数位孪生市场:2023-2027
市场调查报告书
商品编码
1226986

数位孪生市场: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个工作天内

价格
简介目录

本报告调查了数位孪生市场,总结了数位孪生技术的定义和概述、标准化工作、市场规模和前景、竞争格局、促进采用的因素、案例研究以及主要趋势和发展。我来了。

涵盖公司

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

内容

第 1 章执行摘要

第二章介绍

第 3 章技术概述

  • 了解数位孪生架构的关键概念
  • 用于创建和操作数位孪生的关键技术组件
  • 数位孪生参考架构简介
  • 创建数位孪生模型
  • 数位孪生的技术实现

第四章主要机构及标准化工作

  • 概览:主要机构
  • Dive Dive 1:资产管理外壳 (AAS)
  • Dive Dive 2:数位孪生联盟 (DTC)
  • 深入探讨 3:采用 AAS 和 DTC

第五章市场规模与前景

  • 简介:IoT Analytics 考虑的数位孪生软件市场是什么?
  • 查看数位孪生市场:广义和狭义定义
  • 各种宏观因素对数位孪生市场的预期影响
  • 全球数位孪生市场的规模
  • 製造数位孪生市场:离散混合过程
  • 全球数位孪生市场:按地区和国家分布

第六章竞争格局

  • 竞争格局:我从 110 多家供应商的观察中学到的东西
  • 通过在财报电话会议中提及来衡量数位孪生的战略重点
  • 用于创建和操作数位孪生的关键技术组件
  • 数位孪生生态系统
  • 数位孪生供应商简介
  • 数位孪生平台价格

第七章数位孪生项目及热点现状

  • 基于 100 个近期数位孪生项目的分析
  • 数位孪生项目的现状:基于频率的热点
  • AR 软件采购途径
  • 最终用户意见

第 8 章案例研究

第 9 章最终用户洞察

  • 最终用户洞察:3 项研究概览
  • 最终用户通常使用数位孪生做什么
  • 实施不同的工业 4.0 战略:按资产类型
  • 采用智能製造:用例
  • 工厂数位孪生模型的部署:按地区和行业
  • 未来三年的智能製造投资计划:用例
  • 在工厂中实施数位孪生的主要挑战:集成、时间和復杂性
  • 与数位孪生软件相关的支出模式
  • 数位孪生世界调查报告

第十章趋势与发展

第11章投资/併购活动

  • 数位孪生公司资金
  • 近期与数位孪生相关的主要收购

第 12 章研究方法和市场定义

第 13 章关于物联网分析

简介目录

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