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市场调查报告书

商品编码

1544813

工业机械市场人工智慧、机会、成长动力、产业趋势分析与预测，2024-2032

AI in Industrial Machinery Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

出版日期: 2024年07月01日 | 出版商:

Global Market Insights Inc. | 英文 487 Pages | 商品交期: 2-3个工作天内

价格

简介目录

由于製造流程中营运效率和生产力提高的需求，预计 2024 年至 2032 年间，工业机械市场规模中的人工智慧复合年增长率将达到 27.2%。透过利用机器学习 (ML) 和预测分析等技术，人工智慧使机械能够进行即时资料分析、优化生产计划并预测设备故障。这种预测性维护不仅可以减少停机时间，还可以减少维护费用。此外，人工智慧驱动的自动化提高了製造的精度和速度。例如，2024 年 5 月，Composable 推出了无程式码 UI 平台，使工程师能够透过将操作员专业知识整合到现实场景中来直接训练 AI 代理程式。

智慧製造的兴起和工业4.0的推动将进一步推动市场成长。随着企业倾向于互联和自动化生产环境，人工智慧在促进机器、感测器和控制系统之间的无缝互动方面发挥关键作用。这种增强的连接性不仅可以实现即时监控，还可以在製造过程中做出灵活的决策。

整个产业分为组件、技术、应用、最终用途和区域。

基于技术，由于人工智慧在先进视觉分析和品质控制方面的作用，电脑版领域的人工智慧在工业机械市场规模预计将在 2024 年至 2032 年期间显着增长。当与人工智慧整合时，电脑视觉技术使机器能够准确地解释和分析来自感测器和摄影机的视觉资料。这种精度支援缺陷检测、品质保证和自动化检查，确保高生产标准并最大限度地减少浪费。

人工智慧在品质控制应用领域的工业机械市场资料将在 2032 年扩大。它们快速、准确地处理大量资料的能力超过了人类检查员，从而减少了错误和浪费。

亚太地区工业机械产业的人工智慧预计将在 2024 年至 2032 年期间大幅成长。这种激增是由快速工业化和技术进步所推动的。随着中国、印度和日本等製造业强国的能力不断增强，对人工智慧技术推动工业流程效率和创新的需求不断增加。

产业生态系统分析
- 影响价值链的因素
- 利润率分析
- 干扰
- 未来展望
- 製造商
- 经销商
供应商格局
利润率分析
技术概览
监管环境
衝击力
- 成长动力
  - 製造业越来越多地采用铝
  - 与物联网和云端运算集成
  - 高阶分析与决策
- 产业陷阱与挑战
  - 实施成本高
  - 技能差距与劳动适应
成长潜力分析
波特的分析
PESTEL分析

第 4 章：竞争格局

介绍
公司市占率分析
竞争定位矩阵
战略展望矩阵

第 5 章：市场估计与预测：按组成部分，2021-2032 年

主要趋势
硬体
软体
服务

第 6 章：市场估计与预测：按技术划分，2021-2032）

主要趋势
机器学习
电脑视觉
情境意识
自然语言处理

第 7 章：市场估计与预测：按应用划分，2021-2032 年

主要趋势
预测性维护
品质管制
流程优化
供应链优化
智慧机器人
自动驾驶车辆和导引系统
能源管理
人机介面
其他的

第 8 章：市场估计与预测：依最终用途，2021-2032 年

主要趋势
农业
建造
包装
食品加工
矿业
半导体

第 9 章：市场估计与预测：按地区，2021-2032 年

主要趋势
北美洲
- 我们
- 加拿大
欧洲
- 英国
- 德国
- 法国
- 义大利
- 西班牙
- 俄罗斯
- 欧洲其他地区
亚太地区
- 中国
- 印度
- 日本
- 韩国
- 澳洲
- 亚太地区其他地区
拉丁美洲
- 巴西
- 墨西哥
- 拉丁美洲其他地区
MEA
- 南非
- 沙乌地阿拉伯
- 阿联酋
- MEA 的其余部分

第 10 章：公司简介

ABB Ltd.
Amazon Web Services (AWS)
Cisco Systems, Inc.
FANUC Corporation
Google LLC
Hitachi, Ltd.
Honeywell International Inc.
IBM Corporation
Intel Corporation
Microsoft Corporation
NVIDIA Corporation
Qualcomm Technologies
Rockwell Automation, Inc.
Schneider Electric SE
Siemens AG

简介目录

Product Code: 5774

AI in industrial machinery market size is anticipated to witness a 27.2% CAGR between 2024 and 2032 driven by the need for increased operational efficiency and productivity in manufacturing processes. By leveraging technologies like machine learning (ML) and predictive analytics, AI empowers machinery to conduct real-time data analyses, optimize production schedules, and foresee equipment failures. Such predictive maintenance not only curtails downtime but also trims maintenance expenses. Furthermore, AI-driven automation amplifies both precision and speed in manufacturing. For example, in May 2024, Composable unveiled a No-Code UI platform, enabling engineers to train AI agents directly by integrating operator expertise into real-world scenarios.

The ascent of smart manufacturing and the push towards Industry 4.0 is set to further propel the market growth. As enterprises gravitate towards interconnected and automated production landscapes, AI plays a pivotal role in fostering seamless interactions among machines, sensors, and control systems. This enhanced connectivity not only allows for real-time monitoring but also agile decision-making in manufacturing.

The overall industry is divided into component, technology, application, end use, and region.

Based on technology, the AI in industrial machinery market size from the computer version segment is slated to witness significant growth during 2024-2032 driven by its role in advanced visual analysis and quality control. When integrated with AI, computer vision technologies empower machinery to accurately interpret and analyze visual data from sensors and cameras. This precision bolsters defect detection, quality assurance, and automated inspections, ensuring high production standards and minimizing waste.

AI in industrial machinery market from the quality control application segment is anticipated to expand through 2032. AI-driven quality control systems harness advanced algorithms and ML to scrutinize product data, identify defects, and uphold rigorous quality benchmarks. Their ability to swiftly and accurately process vast data volumes surpasses human inspectors, leading to reduced errors and diminished waste.

Asia Pacific AI in industrial machinery industry is anticipated to grow at a significant pace over 2024-2032. This surge is fueled by swift industrialization and technological advancements. As manufacturing powerhouses like China, India, and Japan bolster their capabilities, the demand for AI technologies to drive efficiency and innovation in industrial processes is on the rise.

Chapter 1 Methodology and Scope

1.1 Market scope and definitions
1.2 Base estimates and calculations
1.3 Forecast calculations
1.4 Data sources
- 1.4.1 Primary
- 1.4.2 Secondary
  - 1.4.2.1 Paid sources
  - 1.4.2.2 Public sources

Chapter 2 Executive Summary

2.1 Industry 360° synopsis, 2021-2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
- 3.1.1 Factors affecting the value chain
- 3.1.2 Profit margin analysis
- 3.1.3 Disruptions
- 3.1.4 Future outlook
- 3.1.5 Manufacturers
- 3.1.6 Distributors
3.2 Supplier landscape
3.3 Profit margin analysis
3.4 Technological overview
3.5 Regulatory landscape
3.6 Impact forces
- 3.6.1 Growth drivers
  - 3.6.1.1 Rising adoption of Al in manufacturing sector
  - 3.6.1.2 Integration with IOT and cloud computing
  - 3.6.1.3 Advanced analytics and decision-making
- 3.6.2 Industry pitfalls and challenges
  - 3.6.2.1 High implementation costs
  - 3.6.2.2 Skill Gap and Workforce Adaptation
3.7 Growth potential analysis
3.8 Porter's analysis
3.9 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates and Forecast, By Component, 2021-2032 (USD million)

5.1 Key trends
5.2 Hardware
5.3 Software
5.4 Services

Chapter 6 Market Estimates and Forecast, By Technology, 2021-2032 (USD million))

6.1 Key trends
6.2 Machine learning
6.3 Computer vision
6.4 Context awareness
6.5 Natural language processing

Chapter 7 Market Estimates and Forecast, By Application, 2021-2032 (USD million)

7.1 Key trends
7.2 Predictive maintenance
7.3 Quality control
7.4 Process optimization
7.5 Supply chain optimization
7.6 Intelligent robotics
7.7 Autonomous vehicles and guided systems
7.8 Energy management
7.9 Human-machine interfaces
7.10 Others

Chapter 8 Market Estimates and Forecast, By End Use, 2021-2032 (USD million)

8.1 Key trends
8.2 Agriculture
8.3 Construction
8.4 Packaging
8.5 Food processing
8.6 Mining
8.7 Semiconductor

Chapter 9 Market Estimates and Forecast, By Region, 2021-2032 (USD million)

9.1 Key trends
9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Italy
- 9.3.5 Spain
- 9.3.6 Russia
- 9.3.7 Rest of Europe
9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 South Korea
- 9.4.5 Australia
- 9.4.6 Rest of Asia Pacific
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Rest of Latin America
9.6 MEA
- 9.6.1 South Africa
- 9.6.2 Saudi Arabia
- 9.6.3 UAE
- 9.6.4 Rest of MEA