Autodesk
  • Bentley
  • Bosch
  • Dassault Systemes
  • Emerson
  • GE
  • Google
  • IBM
  • Microsoft
  • Oracle
  • PTC
  • Rockwell Automation
  • Schneider Electric
  • Siemens

Table of Contents

1. Executive Summary

2. Introduction

  • 2.1. Evolution of digital twins
  • 2.2. Definition of a digital twin
  • 2.3. Interest in digital twins
  • 2.4. Digital thread
  • 2.5. Digital twin implementation example

3. Technology Overview

  • 3.1. Key concepts for understanding digital twin architectures
  • 3.2. Key technological components to create and work with digital twins
  • 3.3. Introducing digital twin reference architectures
  • 3.4. Creating digital twin models
  • 3.5. Technical realization of a digital twin

4. Key authorities and standardization efforts

  • 4.1. Overview: Key authorities
  • 4.2. Deep-dive 1: Asset Administration Shell (AAS)
  • 4.3. Deep-dive 2: Digital Twin Consortium (DTC)
  • 4.4. Deep-dive 3: Adoption of AAS and DTC standard

5. Market size & outlook

  • 5.1. Primer: What IoT Analytics considers as the market for digital twin software
  • 5.2. Ways to look at the digital twin market : broad and narrow definitions
  • 5.3. Expected effect of different macro factors on the digital twin market (2022 - 2027)
  • 5.4. Global digital twin market size
  • 5.5. Manufacturing digital twin market - Discrete, hybrid, process
  • 5.6. Global digital twin market - Regional and country specific distribution

6. Competitive landscape

  • 6.1. Competitive Landscape: What We Learned from Looking at 110+ Vendors
  • 6.2. Strategic Focus on Digital Twin as Measured by Mentions in Earnings Calls
  • 6.3. Key Technological Components to Create and Work with Digital Twins
  • 6.4. Digital Twin Ecosystem
  • 6.5. Digital Twin Vendor Profiles
  • 6.6. Pricing of Digital Twin Platforms

7. Current state of digital twin projects and market hotspots

  • 7.1. Analysis based on 100 recent digital twin projects
  • 7.2. Current state of digital twin projects: hotspots based on frequency
  • 7.3. Procurement channels for AR software
  • 7.4. End-user opinions

8. Case studies

9. End-user insights

  • 9.1. End-User Insights-Overview of the Three Surveys
  • 9.2. What End Users Typically Do with Digital Twins
  • 9.3. Implementation of Different Industry 4.0 Strategies - Based on type of asset
  • 9.4. Adoption of Smart Manufacturing Use Cases
  • 9.5. Deployment of Factory Digital Twins by Region and Industry
  • 9.6. Planned Investment in Smart Manufacturing Use Cases in the Next Three Years
  • 9.7. Main Challenges When Adopting Digital Twins in a Factory: Integration, Time, and Complexity
  • 9.8. Spending Patterns Related to Digital Twin Software
  • 9.9. Digital Twin Global Survey Report

10. Trends and developments

11. Investments and M&A activity

  • 11.1. Funding of digital twin companies between 2015 and 2022
  • 11.2. Notable recent acquisitions related to digital twin

12. Methodology and market definitions

13. About IoT Analytics