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商品編碼

2160854

人工智慧驅動的製程控制市場預測至2034年：全球分析（按組件、製程控制方法、部署模型、流程類型、企業規模、人工智慧技術、應用、最終用戶產業和地區分類）

AI-Based Process Control Market Forecasts To 2034 - Global Analysis By Component (Hardware, Software and Services), Process Control Method, Deployment Mode, Process Type, Enterprise Size, AI Technology, Application, End-Use Industry and By Geography

出版日期: 2026年10月22日 | 出版商:

Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

簡介目錄圖表

根據 Stratistics MRC 的數據，預計到 2026 年，全球基於人工智慧的製程控制市場將達到 146 億美元，在預測期內以 23.3% 的複合年成長率成長，到 2034 年將達到 780 億美元。

隨著企業採用人工智慧技術來提升工業績效和簡化生產流程，人工智慧驅動的製程控制市場正在不斷擴張。這些系統融合了機器學習、即時監控和進階數據分析技術，能夠有效控制流程、提高產品品質穩定性並減少營運低效環節。其應用領域涵蓋製造業、能源、製藥、汽車、化學和食品加工等產業。對智慧工廠、工業自動化、預測性維護和成本最佳化的投資不斷增加，也推動了市場的發展。此外，連網型設備、雲端平台和先進感測技術的融合，進一步增強了製程控制能力，並為人工智慧驅動的解決方案在各個工業領域創造了新的機會。

工業自動化應用範圍擴大

工業自動化的日益普及正顯著推動人工智慧製程控制市場的成長。企業正採用智慧技術來提高生產效率、減少對人工的依賴並確保產品品質的穩定性。人工智慧控制系統透過評估即時過程資訊、檢測異常情況並調整運行條件來維持高效率的運作。這些功能使製造商能夠提高生產效率、最大限度地減少操作失誤並最佳化資源消耗。此外，智慧製造設施和工業4.0專案的擴展也推動了對先進自動化解決方案的需求。因此，各行業正在投資人工智慧製程控制技術，以提高效率和生產可靠性。

較高的初始實施和整合成本

實施和整合所需的高昂前期成本可能會阻礙人工智慧驅動的製程控制市場的發展。製造企業可能需要購買先進的軟體、連網感測器、運算資源和相容的自動化設備。將這些技術整合到現有的生產基礎設施中可能需要額外的改造、技術評估和系統升級。員工培訓、平台維護和網路安全措施會進一步增加實施成本。對於預算有限的中小型製造商和企業而言，證明此類投資的合理性可能很困難。此外，初始成本回收期的不確定性可能會延遲購買決策，並減緩人工智慧驅動的製程控制技術的普及。

開發基於雲端和邊緣的人工智慧製程控制解決方案

雲端運算和邊緣人工智慧的進步正為基於人工智慧的過程控制市場開闢新的成長途徑。基於雲端的系統能夠實現集中式分析、遠端監控以及跨地理位置分散的設施的資訊共用。邊緣運算則在更靠近工業設備的位置處理數據，從而實現更快的回應速度並減少對中央伺服器持續通訊的依賴。將這兩種方法結合可以提升製程監控、營運柔軟性和系統效能。此外，它還允許企業根據不斷變化的生產需求擴展其控制基礎設施。隨著互聯工業環境的日益普及，解決方案供應商有機會部署整合平台，從而在各種製造營運中提供高效、響應迅速且易於使用的基於人工智慧的製程控制。

監管不確定性和合規要求

監管的不確定性和不斷變化的合規要求對基於人工智慧的過程控制市場構成威脅。各國政府和產業監管機構正在製定有關人工智慧、資料保護、網路安全和自動化系統安全運作的規則。區域監管差異可能會使技術提供者的產品開發、部署和國際擴張變得更加複雜。行業組織可能需要進行額外的評估、維護詳細的文檔，並證明人工智慧驅動的決策符合適用的安全和課責標準。這些義務會增加合規成本並延長部署週期。此外，不明確的要求可能會給買家帶來不確定性，從而可能延遲受監管行業對基於人工智慧的過程控制解決方案的投資。

新型冠狀病毒（COVID-19）的影響：

新冠疫情危機對人工智慧驅動的製程控制市場產生了影響，初期衝擊和工業數位化需求激增並存。工廠關閉、零件短缺、勞動力短缺以及資本投資延遲等因素暫時減緩了技術應用。同時，企業意識到人工智慧驅動的自動化在維持營運和減少現場人員方面具有重要價值。隨著製造商尋求更高的柔軟性和韌性，遠端監控、預測分析和智慧流程最佳化變得日益重要。疫情促使企業重新評估傳統的生產策略，並投資先進的控制技術。在最初的衝擊過後，對自動化、營運效率和智慧工廠發展的重新關注推動了市場成長和未來的應用。

在預測期內，硬體領域預計將佔據最大的市場佔有率。

預計在預測期內，硬體領域將佔據最大的市場佔有率，這主要得益於對智慧製造、工業互聯和自動化控制基礎設施投資的增加。感測器、工業控制器、計算設備和監控設備等關鍵硬體使基於人工智慧的系統能夠收集運行數據並控制生產流程。智慧工廠和互聯工業機械的日益普及正在推動對這些組件的需求。此外，對精確的流程監控、穩定的產品品質和高效的設備性能日益成長的需求，也促使企業採用先進的硬體技術。這些趨勢進一步凸顯了硬體在人工智慧驅動的工業流程管理中的重要性。

在預測期內，醫藥和生技產業預計將呈現最高的複合年成長率。

在預測期內，受藥品生產規模擴大、生物技術進步以及智慧製造系統日益普及的推動，製藥和生物技術產業預計將呈現最高的成長率。人工智慧驅動的製程控制技術使企業能夠控制關鍵生產參數，保持批次間一致性，並降低製程變異性。對生物製藥、創新療法和疫苗日益成長的需求，加劇了對先進監測和最佳化解決方案的需求。此外，嚴格的品質要求和監管合規義務也在推動自動化技術的應用。機器學習、預測分析和即時製程監測的日益普及，可望提高生產效率，增強產品均一性，並確保藥品和生物技術產品的可靠生產。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其完善的工業生態系統和先進技術的廣泛應用。該地區擁有強大的AI開發商、自動化解決方案供應商和成熟的工業運營商網路。數位轉型、智慧製造和自動化流程管理的投入不斷增加，正在推動市場成長。能源、化學、製藥、電子以及石油和天然氣等行業的公司正在採用人工智慧系統來提高效率、保持品質一致性並最佳化工業營運。此外，技術創新、研發投入以及經驗豐富的技術人才的加入，也鞏固了該地區的市場領先地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於快速的工業化進程、不斷擴大的製造業產能以及對人工智慧技術投資的增加。中國、印度、日本和韓國等國家正在加強其工業自動化基礎建設，並積極採用智慧製造實踐。電子、半導體、製藥、化學和汽車行業日益成長的需求正在推動智慧過程控制系統的應用。政府支持數位轉型和工業現代化的措施也進一步促進了該地區的成長。此外，對互聯工廠、機器人和先進分析技術的投資不斷增加，也為市場擴張創造了巨大的機會。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

企業概況
- 對其他市場參與者（最多 3 家公司）進行全面分析
- 對主要公司進行SWOT分析（最多3家公司）
區域分類
- 根據客戶要求，我們可以提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
競爭性標竿分析
- 根據產品系列、企業發展和策略聯盟對重點公司進行基準分析。

北美洲
- 美國
- 加拿大
- 墨西哥
歐洲
- 英國
- 德國
- 法國
- 義大利
- 西班牙
- 荷蘭
- 比利時
- 瑞典
- 瑞士
- 波蘭
- 其他歐洲國家
亞太地區
- 中國
- 日本
- 印度
- 韓國
- 澳洲
- 印尼
- 泰國
- 馬來西亞
- 新加坡
- 越南
- 其他亞太國家
南美洲
- 巴西
- 阿根廷
- 哥倫比亞
- 智利
- 秘魯
- 其他南美國家
世界其他地區（RoW）
- 中東
  - 沙烏地阿拉伯
  - 阿拉伯聯合大公國
  - 卡達
  - 以色列
  - 其他中東國家
- 非洲
  - 南非
  - 埃及
  - 摩洛哥
  - 其他非洲國家

第14章策略市場資訊

工業價值網路和供應鏈評估
空白區域和機會地圖
產品演進與市場生命週期分析
通路、經銷商和打入市場策略的評估

第15章產業趨勢與策略舉措

併購
夥伴關係、聯盟和合資企業
新產品發布和認證
擴大生產能力和投資
其他策略舉措

第16章：公司簡介

Siemens AG
ABB Ltd.
Honeywell International Inc.
Emerson Electric Co.
Yokogawa Electric Corporation
Rockwell Automation, Inc.
Schneider Electric SE
Mitsubishi Electric Corporation
GE Vernova
Valmet Oyj
SUPCON Technology Co., Ltd.
HollySys Automation Technologies Ltd.
Fuji Electric Co., Ltd.
Bosch Rexroth AG
FLSmidth A/S
PiControl Solutions LLC
Mitsubishi Heavy Industries, Ltd.
Endress+Hauser Group

簡介目錄圖表

Product Code: SMRC40364

According to Stratistics MRC, the Global AI-Based Process Control Market is accounted for $14.6 billion in 2026 and is expected to reach $78.0 billion by 2034 growing at a CAGR of 23.3% during the forecast period. The AI-Based Process Control Market is expanding as businesses integrate artificial intelligence technologies to enhance industrial performance and streamline production activities. These systems combine machine learning, real-time monitoring, and advanced data analysis to regulate processes, improve product consistency, and reduce operational inefficiencies. Their applications span manufacturing, energy, pharmaceuticals, automotive, chemicals, and food processing. Increasing investments in smart factories, industrial automation, predictive maintenance, and cost optimization are contributing to market development. Additionally, the integration of connected devices, cloud-based platforms, and advanced sensing technologies is strengthening process control capabilities and creating new opportunities for AI-driven solutions across diverse industrial sectors.

Market Dynamics:

Driver:

Increasing Adoption of Industrial Automation

The growing implementation of industrial automation is significantly supporting the expansion of the AI-Based Process Control Market. Businesses are deploying intelligent technologies to streamline production, reduce dependence on manual operations, and ensure consistent output quality. AI-enabled control systems evaluate live process information, detect irregularities, and modify operating conditions to maintain efficient performance. These functions enable manufacturers to enhance productivity, limit operational mistakes, and optimize resource consumption. Additionally, the expansion of smart manufacturing facilities and Industry 4.0 programs is increasing demand for advanced automation solutions. As a result, industries are investing in AI-powered process control technologies to strengthen efficiency and production reliability.

Restraint:

High Initial Implementation and Integration Costs

The substantial upfront expenditure required for deployment and integration can restrict the growth of the AI-Based Process Control Market. Industrial companies may need to purchase advanced software, connected sensors, computing resources, and compatible automation equipment. Integrating these technologies with established production infrastructure can require additional modifications, technical assessments, and system upgrades. Training employees, maintaining platforms, and implementing cybersecurity measures further increase implementation expenses. Smaller manufacturers and organizations operating with limited budgets may find these investments difficult to justify. Moreover, uncertainty regarding the time needed to recover initial costs can delay purchasing decisions and slow the adoption of AI-powered process control technologies.

Opportunity:

Development of Cloud-Based and Edge AI Process Control Solutions

Advancements in cloud computing and edge AI are opening new growth avenues for the AI-Based Process Control Market. Cloud-based systems facilitate centralized analytics, remote supervision, and information sharing between geographically dispersed facilities. Edge computing processes data near industrial equipment, supporting faster responses and reducing dependence on continuous communication with centralized servers. Integrating both approaches can enhance process monitoring, operational flexibility, and system performance. Businesses can also expand their control infrastructure according to changing production needs. As connected industrial environments become more common, solution providers have opportunities to introduce integrated platforms that deliver efficient, responsive, and accessible AI-based process control for different manufacturing operations.

Threat:

Regulatory Uncertainty and Compliance Requirements

Regulatory uncertainty and evolving compliance requirements pose a threat to the AI-Based Process Control Market. Governments and industry authorities are developing rules addressing artificial intelligence, data protection, cybersecurity, and the safe operation of automated systems. Differences between regional regulations can complicate product development, deployment, and international expansion for technology providers. Industrial organizations may need to conduct additional assessments, maintain detailed documentation, and demonstrate that AI-driven decisions meet applicable safety and accountability standards. These obligations can increase compliance expenses and extend implementation timelines. Unclear requirements may also create uncertainty among buyers, potentially delaying investments in AI-based process control solutions across regulated industries.

Covid-19 Impact:

The COVID-19 crisis influenced the AI-Based Process Control Market through initial disruptions and increased demand for industrial digitalization. Factory closures, component shortages, limited workforce availability, and postponed capital expenditure temporarily slowed technology implementation. At the same time, businesses recognized the value of AI-powered automation for maintaining operations with fewer on-site personnel. Remote supervision, predictive analytics, and intelligent process optimization gained importance as manufacturers sought greater flexibility and resilience. The pandemic encouraged companies to reconsider traditional production strategies and invest in advanced control technologies. Following the initial disruption, renewed emphasis on automation, operational efficiency, and smart factory development helped support market growth and future adoption.

The Hardware segment is expected to be the largest during the forecast period

The Hardware segment is expected to account for the largest market share during the forecast period, driven by rising investments in intelligent manufacturing, industrial connectivity, and automated control infrastructure. Essential hardware, such as sensors, industrial controllers, computing equipment, and monitoring devices, enables AI-based systems to collect operational data and regulate production processes. Increasing implementation of smart factories and connected industrial machinery is strengthening demand for these components. Furthermore, the growing need for accurate process supervision, consistent product quality, and efficient equipment performance is encouraging businesses to adopt advanced hardware technologies. These developments are reinforcing the importance of hardware in AI-driven industrial process management.

The Pharmaceuticals and Biotechnology segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the Pharmaceuticals and Biotechnology segment is predicted to witness the highest growth rate, driven by expanding pharmaceutical production, biotechnology advancements, and increasing adoption of intelligent manufacturing systems. AI-powered process control technologies enable companies to regulate critical production parameters, maintain consistent batches, and reduce process variability. Rising demand for biologics, innovative therapies, and vaccines is strengthening the need for advanced monitoring and optimization solutions. Furthermore, strict quality requirements and regulatory compliance obligations are encouraging the implementation of automated technologies. Growing use of machine learning, predictive analysis, and real-time process supervision is expected to improve manufacturing efficiency, enhance product consistency, and support reliable pharmaceutical and biotechnology production.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by its well-developed industrial ecosystem and widespread integration of advanced technologies. The region has a strong network of artificial intelligence developers, automation solution providers, and established industrial operators. Growing expenditure on digital transformation, intelligent manufacturing, and automated process management is encouraging market growth. Companies across energy, chemical processing, pharmaceutical production, electronics, and oil and gas are implementing AI-driven systems to enhance efficiency, maintain consistent quality, and optimize industrial operations. Additionally, technological innovation, research investments, and access to experienced technical personnel contribute to the region's market leadership.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid industrialization, expanding manufacturing capabilities, and increasing investments in artificial intelligence technologies. Countries such as China, India, Japan, and South Korea are strengthening their industrial automation infrastructure and adopting smart manufacturing practices. Growing demand from the electronics, semiconductor, pharmaceutical, chemical, and automotive industries is encouraging the implementation of intelligent process control systems. Government initiatives supporting digital transformation and industrial modernization are further contributing to regional growth. Additionally, increasing investments in connected factories, robotics, and advanced analytics are creating significant opportunities for market expansion.

Key players in the market

Some of the key players in AI-Based Process Control Market include Siemens AG, ABB Ltd., Honeywell International Inc., Emerson Electric Co., Yokogawa Electric Corporation, Rockwell Automation, Inc., Schneider Electric SE, Mitsubishi Electric Corporation, GE Vernova, Valmet Oyj, SUPCON Technology Co., Ltd., HollySys Automation Technologies Ltd., Fuji Electric Co., Ltd., Bosch Rexroth AG, FLSmidth A/S, PiControl Solutions LLC, Mitsubishi Heavy Industries, Ltd. and Endress+Hauser Group

Key Developments:

In July 2026, Rockwell Automation and Augury: Announced a strategic technology and go-to-market partnership integrating Augury's Industrial AI Workforce with Rockwell's Fiix and FactoryTalk technologies.

In May 2026, Emerson and SiMa.ai: Announced a collaboration to deliver physical AI capabilities on Emerson's industrial PCs. The partnership supports real-time industrial data analysis, process and energy optimization, anomaly detection, and predictive maintenance at the industrial edge.

In January 2026, Siemens and NVIDIA Expanded their strategic partnership to build an Industrial AI Operating System, combining NVIDIA's AI infrastructure and simulation technologies with Siemens' industrial automation and software.

Components Covered:

Hardware
Software
Services

Process Control Methods Covered:

AI-Enabled Advanced Process Control
AI-Enabled Model Predictive Control
Adaptive Process Control
AI-Based Closed-Loop Control
Hybrid Model-Based and Data-Driven Control

Deployment Modes Covered:

On-Premises
Cloud-Based
Edge-Based
Hybrid Deployment

Process Types Covered:

Continuous Processes
Batch Processes
Discrete Processes
Hybrid Processes

Enterprise Sizes Covered:

Small and Medium-Sized Enterprises
Large Enterprises

Technologies Covered:

Machine Learning
Deep Learning
Reinforcement Learning
Fuzzy Logic and Neuro-Fuzzy Systems
Expert Systems

Applications Covered:

Process Monitoring and State Estimation
Fault Detection and Diagnosis
Predictive Quality Control
Process Parameter Optimization
Production Yield Optimization
Energy and Resource Optimization
Process Stability and Variability Reduction

End-Use Industries Covered:

Oil and Gas
Chemicals and Petrochemicals
Pharmaceuticals and Biotechnology
Food and Beverages
Energy and Power Generation
Electronics and Semiconductors
Metals and Mining
Pulp and Paper
Water and Wastewater Treatment

Regions Covered:

North America
- United States
- Canada
- Mexico
Europe
- United Kingdom
- Germany
- France
- Italy
- Spain
- Netherlands
- Belgium
- Sweden
- Switzerland
- Poland
- Rest of Europe
Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Thailand
- Malaysia
- Singapore
- Vietnam
- Rest of Asia Pacific
South America
- Brazil
- Argentina
- Colombia
- Chile
- Peru
- Rest of South America
Rest of the World (RoW)
- Middle East
Saudi Arabia
United Arab Emirates
Qatar
Israel
Rest of Middle East
- Africa
South Africa
Egypt
Morocco
Rest of 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 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
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

1 Executive Summary

1.1 Market Snapshot and Key Highlights
1.2 Growth Drivers, Challenges, and Opportunities
1.3 Competitive Landscape Overview
1.4 Strategic Insights and Recommendations

2 Research Framework

2.1 Study Objectives and Scope
2.2 Stakeholder Analysis
2.3 Research Assumptions and Limitations
2.4 Research Methodology
- 2.4.1 Data Collection (Primary and Secondary)
- 2.4.2 Data Modeling and Estimation Techniques
- 2.4.3 Data Validation and Triangulation
- 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

3.1 Market Definition and Structure
3.2 Key Market Drivers
3.3 Market Restraints and Challenges
3.4 Growth Opportunities and Investment Hotspots
3.5 Industry Threats and Risk Assessment
3.6 Technology and Innovation Landscape
3.7 Emerging and High-Growth Markets
3.8 Regulatory and Policy Environment
3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

4.1 Porter's Five Forces Analysis
- 4.1.1 Supplier Bargaining Power
- 4.1.2 Buyer Bargaining Power
- 4.1.3 Threat of Substitutes
- 4.1.4 Threat of New Entrants
- 4.1.5 Competitive Rivalry
4.2 Market Share Analysis of Key Players
4.3 Product Benchmarking and Performance Comparison

5 Global AI-Based Process Control Market, By Component

5.1 Hardware
5.2 Software
5.3 Services

6 Global AI-Based Process Control Market, By Process Control Method

6.1 AI-Enabled Advanced Process Control
6.2 AI-Enabled Model Predictive Control
6.3 Adaptive Process Control
6.4 AI-Based Closed-Loop Control
6.5 Hybrid Model-Based and Data-Driven Control

7 Global AI-Based Process Control Market, By Deployment Mode

7.1 On-Premises
7.2 Cloud-Based
7.3 Edge-Based
7.4 Hybrid Deployment

8 Global AI-Based Process Control Market, By Process Type

8.1 Continuous Processes
8.2 Batch Processes
8.3 Discrete Processes
8.4 Hybrid Processes

9 Global AI-Based Process Control Market, By Enterprise Size

9.1 Small and Medium-Sized Enterprises
9.2 Large Enterprises

10 Global AI-Based Process Control Market, By AI Technology

10.1 Machine Learning
10.2 Deep Learning
10.3 Reinforcement Learning
10.4 Fuzzy Logic and Neuro-Fuzzy Systems
10.5 Expert Systems

11 Global AI-Based Process Control Market, By Application

11.1 Process Monitoring and State Estimation
11.2 Fault Detection and Diagnosis
11.3 Predictive Quality Control
11.4 Process Parameter Optimization
11.5 Production Yield Optimization
11.6 Energy and Resource Optimization
11.7 Process Stability and Variability Reduction

12 Global AI-Based Process Control Market, By End-Use Industry

12.1 Oil and Gas
12.2 Chemicals and Petrochemicals
12.3 Pharmaceuticals and Biotechnology
12.4 Food and Beverages
12.5 Energy and Power Generation
12.6 Electronics and Semiconductors
12.7 Metals and Mining
12.8 Pulp and Paper
12.9 Water and Wastewater Treatment

13 Global AI-Based Process Control Market, By Geography

13.1 North America
- 13.1.1 United States
- 13.1.2 Canada
- 13.1.3 Mexico
13.2 Europe
- 13.2.1 United Kingdom
- 13.2.2 Germany
- 13.2.3 France
- 13.2.4 Italy
- 13.2.5 Spain
- 13.2.6 Netherlands
- 13.2.7 Belgium
- 13.2.8 Sweden
- 13.2.9 Switzerland
- 13.2.10 Poland
- 13.2.11 Rest of Europe
13.3 Asia Pacific
- 13.3.1 China
- 13.3.2 Japan
- 13.3.3 India
- 13.3.4 South Korea
- 13.3.5 Australia
- 13.3.6 Indonesia
- 13.3.7 Thailand
- 13.3.8 Malaysia
- 13.3.9 Singapore
- 13.3.10 Vietnam
- 13.3.11 Rest of Asia Pacific
13.4 South America
- 13.4.1 Brazil
- 13.4.2 Argentina
- 13.4.3 Colombia
- 13.4.4 Chile
- 13.4.5 Peru
- 13.4.6 Rest of South America
13.5 Rest of the World (RoW)
- 13.5.1 Middle East
  - 13.5.1.1 Saudi Arabia
  - 13.5.1.2 United Arab Emirates
  - 13.5.1.3 Qatar
  - 13.5.1.4 Israel
  - 13.5.1.5 Rest of Middle East
- 13.5.2 Africa
  - 13.5.2.1 South Africa
  - 13.5.2.2 Egypt
  - 13.5.2.3 Morocco
  - 13.5.2.4 Rest of Africa

14 Strategic Market Intelligence

14.1 Industry Value Network and Supply Chain Assessment
14.2 White-Space and Opportunity Mapping
14.3 Product Evolution and Market Life Cycle Analysis
14.4 Channel, Distributor, and Go-to-Market Assessment

15 Industry Developments and Strategic Initiatives

15.1 Mergers and Acquisitions
15.2 Partnerships, Alliances, and Joint Ventures
15.3 New Product Launches and Certifications
15.4 Capacity Expansion and Investments
15.5 Other Strategic Initiatives

16 Company Profiles

16.1 Siemens AG
16.2 ABB Ltd.
16.3 Honeywell International Inc.
16.4 Emerson Electric Co.
16.5 Yokogawa Electric Corporation
16.6 Rockwell Automation, Inc.
16.7 Schneider Electric SE
16.8 Mitsubishi Electric Corporation
16.9 GE Vernova
16.10 Valmet Oyj
16.11 SUPCON Technology Co., Ltd.
16.12 HollySys Automation Technologies Ltd.
16.13 Fuji Electric Co., Ltd.
16.14 Bosch Rexroth AG
16.15 FLSmidth A/S
16.16 PiControl Solutions LLC
16.17 Mitsubishi Heavy Industries, Ltd.
16.18 Endress+Hauser Group

簡介目錄圖表

List of Tables

Table 1 Global AI-Based Process Control Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global AI-Based Process Control Market Outlook, By Component (2023-2034) ($MN)
Table 3 Global AI-Based Process Control Market Outlook, By Hardware (2023-2034) ($MN)
Table 4 Global AI-Based Process Control Market Outlook, By Software (2023-2034) ($MN)
Table 5 Global AI-Based Process Control Market Outlook, By Services (2023-2034) ($MN)
Table 6 Global AI-Based Process Control Market Outlook, By Process Control Method (2023-2034) ($MN)
Table 7 Global AI-Based Process Control Market Outlook, By AI-Enabled Advanced Process Control (2023-2034) ($MN)
Table 8 Global AI-Based Process Control Market Outlook, By AI-Enabled Model Predictive Control (2023-2034) ($MN)
Table 9 Global AI-Based Process Control Market Outlook, By Adaptive Process Control (2023-2034) ($MN)
Table 10 Global AI-Based Process Control Market Outlook, By AI-Based Closed-Loop Control (2023-2034) ($MN)
Table 11 Global AI-Based Process Control Market Outlook, By Hybrid Model-Based and Data-Driven Control (2023-2034) ($MN)
Table 12 Global AI-Based Process Control Market Outlook, By Deployment Mode (2023-2034) ($MN)
Table 13 Global AI-Based Process Control Market Outlook, By On-Premises (2023-2034) ($MN)
Table 14 Global AI-Based Process Control Market Outlook, By Cloud-Based (2023-2034) ($MN)
Table 15 Global AI-Based Process Control Market Outlook, By Edge-Based (2023-2034) ($MN)
Table 16 Global AI-Based Process Control Market Outlook, By Hybrid Deployment (2023-2034) ($MN)
Table 17 Global AI-Based Process Control Market Outlook, By Process Type (2023-2034) ($MN)
Table 18 Global AI-Based Process Control Market Outlook, By Continuous Processes (2023-2034) ($MN)
Table 19 Global AI-Based Process Control Market Outlook, By Batch Processes (2023-2034) ($MN)
Table 20 Global AI-Based Process Control Market Outlook, By Discrete Processes (2023-2034) ($MN)
Table 21 Global AI-Based Process Control Market Outlook, By Hybrid Processes (2023-2034) ($MN)
Table 22 Global AI-Based Process Control Market Outlook, By Enterprise Size (2023-2034) ($MN)
Table 23 Global AI-Based Process Control Market Outlook, By Small and Medium-Sized Enterprises (2023-2034) ($MN)
Table 24 Global AI-Based Process Control Market Outlook, By Large Enterprises (2023-2034) ($MN)
Table 25 Global AI-Based Process Control Market Outlook, By AI Technology (2023-2034) ($MN)
Table 26 Global AI-Based Process Control Market Outlook, By Machine Learning (2023-2034) ($MN)
Table 27 Global AI-Based Process Control Market Outlook, By Deep Learning (2023-2034) ($MN)
Table 28 Global AI-Based Process Control Market Outlook, By Reinforcement Learning (2023-2034) ($MN)
Table 29 Global AI-Based Process Control Market Outlook, By Fuzzy Logic and Neuro-Fuzzy Systems (2023-2034) ($MN)
Table 30 Global AI-Based Process Control Market Outlook, By Expert Systems (2023-2034) ($MN)
Table 31 Global AI-Based Process Control Market Outlook, By Application (2023-2034) ($MN)
Table 32 Global AI-Based Process Control Market Outlook, By End-Use Industry (2023-2034) ($MN)
Table 33 Global AI-Based Process Control Market Outlook, By Oil and Gas (2023-2034) ($MN)
Table 34 Global AI-Based Process Control Market Outlook, By Chemicals and Petrochemicals (2023-2034) ($MN)
Table 35 Global AI-Based Process Control Market Outlook, By Pharmaceuticals and Biotechnology (2023-2034) ($MN)
Table 36 Global AI-Based Process Control Market Outlook, By Food and Beverages (2023-2034) ($MN)
Table 37 Global AI-Based Process Control Market Outlook, By Energy and Power Generation (2023-2034) ($MN)
Table 38 Global AI-Based Process Control Market Outlook, By Electronics and Semiconductors (2023-2034) ($MN)
Table 39 Global AI-Based Process Control Market Outlook, By Metals and Mining (2023-2034) ($MN)
Table 40 Global AI-Based Process Control Market Outlook, By Pulp and Paper (2023-2034) ($MN)
Table 41 Global AI-Based Process Control Market Outlook, By Water and Wastewater Treatment (2023-2034) ($MN)