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自動化

市場調查報告書

商品編碼

1892094

流程自動化的未來，2025年

The Future of Process Automation, 2025

出版日期: 2025年10月17日 | 出版商:

Frost & Sullivan | 英文 36 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

共生智慧和自動駕駛將引領流程產業的變革性成長。

本研究檢驗了製程自動化市場的未來，並分析了流程工業和混合工業中從傳統硬體中心系統向軟體定義、人工智慧驅動的自主運作的轉型。研究採用ISA-95技術層分類法，評估了石油天然氣、化學、製藥和連續加工產業的市場演變和競爭動態。

透過全面的供應商分析，識別出下一代自動化架構的競爭性策略願景，並揭示了三大關鍵成長機會：人工智慧驅動的自主最佳化平台、邊緣人工智慧預測性維護生態系統以及開放式自動化整合平台。顛覆性技術、創新經營模式和日益激烈的競爭等策略挑戰從根本上重塑傳統的自動化範式。

分析表明，勞動力挑戰、營運複雜性、網路安全威脅和監管合規要求推動流程工業架構向共生智慧和自主運行方向演進。主要調查結果包括：現場級高階控制系統和跨層平台技術具有最大的成長潛力，而智慧營運管理則面臨巨大的實施障礙。

這項研究深入分析了推動流程自動化轉變為軟體定義自主營運框架的技術和市場促進因素。

報告摘要：流程自動化市場，2024-2032年

全球過程自動化市場在2024年達到481.3億美元，到2032年將達到1,842.9億美元，2024年至2032年的年複合成長率（CAGR）為18.3%。該市場涵蓋工業人工智慧、自主運作、數位雙胞胎和預測性維護解決方案，推動智慧化、自最佳化和互聯化工業系統邁入新時代。軟體定義自動化、即時人工智慧驅動運作和先進數位雙胞胎的應用將幫助流程工業提高效率、安全性和營運韌性。

關鍵市場趨勢與洞察

自動化工程師嚴重短缺和勞動力老化推動對自動駕駛的需求，減少人為干預並擴大專業能力。
人工智慧驅動的自動化和邊緣運算能夠實現即時流程最佳化、預測性維護和自我修復操作。
受各行業向模組化、廠商中立平台轉變的推動，軟體定義自動化市場預計將以超過 15%的年複合成長率成長。
數位雙胞胎解決方案正擴大用於模擬和管理複雜操作，提高資產可見度和生命週期管理能力。
預測性維護的採用率持續成長，有助於最大限度地減少停機時間並延長資產壽命。

市場規模及預測

2024年市場規模：481.3億美元
2032年預測市場規模：1,842.9億美元
2024-2032年年複合成長率：18.3%
在預測期內，增強型現場控制（人工智慧賦能）將成為規模最大、成長最快的細分市場。

市場概覽 - 流程自動化市場，2024-2032年

在全球範圍內，工業自動化、工業人工智慧和數位雙胞胎市場融合，重新定義著各行業的競爭力和效率。流程自動化產業正從人工監控系統轉型為由人工智慧決策引擎和邊緣連接主導的整合式智慧營運。

影響自動駕駛市場的關鍵結構性變化包括：

採用軟體定義控制系統來實現分散式智慧
擴展人工智慧驅動的預測性維護策略，以預測設備故障。
透過模擬即時工廠性能的數位雙胞胎生態系統，實現平台化發展。
轉變企業文化，使人類和人工智慧能夠無縫協作。

工業4.0推動自動化從被動回應向自學習、自主工作流程轉型，減少對人的依賴，並彌合技能短缺造成的創新鴻溝。Emerson、Honeywell、Siemens、Yokogawa等領先的自動化公司正主導著向「自主設計」的轉型，將開放式架構、零信任網路安全和可擴展資料模型相結合。

這些變化與工業人工智慧市場的全球大趨勢相符。人工智慧驅動的分析引擎如今已成為大多數製程控制系統的基礎。加之預測性維護市場的進步，工業企業正朝著「始終運作」的營運模式發展，將停機時間減少高達30%。

這項轉型將形成一個「自動化三角」，將人工智慧、數位雙胞胎平台和自主控制系統結合在一起，構成未來工業價值鏈的核心基礎設施。

市場規模與收入預測 - 過程自動化市場，2024-2032年

預計製程自動化市場將從2024年的481.3億美元成長到2032年的1,842.9億美元，年複合成長率高達18.3%。在這個生態系統中，工業人工智慧市場和自動駕駛市場等相關產業快速擴張，形成協同成長動力。

增強型現場控制與嵌入式人工智慧是工業數位化發展的核心引擎，它使工廠能夠演進為完全自主的系統。數位雙胞胎技術的整合提升了可視性和預測性控制能力，而跨層軟體平台則實現了現場、邊緣和企業系統的近即時統一。

預測性維護市場也促進了這一擴張，基於人工智慧的監控和故障建模成為現代製程控制框架的核心能力。

分析範圍 - 流程自動化市場，2024-2032年

弗若斯特沙利文的這項研究以流程自動化、工業人工智慧和自主營運市場的交集為中心，分析了這三個市場將對全球製造業、能源和化學產業產生的綜合影響。

產業：石油天然氣、發電、化工、製藥、採礦
技術領域：數位雙胞胎平台、人工智慧分析、預測性維護軟體。
自動化等級：ISA-95 層涵蓋現場控制、智慧操作、企業智慧和跨層連接。

預測期為2023年至2032年，收入以美元計，依製造商層級計算。本分析不包括機器人和業務流程自動化，而是致力於人工智慧驅動的操作技術，這些技術能夠提升工業環境中的即時控制、安全性和可靠性。

細分市場分析 - 流程自動化市場，2024-2032年

市場區隔反映了傳統自動化和工業人工智慧市場的整合：

增強型現場控制（人工智慧層）：到2032年，該細分市場將佔 56%的市場佔有率，它將整合人工智慧感測器、智慧致動器和機器人技術，以建立邊緣級自主單元。
智慧營運：利用機器學習驅動的先進製程控制功能最佳化製造營運。此細分市場成長穩健，是預測性維護市場的基礎，它將維護預測與工廠流程最佳化結合。
企業智慧（數位雙胞胎層）：數位雙胞胎市場是企業數位化的基礎，透過基於模擬的決策環境提供跨設施洞察和資產生命週期最佳化。
跨層技術（AI + 邊緣）：一個快速成長的領域，可實現 AI 驅動的分析、網路彈性和雲端原生架構。

這些細分領域共同代表了工業運作各層向智慧自主網路的技術融合。這些技術的融合在人工智慧預測、數位模擬和流程執行之間建構了一個共生生態系統，構成了自主營運市場的基礎。

成長要素- 流程自動化市場，2024-2032年

自動化工程師嚴重短缺（預計未來十年將超過200萬）以及老齡化勞動力即將退休，加速對自主系統的需求，這些系統可以增強剩餘的專業知識，同時減少對人工干預的需求。
營運成本、能源支出和競爭壓力不斷上升，即時需要人工智慧驅動的自動化技術來即時最佳化流程並減少浪費。
人工智慧代理和邊緣運算的成熟將使工廠車間能夠進行即時自主決策，消除雲端延遲，同時實現傳統系統無法實現的預測性維護和自我最佳化能力。
受企業對獨立於供應商、模組化、硬體無關且可快速部署和更新的解決方案的需求所推動，全球軟體定義自動化市場預計將從2024年到2032年實現超過 15%的年複合成長率。

成長限制因素 - 流程自動化市場，2024-2032年

人工智慧平台、邊緣基礎設施和系統整合的高昂前期成本構成了財務障礙，尤其對於中小企業而言；同時，投資回收期的不確定性和複雜的投資回報率（ROI）計算也可能使經營團隊難以做出正確的決定。
超過 50%的流程工業客戶依賴幾十年前的DCS/SCADA 系統，這些系統使用專有通訊協定，與現代 AI 和軟體定義解決方案不相容，需要昂貴的維修或複雜的整合方法。
近 50%的流程工業客戶面臨資料分散、系統不連通、資料品質不佳、感測器測量資料缺失等問題，這阻礙了人工智慧模型的訓練，並妨礙了自主解決方案的有效部署。
由於數位化連接，工業系統的攻擊面不斷擴大，而缺乏現代安全功能則會帶來安全風險，這使得各組織對可能受到攻擊的自動駕駛系統保持警惕。
許多行業從業人員對人工智慧系統持謹慎態度，擔心它們會取代他們的工作而不是幫助他們，而且抵制數位轉型的組織文化即使技術可用，也會造成採用障礙。

競爭格局 - 流程自動化市場，2024-2032年

自動駕駛市場的競爭特徵是主要企業和大型控制系統供應商之間快速的技術創新。

Frost & Sullivan已確定以下主要參與者：

Emerson - 透過「Project Beyond」，該公司將把其控制系統與 AspenTech 的人工智慧層整合，以實現自我最佳化自動化。
Siemens AG - 憑藉其 Xcelerator 平台引領數位雙胞胎市場，該平台整合了 AI Copilot，用於模型驅動的操作。
Schneider Electric - 開發 EcoStruxure Automation Expert，這將實現與供應商無關的即插即用架構。
Honeywell - 將預測性維護市場洞察融入其「Forge Autonomous Operations」。
Yokogawa - 擴展 OpreX IA2IA 架構，整合機器人和開放平台，以實現資料驅動的流程自主性。
AspenTech 與ExxonMobil合作，推動開放自動化標準和石油與天然氣產業自主化計畫。

這些公司正朝著統一的願景邁進，即採用軟體定義、雲端原生技術來建構自主的工業生態系統。它們的策略方向強調模組化人工智慧平台、開放原始碼協作和基於SaaS的預測控制，推動工業人工智慧、數位雙胞胎和預測性維護領域的市場整合。

常見問題：

1.預計到2032年，製程自動化產業的市場規模將達到多少？
- 預計製程自動化市場將從2024年的481.3億美元成長到2032年的1,842.9億美元，年複合成長率為 18.3%。
2.工業人工智慧將如何為製程自動化的未來做出貢獻？
- 工業人工智慧能夠實現即時自主決策、預測性維護和自我最佳化，顯著提高營運效率。
3.數位雙胞胎在工業運作中扮演什麼角色？
- 數位雙胞胎創建實體資產的虛擬副本，並提供持續的模擬和分析，以改善資產生命週期管理和流程最佳化。
4.自動化操作需求不斷成長的原因是什麼？
- 透過人工智慧和邊緣運算，自動駕駛減少了對人為干預的依賴，有助於緩解勞動力短缺並提高營運韌性。
5.預測性維護如何影響生產效率？
- 預測性維護市場利用人工智慧和物聯網來預測設備故障、最大限度地減少停機時間並降低維護成本。
6.流程自動化市場面臨哪些挑戰？
- 挑戰包括前期成本高、難以與舊有系統整合、資料碎片化、網路安全風險以及對數位轉型的抵制。
7.哪些產業最積極採用流程自動化技術？
- 重點產業包括石油天然氣、化學、製藥、發電和採礦。
8.哪些技術趨勢將推動軟體定義自動化的發展？
- 模組化、與供應商無關的平台，無需依賴硬體即可快速部署和更新，這是關鍵促進因素。
9.市場領導如何脫穎而出？
- Emerson、Siemens、Schneider Electric和Honeywell等公司正致力於人工智慧平台、數位雙胞胎和可擴展的雲端邊緣架構。
10.邊緣運算對流程自動化意味著什麼？
- 邊緣運算能夠實現低延遲的本地人工智慧決策，提高工廠車間的反應速度和自主性。

This study examines the future of the process automation market, analyzing the shift from traditional hardware-centric systems to software-defined, AI-driven autonomous operations within process and hybrid industries. The research employs ISA-95 technology layer segmentation to assess market evolution and competitive dynamics across oil & gas, chemicals, pharmaceuticals, and continuous process sectors.

Through comprehensive vendor analysis, the study identifies competing strategic visions for next-generation automation architectures, revealing three critical growth opportunities: AI-driven autonomous optimization platforms, edge AI predictive maintenance ecosystems, and open automation integration platforms. Strategic imperatives, including disruptive technologies, innovative business models, and competitive intensity, fundamentally reshape traditional automation paradigms.

The analysis demonstrates process industries' architectural evolution toward symbiotic intelligence and autonomous operations, driven by workforce challenges, operational complexity, cybersecurity threats, and regulatory compliance demands. Key findings indicate that field-level enhanced control systems and cross-layer platform technologies represent the highest growth potential, while intelligent operations management faces significant implementation barriers.

This research provides insights into the technological and market forces transforming process automation toward software-defined, autonomous operational frameworks.

Report Summary: Process Automation Market, 2024-2032

The global process automation market was valued at USD 48.13 billion in 2024 and is projected to reach USD 184.29 billion by 2032, growing at a CAGR of 18.3% from 2024 to 2032. This market spans Industrial AI, Autonomous Operations, Digital Twin, and Predictive Maintenance solutions, driving a new era of intelligent, self-optimizing, and connected industrial systems. The adoption of software-defined automation, real-time AI-driven operations, and advanced digital twins positions process industries for enhanced efficiency, safety, and operational resilience.

Key Market Trends & Insights

The acute shortage of automation engineers and an aging workforce are accelerating demand for autonomous operations, reducing human intervention and amplifying expert capabilities.
AI-driven automation and edge computing are enabling real-time process optimization, predictive maintenance, and self-healing operations.
The software-defined automation market is expected to exceed 15% CAGR, with strong industry movement toward modular, vendor-agnostic platforms.
Digital Twin solutions are increasingly used to simulate and manage complex operations, providing enhanced asset visibility and lifecycle management.
Predictive Maintenance adoption continues to rise, minimizing downtime and supporting asset longevity.

Market Size & Forecast

2024 Market Size: USD 48.13 Billion
Projected 2032 Market Size: USD 184.29 Billion
CAGR (2024-2032): 18.3%
Enhanced Field Control (AI-enabled) is the largest and fastest-growing segment in the forecast period.

Market Overview - Process Automation Market, 2024-2032

Globally, the convergence of the industrial automation, Industrial AI, and Digital Twin markets is redefining competitiveness and efficiency across sectors. The process automation industry is transitioning from manual monitoring systems to integrated, intelligent operations led by AI-based decision engines and edge connectivity.

Key structural changes influencing the Autonomous Operations market include:

Adoption of software-defined control systems enabling decentralized intelligence.
Expansion of AI-powered predictive maintenance strategies that anticipate equipment failures.
Platformization through Digital Twin ecosystems that simulate real-time plant performance.
A cultural transformation across enterprises as humans and AI collaborate seamlessly.

Industry 4.0 is driving automation from reactive to self-learning, autonomous workflows, reducing manual dependency and closing the innovation gap caused by skill shortages. Major automation players such as Emerson, Honeywell, Siemens, and Yokogawa lead the shift toward ""autonomy by design,"" combining open architecture, zero-trust cybersecurity, and scalable data models.

These changes synchronize with global megatrends in the Industrial AI market, where AI-driven analytics engines now underpin most process control systems. Paired with advancements in the Predictive Maintenance market, industrial companies are moving toward ""always-on"" operations that lower downtime by up to 30%.

This transformation creates a cohesive ""Automation Triangle""-with AI, Digital Twin infrastructure, and autonomous control systems forming the core infrastructure of tomorrow's industrial value chain.

Market Size and Revenue Forecast - Process Automation Market, 2024-2032

The process automation market is forecasted to grow from USD 48.13 billion in 2024 to USD 184.29 billion by 2032, recording an exceptional CAGR of 18.3%. Within this ecosystem, adjacent industries such as the Industrial AI market and Autonomous Operations market are expanding rapidly, providing synergistic growth momentum.

Enhanced Field Control-powered by embedded AI-is the growth engine of industrial digitization, enabling factories to evolve toward fully autonomous setups. The integration of Digital Twin technologies drives visibility and predictive control, while cross-layer software platforms unify field, edge, and enterprise systems in near real time.

The Predictive Maintenance market complements this expansion, as AI-based monitoring and failure modeling become core functions of modern process control frameworks.

Scope of Analysis - Process Automation Market, 2024-2032

This Frost & Sullivan study centers on the intersection of the process automation market, Industrial AI market, and Autonomous Operations market, analyzing their collective impact on global manufacturing, energy, and chemical sectors. The scope covers:

Industrial Verticals: Oil & gas, power generation, chemicals, pharmaceuticals, and mining.
Technological Segments: Digital Twin platforms, AI analytics, and predictive maintenance software.
Automation Levels: ISA-95 layers covering field control, intelligent operations, enterprise intelligence, and cross-layer connectivity.

The forecast period runs through 2023-2032, with revenue measured in US dollars at the manufacturer level. The analysis excludes robotic and business process automation and focuses on AI-driven operational technologies that enhance real-time control, safety, and reliability in industrial settings.

Segmentation Analysis - Process Automation Market, 2024-2032

The market's segmentation mirrors the integration between traditional automation and the Industrial AI market:

Enhanced Field Control (AI Layer): This segment represents 56% of the 2032 market share, integrating AI sensors, smart actuators, and robotics to create edge-level autonomous units.
Intelligent Operations: Advanced process control capabilities powered by machine learning optimize manufacturing sequences. While showing moderate growth, this layer remains foundational to the Predictive Maintenance market, integrating maintenance prediction and plant process optimization.
Enterprise Intelligence (Digital Twin Layer): The Digital Twin market underpins enterprise digitalization, providing cross-facility insights and lifecycle optimization of assets through simulation-based decision environments.
Cross-Layer Technologies (AI + Edge): A fast-growing segment enabling AI-driven analytics, cyber resilience, and cloud-native architecture.

Collectively, these segments signify the technological merging of industrial operational layers into an intelligent autonomy network. The integration of these technologies is creating a symbiotic ecosystem between AI prediction, digital simulation, and process execution-forming the backbone of the Autonomous Operations market.

Growth Drivers - Process Automation Market, 2024-2032

An acute shortage of automation engineers (over 2 million expected over the next 10 years) and the aging workforce's impending retirement are accelerating demand for autonomous systems that reduce human intervention requirements while amplifying the remaining expert capabilities.
Rising operational costs, energy expenses, and competitive pressures drive immediate demand for AI-driven automation that can optimize processes in real time and reduce waste.
The maturation of AI agents and edge computing enables real-time autonomous decision-making directly at production sites, eliminating cloud latency while enabling predictive maintenance and self-optimization capabilities that traditional systems cannot deliver.
The global software-defined automation market is expected to record over 15% compound annual growth rate (CAGR) between 2024 and 2032, driven by organizations seeking vendor-agnostic, modular solutions that enable rapid deployment and updates without hardware dependencies.

Growth Restraints - Process Automation Market, 2024-2032

High upfront costs for AI platforms, edge infrastructure, and system integration create financial barriers, especially for small and medium-sized enterprises, while uncertain return timelines and complex return-on-investment calculations make justification difficult for executives.
More than 50% of process industry customers depend on decades-old DCS/SCADA systems with proprietary protocols that are incompatible with modern AI and software-defined solutions, requiring costly overhauls or complex integration approaches.
Nearly 50% of process industry customers face data fragmentation across disconnected systems, poor data quality, and missing sensor readings that break AI model training, preventing effective deployment of autonomous solutions.
Industrial systems face expanding attack surfaces due to digital connectivity, while lacking modern security features, creating safety risks that make organizations cautious about autonomous operations that could be compromised.
Most industrial workers are wary of AI systems, fearing job displacement rather than augmentation, while organizational cultures resist digital transformation, creating implementation barriers even when the technology is available.

Competitive Landscape - Process Automation Market, 2024-2032

Competition in the Autonomous Operations market is defined by rapid innovation among industrial AI champions and leading control system providers.

Frost & Sullivan identifies the following key participants:

Emerson - Through Project Beyond, merging its control systems with AspenTech's AI layer for self-optimizing automation.
Siemens AG - Driving the Digital Twin market via the Xcelerator platform integrating AI copilots for model-driven operations.
Schneider Electric - Developing EcoStruxure Automation Expert, enabling vendor-agnostic, plug-and-produce architectures.
Honeywell - Integrating predictive maintenance market insights within the Forge Autonomous Operations environment.
Yokogawa - Expanding its OpreX IA2IA architecture, connecting robotics and open platforms for data-driven process autonomy.
AspenTech & ExxonMobil - Collaborating to advance open automation standards and oil & gas autonomy programs.

These players are converging on a unified vision-software-defined, cloud-native technologies that enable autonomous industrial ecosystems. Their strategic direction emphasizes modular AI platforms, open-source collaboration, and SaaS-based predictive control, driving market consolidation across the Industrial AI, Digital Twin, and Predictive Maintenance segments.

FAQ:

1. What is the projected market size for the process automation industry by 2032?
- The process automation market is expected to grow from USD 48.13 billion in 2024 to USD 184.29 billion by 2032, representing an 18.3% CAGR.
2. How does Industrial AI contribute to the future of process automation?
- Industrial AI enables real-time autonomous decision-making, predictive maintenance, and self-optimization, significantly enhancing operational efficiency.
3. What role do Digital Twins play in industrial operations?
- Digital Twins create virtual replicas of physical assets, providing continuous simulation and analytics that improve asset lifecycle management and process optimization.
4. Why is there a growing demand for Autonomous Operations?
- Autonomous Operations reduce reliance on manual interventions through AI and edge computing, helping to address workforce shortages and improve operational resilience.
5. How does Predictive Maintenance impact manufacturing efficiency?
- Predictive Maintenance markets leverage AI and IoT to foresee equipment failures, minimizing downtime and reducing maintenance costs.
6. What challenges does the process automation market face?
- Challenges include high upfront costs, legacy system integration difficulties, data fragmentation, cybersecurity risks, and resistance to digital transformation.
7. Which industries are most actively adopting process automation technologies?
- Key sectors include oil & gas, chemicals, pharmaceuticals, power generation, and mining.
8. What technological trends are driving software-defined automation growth?
- Modular, vendor-agnostic platforms supporting rapid deployment and updates without hardware dependency are key enablers.
9. How are market leaders differentiating themselves?
- Companies like Emerson, Siemens, Schneider Electric, and Honeywell focus on AI-enabled platforms, digital twins, and scalable cloud-edge architectures.
10. What is the significance of edge computing in process automation?
- Edge computing facilitates low-latency, localized AI-based decision-making, enhancing responsiveness and operational autonomy at production sites.

Strategic Imperatives

Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on the Future of Process Automation Market