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市場調查報告書
商品編碼
1544813
工業機械市場人工智慧、機會、成長動力、產業趨勢分析與預測，2024-2032AI in Industrial Machinery Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032 |
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由於製造流程中營運效率和生產力提高的需求，預計 2024 年至 2032 年間，工業機械市場規模中的人工智慧複合年成長率將達到 27.2%。透過利用機器學習 (ML) 和預測分析等技術，人工智慧使機械能夠進行即時資料分析、最佳化生產計劃並預測設備故障。這種預測性維護不僅可以減少停機時間，還可以減少維護費用。此外，人工智慧驅動的自動化提高了製造的精度和速度。例如，2024 年 5 月，Composable 推出了無程式碼 UI 平台，使工程師能夠透過將操作員專業知識整合到現實場景中來直接訓練 AI 代理程式。
智慧製造的興起和工業4.0的推動將進一步推動市場成長。隨著企業傾向於互聯和自動化生產環境，人工智慧在促進機器、感測器和控制系統之間的無縫互動方面發揮關鍵作用。這種增強的連接性不僅可以實現即時監控，還可以在製造過程中做出靈活的決策。
整個產業分為組件、技術、應用、最終用途和區域。
基於技術，由於人工智慧在先進視覺分析和品質控制方面的作用，電腦版領域的人工智慧在工業機械市場規模預計將在 2024 年至 2032 年期間顯著成長。當與人工智慧整合時，電腦視覺技術使機器能夠準確地解釋和分析來自感測器和攝影機的視覺資料。這種精度支援缺陷檢測、品質保證和自動化檢查，確保高生產標準並最大限度地減少浪費。
人工智慧在品質控制應用領域的工業機械市場資料將在 2032 年擴大。它們快速、準確地處理大量資料的能力超過了人類檢查員，從而減少了錯誤和浪費。
亞太地區工業機械產業的人工智慧預計將在 2024 年至 2032 年期間大幅成長。這種激增是由快速工業化和技術進步所推動的。隨著中國、印度和日本等製造業強國的能力不斷增強，對人工智慧技術推動工業流程效率和創新的需求不斷增加。
目錄
第 1 章：方法與範圍
第 2 章：執行摘要
第 3 章：產業洞察
- 產業生態系統分析
- 影響價值鏈的因素
- 利潤率分析
- 干擾
- 未來展望
- 製造商
- 經銷商
- 供應商格局
- 利潤率分析
- 技術概覽
- 監管環境
- 衝擊力
- 成長動力
- 製造業擴大採用鋁
- 與物聯網和雲端運算整合
- 高階分析與決策
- 產業陷阱與挑戰
- 實施成本高
- 技能差距與勞動適應
- 成長動力
- 成長潛力分析
- 波特的分析
- PESTEL分析
第 4 章：競爭格局
- 介紹
- 公司市佔率分析
- 競爭定位矩陣
- 戰略展望矩陣
第 5 章：市場估計與預測：按組成部分，2021-2032 年
- 主要趨勢
- 硬體
- 軟體
- 服務
第 6 章：市場估計與預測：按技術分類，2021-2032）
- 主要趨勢
- 機器學習
- 電腦視覺
- 情境意識
- 自然語言處理
第 7 章：市場估計與預測：按應用分類，2021-2032 年
- 主要趨勢
- 預測性維護
- 品質管制
- 流程最佳化
- 供應鏈最佳化
- 智慧機器人
- 自動駕駛車輛和導引系統
- 能源管理
- 人機介面
- 其他
第 8 章：市場估計與預測：依最終用途，2021-2032 年
- 主要趨勢
- 農業
- 建造
- 包裝
- 食品加工
- 礦業
- 半導體
第 9 章：市場估計與預測：按地區，2021-2032 年
- 主要趨勢
- 北美洲
- 美國
- 加拿大
- 歐洲
- 英國
- 德國
- 法國
- 義大利
- 西班牙
- 俄羅斯
- 歐洲其他地區
- 亞太地區
- 中國
- 印度
- 日本
- 韓國
- 澳洲
- 亞太地區其他地區
- 拉丁美洲
- 巴西
- 墨西哥
- 拉丁美洲其他地區
- MEA
- 南非
- 沙烏地阿拉伯
- 阿拉伯聯合大公國
- MEA 的其餘部分
第 10 章：公司簡介
- 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
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.
Table of Contents
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
- 3.6.1 Growth drivers
- 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
Chapter 10 Company Profiles
- 10.1 ABB Ltd.
- 10.2 Amazon Web Services (AWS)
- 10.3 Cisco Systems, Inc.
- 10.4 FANUC Corporation
- 10.5 Google LLC
- 10.6 Hitachi, Ltd.
- 10.7 Honeywell International Inc.
- 10.8 IBM Corporation
- 10.9 Intel Corporation
- 10.10 Microsoft Corporation
- 10.11 NVIDIA Corporation
- 10.12 Qualcomm Technologies
- 10.13 Rockwell Automation, Inc.
- 10.14 Schneider Electric SE
- 10.15 Siemens AG
