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市场调查报告书
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1856861

面向工业自动化的边缘人工智慧市场预测至2032年：按组件、部署模式、应用、最终用户和区域分類的全球分析

Edge AI for Industrial Automation Market Forecasts to 2032 - Global Analysis By Component (Edge AI Hardware, Edge AI Software and Edge AI Services), Deployment Model, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，全球工业自动化边缘人工智慧市场预计到 2025 年将达到 30.4 亿美元，到 2032 年将达到 137.8 亿美元，预测期内复合年增长率为 24.1%。

边缘人工智慧正在变革工业自动化，它直接在生产车间的机器和设备层面处理人工智慧。与传统的云端人工智慧不同，边缘人工智慧能够实现即时数据分析，从而加快关键任务的决策速度。它能够改善预测性维护，确保更高的品管，提高整体效率，并减少机器停机时间。本地资料处理还能增强安全性和隐私性，因为它将关键运行资料保留在本地，而不是发送到远端伺服器。此外，边缘人工智慧支援在各种工业环境中灵活且可扩展地部署，帮助製造商降低成本、优化生产力并快速回应不断变化的生产需求。

根据塔塔咨询服务公司 (TCS) 的数据，来自高科技製造业的数据显示，边缘人工智慧系统可以透过在地化的智慧决策，减少 40-60% 的云端通讯，同时提高运作和产品品质。

提高营运效率

边缘人工智慧透过优化工作流程、自动化重复性任务和实现预测性维护，显着提升工业场所的营运效率。智慧监控和数据驱动的洞察能够减少错误并最大限度地减少资源浪费。自动化决策有助于快速调整生产线，减少人为干预并提升整体绩效。这不仅降低了成本，提高了产量，还有助于在不牺牲品质的前提下满足不断增长的需求。借助边缘人工智慧，製造商可以改善流程、最大限度地提高机器利用率并提升能源效率。对效率和成本效益的关注是市场成长的主要驱动力，有助于企业保持竞争优势和卓越营运。

高昂的实施成本

在工业自动化领域部署边缘人工智慧需要对先进的硬体、软体和基础设施进行大量前期投资。这种财务负担对中小企业来说是一项挑战，阻碍了边缘人工智慧的广泛应用。将边缘人工智慧整合到传统设备中通常需要昂贵的客製化和专业人员。持续的维护、软体升级和安全措施进一步增加了支出。儘管边缘人工智慧能够提高营运效率，但高昂的实施成本仍是一大障碍。预算有限的企业可能仍依赖传统的自动化技术，而资金限制是限制边缘人工智慧在全球工业环境中推广应用的主要因素。

采用智慧製造

边缘人工智慧透过提供即时监控、预测性维护和自动化决策，为智慧製造创造了机会。在生产设施中，现场人工智慧处理可以优化工作流程、最大限度地减少停机时间并提高产品品质。边缘人工智慧与物联网设备结合，可实现无缝资料撷取和智慧自动化。随着对工业4.0解决方案的需求不断增长，边缘人工智慧正成为数位转型的关键驱动力。实施边缘人工智慧能够帮助製造商提高效率、降低成本并快速回应不断变化的生产需求。这一成长趋势为边缘人工智慧技术在全球工业自动化领域带来了巨大的市场潜力。

科技快速变革

边缘人工智慧（Edge AI）的普及应用面临来自人工智慧（AI）、物联网（IoT）和工业自动化技术快速发展的威胁。新技术的涌现和频繁的系统更新可能迅速使现有边缘人工智慧解决方案过时。企业可能需要投入高昂的成本，并面临营运方面的挑战，才能更新基础设施以跟上技术进步的脚步。这种快速变化会给投资者和製造商带来不确定性，从而推迟他们的采用决策。无法持续升级的企业将面临落后于竞争对手的风险，而行动迟缓的企业则可能难以维持营运效率。技术的快速发展和潜在的过时风险对工业自动化边缘人工智慧市场的成长构成了重大威胁。

新冠疫情的影响：

新冠疫情对工业自动化领域的边缘人工智慧市场产生了显着影响，扰乱了供应链并延缓了工业专案的推进。劳动力限制和封锁措施迫使製造商部署自动化技术，以在现场员工减少的情况下维持营运。边缘人工智慧因其能够实现远端监控、预测性维护和运作控制，从而最大限度地减少对人工干预的依赖，而备受青睐。儘管边缘人工智慧优势显着，但经济的不确定性和预算的限制阻碍了对先进人工智慧解决方案的大规模投资。随着各行业的復苏，数位转型正在加速推进，边缘人工智慧的应用日益广泛，旨在提高效率、韧性和职场安全，这在全球范围内既带来了市场挑战，也带来了机会。

预计在预测期内，边缘人工智慧硬体细分市场将是最大的细分市场。

由于边缘人工智慧硬体具备即时数据分析和现场决策的固有能力，预计在预测期内，该细分市场将占据最大的市场份额。工业运作依赖处理器、感测器和专用运算设备来成功实施边缘人工智慧解决方案。这些硬体作为支援软体和服务应用的基础，同时也能与现有的工业系统和物联网设备整合。对可靠、高性能和节能硬体日益增长的需求正在推动其市场主导地位。随着工业领域越来越重视自动化、预测性维护和流程优化，对边缘人工智慧硬体的投资仍然十分可观，使其成为工业边缘人工智慧市场中规模最大、最具影响力的细分市场。

预计在预测期内，电子和半导体产业将实现最高的复合年增长率。

由于製造业对更高精度、更高速度和更高自动化程度的需求，预计电子和半导体产业在预测期内将实现最高成长率。即时监控、预测性维护和缺陷检测对于最大限度地提高半导体和电子产品生产的产量比率和减少停机时间至关重要。边缘人工智慧能够实现现场数据处理和分析，从而提高营运效率和准确性。智慧工厂技术、工业4.0实践和基于自动化的品管的日益普及，正在推动该行业的快速扩张。电子製造领域的持续技术创新，进一步巩固了该产业作为边缘人工智慧市场加速成长的主要推动力。

比最大的地区

在预测期内，北美预计将占据最大的市场份额，这主要得益于快速的工业数位转型、大量的研发投入以及完善的製造基础设施。该地区汇集了许多领先的人工智慧和工业自动化公司，推动了边缘人工智慧解决方案的早期和广泛部署。汽车、电子和半导体等关键产业正在利用即时分析、预测性维护和智慧工厂实践。有利的政府政策和对工业4.0技术日益增长的需求进一步巩固了其市场领先地位。技术创新、经验丰富的劳动力和强大的工业生态系统使北美能够保持最大的市场份额，并使其成为全球工业自动化边缘人工智慧应用的领先中心。

复合年增长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率，这主要得益于快速的工业发展和人工智慧赋能的智慧製造技术的日益普及。包括中国、日本、韩国和印度在内的主要国家正在推动工业4.0战略、即时监控和预测性维护在汽车、电子和重型机械领域的应用。政府对工业现代化的大力支持以及对营运效率的日益重视进一步推动了这一成长。亚太地区是成长最快的地区，这得益于新兴市场、技术进步和不断扩大的工业基础设施，使其成为全球工业自动化边缘人工智慧应用的领先中心。

免费客製化服务

订阅本报告的用户可享有以下免费客製化服务之一：

  • 公司简介
    • 对至多三家其他市场公司进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行市场估算、预测和复合年增长率分析（註：基于可行性检查）
  • 竞争基准化分析
    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究资讯来源
    • 初级研究资讯来源
    • 次级研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章：按组件分類的工业自动化边缘人工智慧市场

  • 边缘人工智慧硬体
  • 边缘人工智慧软体
  • 边缘人工智慧服务

6. 按部署模式分類的工业自动化边缘人工智慧市场

  • 本地部署边缘
  • 混合边缘云端
  • 联邦学习模型

第七章：按应用分類的工业自动化边缘人工智慧市场

  • 预测性维护
  • 品质检验
  • 流程优化
  • 人机介面（HMI）
  • 安全与合规性监控

第八章：面向最终用户的工业自动化边缘人工智慧市场

  • 汽车製造
  • 电子和半导体
  • 食品和饮料加工
  • 化工和製药厂
  • 重型机械和设备

9. 全球工业自动化边缘人工智慧市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十章：重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与併购
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十一章 企业概况

  • Siemens
  • Rockwell Automation
  • ABB
  • Schneider Electric
  • Honeywell
  • Emerson Electric
  • Mitsubishi Electric
  • Advantech
  • Dell Technologies
  • NVIDIA
  • Intel
  • Arm
  • Cyient
  • MosChip Technologies
  • Barbara Tech
Product Code: SMRC31733

According to Stratistics MRC, the Global Edge AI for Industrial Automation Market is accounted for $3.04 billion in 2025 and is expected to reach $13.78 billion by 2032 growing at a CAGR of 24.1% during the forecast period. Industrial automation is being transformed by Edge AI, which processes artificial intelligence directly at the machine or device level on production floors. Unlike conventional cloud AI, Edge AI allows instant data analysis, enabling quicker decision-making for essential operations. It improves predictive maintenance, ensures higher quality control, and boosts overall efficiency while decreasing machine downtime. Local data processing also enhances security and privacy by keeping critical operational data on-site instead of sending it to remote servers. Furthermore, Edge AI allows flexible, scalable deployment across various industrial environments, helping manufacturers cut costs, optimize productivity, and swiftly respond to evolving production requirements.

According to Tata Consultancy Services (TCS), data from high-tech manufacturing operations reveals that Edge AI systems can reduce cloud transmission volume by 40-60%, while improving uptime and product quality through localized, intelligent decision-making.

Market Dynamics:

Driver:

Enhanced operational efficiency

Operational efficiency in industrial settings is significantly improved through Edge AI, which optimizes workflows, automates repetitive tasks, and enables predictive maintenance. Intelligent monitoring and data-driven insights reduce errors and minimize resource wastage. Automated decisions facilitate rapid adjustments on production lines, limiting human intervention and enhancing overall performance. This leads to cost reductions, increased throughput, and the ability to meet growing demand without sacrificing quality. By leveraging Edge AI, manufacturers can refine processes, maximize machinery usage, and improve energy efficiency. The focus on efficiency and cost-effectiveness is a key driver of market growth, helping businesses maintains competitiveness and operational excellence.

Restraint:

High implementation costs

Implementing Edge AI for industrial automation demands substantial initial investments in advanced hardware, software, and infrastructure. This financial burden can be challenging for small and medium enterprises, hindering widespread adoption. Integrating Edge AI with legacy equipment often requires costly customization and expert personnel. Ongoing maintenance, software upgrades, and security measures further increase expenditure. Even though Edge AI improves operational efficiency, the high implementation cost remains a key barrier. Organizations with restricted budgets may continue relying on conventional automation techniques, making financial constraints a significant restraint on the global expansion of Edge AI in industrial environments.

Opportunity:

Adoption of smart manufacturing

Edge AI creates opportunities in smart manufacturing by providing real-time monitoring, predictive maintenance, and automated decision-making. Production facilities can optimize workflows, minimize downtime, and enhance product quality using on-site AI processing. Coupled with IoT devices, Edge AI enables seamless data collection and intelligent automation. As the demand for Industry 4.0 solutions grows, Edge AI emerges as a crucial driver of digital transformation. Implementing Edge AI allows manufacturers to increase efficiency, reduce costs, and quickly adapt to evolving production needs. This growing trend offers substantial market potential for Edge AI technologies in global industrial automation sectors.

Threat:

Rapid technological changes

Edge AI adoption faces threats from the rapid evolution of AI, IoT, and industrial automation technologies. New innovations and frequent system updates can quickly make current Edge AI solutions outdated. Companies may incur high costs and face operational challenges to update infrastructure in line with technological advancements. Such rapid changes create uncertainty for investors and manufacturers, potentially delaying implementation decisions. Organizations that cannot continuously upgrade risk lagging behind competitors while slower adopters may struggle to maintain operational efficiency. The fast pace of technological progress and the possibility of obsolescence pose a significant threat to the growth of the Edge AI market in industrial automation.

Covid-19 Impact:

The COVID-19 pandemic had a notable effect on the Edge AI for Industrial Automation Market, disrupting supply chains and postponing industrial initiatives. Workforce limitations and lockdown measures compelled manufacturers to implement automation technologies to sustain operations with fewer on-site employees. Edge AI became valuable for enabling remote monitoring, predictive maintenance, and operational control, minimizing reliance on human intervention. Despite its benefits, economic uncertainties and limited budgets slowed significant investments in advanced AI solutions. As industries recover, there is an accelerated push toward digital transformation, with Edge AI adoption increasing to improve efficiency, resilience, and workplace safety, presenting both market challenges and opportunities globally.

The edge AI hardware segment is expected to be the largest during the forecast period

The edge AI hardware segment is expected to account for the largest market share during the forecast period due to its essential function in enabling real-time data analysis and on-site decision-making. Industrial operations depend on processors, sensors, and dedicated computing equipment to implement Edge AI solutions successfully. Hardware serves as the backbone for supporting software and service applications while integrating with existing industrial systems and IoT devices. The growing need for dependable, high-performance, and energy-efficient hardware strengthens its market dominance. With industries increasingly focusing on automation, predictive maintenance, and process optimization, investments in Edge AI hardware remain substantial, making it the largest and most influential segment in the industrial Edge AI market.

The electronics & semiconductors segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the electronics & semiconductors segment is predicted to witness the highest growth rate, driven by the need for high precision, speed, and automation in manufacturing. Real-time monitoring, predictive maintenance, and defect detection are crucial for maximizing yields and reducing downtime in semiconductor and electronics production. Edge AI enables on-site data processing and analytics, enhancing operational efficiency and accuracy. Increasing adoption of smart factory technologies, Industry 4.0 practices, and automation-based quality control supports the rapid expansion of this segment. Continuous innovation in electronics manufacturing further positions this sector as a major contributor to the accelerated growth of the Edge AI market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to rapid industrial digital transformation, significant R&D spending, and a well-established manufacturing infrastructure. The region hosts major AI and industrial automation companies, facilitating early and widespread deployment of Edge AI solutions. Key industries, including automotive, electronics, and semiconductors, leverage real-time analytics, predictive maintenance, and smart factory practices. Favorable government regulations and growing demand for Industry 4.0 technologies further support its market leadership. Technological innovation, an experienced workforce, and a strong industrial ecosystem enable North America to maintain the largest market share, making it the primary hub for global Edge AI adoption in industrial automation.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid industrial development and increasing adoption of AI-enabled smart manufacturing. Key economies, including China, Japan, South Korea, and India, are implementing Industry 4.0 strategies, real-time monitoring, and predictive maintenance across automotive, electronics, and heavy equipment sectors. Strong government support for industrial modernization and a growing focus on operational efficiency further accelerate growth. The region's combination of emerging markets, technological progress, and expanding industrial infrastructure positions Asia-Pacific as the region with the highest growth rate, making it a major hub for Edge AI adoption in global industrial automation.

Key players in the market

Some of the key players in Edge AI for Industrial Automation Market include Siemens, Rockwell Automation, ABB, Schneider Electric, Honeywell, Emerson Electric, Mitsubishi Electric, Advantech, Dell Technologies, NVIDIA, Intel, Arm, Cyient, MosChip Technologies and Barbara Tech.

Key Developments:

In October 2025, Siemens Mobility has signed a major contract with Trivia Trens S.A. to modernise three of Sao Paulo's commuter rail lines using Automatic Train Operation (ATO) over ETCS Level 2 - the most extensive deployment of this technology in Latin America. The project, covering 140 kilometres of track and 46 stations across lines 11-Coral, 12-Sapphire, and 13-Jade, will deliver a fully digital signalling and control system designed to increase capacity, safety, and efficiency across one of the busiest rail networks in the region.

In October 2025, ABB has signed a term sheet agreement with SwitcH2 to engineer and supply automation and electrification solutions for SwitcH2's floating production, storage and offloading (FPSO) unit dedicated to producing green ammonia from green hydrogen, to support future demand for low-carbon marine fuels.

In April 2023, Rockwell Automation, Inc signed a Memorandum of Understanding to form a partnership with leading global robot manufacturer Doosan Robotics and its parent company Doosan Corporation, both Seoul-based entities and members of the historic summit in Washington, D.C., commemorating the 70th anniversary of the U.S. - South Korea alliance.

Components Covered:

  • Edge AI Hardware
  • Edge AI Software
  • Edge AI Services

Deployment Models Covered:

  • On-Premise Edge
  • Hybrid Edge-Cloud
  • Federated Learning Models

Applications Covered:

  • Predictive Maintenance
  • Quality Inspection
  • Process Optimization
  • Human-Machine Interface (HMI)
  • Safety & Compliance Monitoring

End Users Covered:

  • Automotive Manufacturing
  • Electronics & Semiconductors
  • Food & Beverage Processing
  • Chemical & Pharmaceutical Plants
  • Heavy Machinery & Equipment

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Edge AI for Industrial Automation Market, By Component

  • 5.1 Introduction
  • 5.2 Edge AI Hardware
  • 5.3 Edge AI Software
  • 5.4 Edge AI Services

6 Global Edge AI for Industrial Automation Market, By Deployment Model

  • 6.1 Introduction
  • 6.2 On-Premise Edge
  • 6.3 Hybrid Edge-Cloud
  • 6.4 Federated Learning Models

7 Global Edge AI for Industrial Automation Market, By Application

  • 7.1 Introduction
  • 7.2 Predictive Maintenance
  • 7.3 Quality Inspection
  • 7.4 Process Optimization
  • 7.5 Human-Machine Interface (HMI)
  • 7.6 Safety & Compliance Monitoring

8 Global Edge AI for Industrial Automation Market, By End User

  • 8.1 Introduction
  • 8.2 Automotive Manufacturing
  • 8.3 Electronics & Semiconductors
  • 8.4 Food & Beverage Processing
  • 8.5 Chemical & Pharmaceutical Plants
  • 8.6 Heavy Machinery & Equipment

9 Global Edge AI for Industrial Automation Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Siemens
  • 11.2 Rockwell Automation
  • 11.3 ABB
  • 11.4 Schneider Electric
  • 11.5 Honeywell
  • 11.6 Emerson Electric
  • 11.7 Mitsubishi Electric
  • 11.8 Advantech
  • 11.9 Dell Technologies
  • 11.10 NVIDIA
  • 11.11 Intel
  • 11.12 Arm
  • 11.13 Cyient
  • 11.14 MosChip Technologies
  • 11.15 Barbara Tech

List of Tables

  • Table 1 Global Edge AI for Industrial Automation Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Edge AI for Industrial Automation Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Edge AI for Industrial Automation Market Outlook, By Edge AI Hardware (2024-2032) ($MN)
  • Table 4 Global Edge AI for Industrial Automation Market Outlook, By Edge AI Software (2024-2032) ($MN)
  • Table 5 Global Edge AI for Industrial Automation Market Outlook, By Edge AI Services (2024-2032) ($MN)
  • Table 6 Global Edge AI for Industrial Automation Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 7 Global Edge AI for Industrial Automation Market Outlook, By On-Premise Edge (2024-2032) ($MN)
  • Table 8 Global Edge AI for Industrial Automation Market Outlook, By Hybrid Edge-Cloud (2024-2032) ($MN)
  • Table 9 Global Edge AI for Industrial Automation Market Outlook, By Federated Learning Models (2024-2032) ($MN)
  • Table 10 Global Edge AI for Industrial Automation Market Outlook, By Application (2024-2032) ($MN)
  • Table 11 Global Edge AI for Industrial Automation Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 12 Global Edge AI for Industrial Automation Market Outlook, By Quality Inspection (2024-2032) ($MN)
  • Table 13 Global Edge AI for Industrial Automation Market Outlook, By Process Optimization (2024-2032) ($MN)
  • Table 14 Global Edge AI for Industrial Automation Market Outlook, By Human-Machine Interface (HMI) (2024-2032) ($MN)
  • Table 15 Global Edge AI for Industrial Automation Market Outlook, By Safety & Compliance Monitoring (2024-2032) ($MN)
  • Table 16 Global Edge AI for Industrial Automation Market Outlook, By End User (2024-2032) ($MN)
  • Table 17 Global Edge AI for Industrial Automation Market Outlook, By Automotive Manufacturing (2024-2032) ($MN)
  • Table 18 Global Edge AI for Industrial Automation Market Outlook, By Electronics & Semiconductors (2024-2032) ($MN)
  • Table 19 Global Edge AI for Industrial Automation Market Outlook, By Food & Beverage Processing (2024-2032) ($MN)
  • Table 20 Global Edge AI for Industrial Automation Market Outlook, By Chemical & Pharmaceutical Plants (2024-2032) ($MN)
  • Table 21 Global Edge AI for Industrial Automation Market Outlook, By Heavy Machinery & Equipment (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.