查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1892094

2025 年流程自动化的未来

The Future of Process Automation, 2025
出版日期: | 出版商: Frost & Sullivan | 英文 36 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

共生智慧和自动驾驶将引领流程产业的变革性成长。

本研究检验了製程自动化市场的未来，并分析了流程工业和混合工业中从传统硬体中心系统向软体定义、人工智慧驱动的自主运作的转型。研究采用ISA-95技术层分类法，评估了石油天然气、化学、製药和连续加工产业的市场演变和竞争动态。

透过全面的供应商分析，我们识别出下一代自动化架构的竞争性策略愿景，并揭示了三大关键成长机会：人工智慧驱动的自主优化平台、边缘人工智慧预测性维护生态系统以及开放式自动化整合平台。颠覆性技术、创新经营模式和日益激烈的竞争等策略挑战正在从根本上重塑传统的自动化范式。

分析表明，劳动力挑战、营运复杂性、网路安全威胁和监管合规要求正在推动流程工业架构向共生智慧和自主运行方向演进。主要发现包括：现场级高阶控制系统和跨层平台技术具有最大的成长潜力，而智慧营运管理则面临巨大的实施障碍。

这项研究深入分析了推动流程自动化转变为软体定义自主营运框架的技术和市场驱动因素。

报告摘要：流程自动化市场，2024-2032年

全球过程自动化市场预计在2024年达到481.3亿美元，到2032年将达到1,842.9亿美元，2024年至2032年的复合年增长率（CAGR）为18.3%。该市场涵盖工业人工智慧、自主运作、数位双胞胎和预测性维护解决方案，推动智慧化、自优化和互联化工业系统迈入新时代。软体定义自动化、即时人工智慧驱动运作和先进数位双胞胎的应用将帮助流程工业提高效率、安全性和营运韧性。

关键市场趋势与洞察

  • 自动化工程师严重短缺和劳动力老化正在推动对自动驾驶的需求，从而减少人为干预并扩大专业能力。
  • 人工智慧驱动的自动化和边缘运算能够实现即时流程优化、预测性维护和自我修復操作。
  • 受各行业向模组化、厂商中立平台转变的推动，软体定义自动化市场预计将以超过 15% 的复合年增长率成长。
  • 数位双胞胎解决方案正越来越多地用于模拟和管理复杂操作，从而提高资产可见度和生命週期管理能力。
  • 预测性维护的采用率持续成长，有助于最大限度地减少停机时间并延长资产寿命。

市场规模及预测

  • 2024年市场规模：481.3亿美元
  • 预计2032年市场规模：1,842.9亿美元
  • 2024-2032年复合年增长率：18.3%
  • 在预测期内，增强型现场控制（人工智慧赋能）将成为规模最大、成长最快的细分市场。

市场概览 - 流程自动化市场，2024-2032 年

在全球范围内，工业自动化、工业人工智慧和数数位双胞胎市场正在融合，重新定义着各行业的竞争力和效率。流程自动化产业正从人工监控系统转型为由人工智慧决策引擎和边缘连接主导的整合式智慧营运。

影响自动驾驶市场的关键结构性变化包括：

  • 采用软体定义控制系统来实现分散式智能
  • 扩展人工智慧驱动的预测性维护策略，以预测设备故障。
  • 透过模拟即时工厂性能的数位双胞胎生态系统，实现平台化发展。
  • 转变企业文化，使人类和人工智慧能够无缝协作。

工业4.0正在推动自动化从被动回应向自学习、自主工作流程转型，从而减少对人的依赖，并弥合技能短缺造成的创新鸿沟。艾默生、Honeywell、西门子和横河电机等领先的自动化公司正主导着向「自主设计」的转型，将开放式架构、零信任网路安全和可扩展资料模型相结合。

这些变化与工业人工智慧市场的全球大趋势相符。人工智慧驱动的分析引擎如今已成为大多数製程控制系统的基础。加之预测性维护市场的进步，工业企业正朝着「始终运作」的营运模式发展，将停机时间减少高达30%。

这项转型将形成一个“自动化三角”，将人工智慧、数位双胞胎平台和自主控制系统结合在一起，构成未来工业价值链的核心基础设施。

市场规模与收入预测 - 过程自动化市场，2024-2032 年

预计製程自动化市场将从2024年的481.3亿美元成长到2032年的1,842.9亿美元，复合年增长率高达18.3%。在这个生态系统中，工业人工智慧市场和自动驾驶市场等相关产业正在快速扩张，从而形成协同成长势头。

增强型现场控制与嵌入式人工智慧是工业数位化发展的核心引擎，它使工厂能够演进为完全自主的系统。数位双胞胎技术的整合提升了可视性和预测性控制能力，而跨层软体平台则实现了现场、边缘和企业系统的近实时统一。

预测性维护市场也促进了这一扩张，基于人工智慧的监控和故障建模成为现代製程控制框架的核心能力。

分析范围－流程自动化市场，2024-2032年

弗若斯特沙利文的这项研究以流程自动化、工业人工智慧和自主营运市场的交集为中心，分析了这三个市场将对全球製造业、能源和化学产业产生的综合影响。

  • 产业：石油天然气、发电、化工、製药、采矿
  • 技术领域：数位双胞胎平台、人工智慧分析、预测性维护软体。
  • 自动化等级：ISA-95 层涵盖现场控制、智慧操作、企业智慧和跨层连接。

预测期为2023年至2032年，收入以美元计，依製造商层级计算。本分析不包括机器人和业务流程自动化，而是专注于人工智慧驱动的操作技术，这些技术能够提升工业环境中的即时控制、安全性和可靠性。

细分市场分析 - 流程自动化市场，2024-2032 年

市场区隔反映了传统自动化和工业人工智慧市场的整合：

  • 增强型现场控制（人工智慧层）：到 2032 年，该细分市场将占 56% 的市场份额，它将整合人工智慧感测器、智慧致动器和机器人技术，以建立边缘级自主单元。
  • 智慧营运：利用机器学习驱动的先进製程控制功能优化製造营运。此细分市场成长稳健，是预测性维护市场的基础，它将维护预测与工厂流程最佳化结合。
  • 企业智慧（数位双胞胎层）：数位双胞胎市场是企业数位化的基础，透过基于模拟的决策环境提供跨设施洞察和资产生命週期最佳化。
  • 跨层技术（AI + 边缘）：一个快速成长的领域，可实现 AI 驱动的分析、网路弹性和云端原生架构。

这些细分领域共同代表了工业运作各层向智慧自主网路的技术融合。这些技术的融合在人工智慧预测、数位模拟和流程执行之间建构了一个共生生态系统，构成了自主营运市场的基础。

成长要素- 流程自动化市场，2024-2032 年

  • 自动化工程师严重短缺（预计未来十年将超过 200 万）以及老龄化劳动力即将退休，正在加速对自主系统的需求，这些系统可以增强剩余的专业知识，同时减少对人工干预的需求。
  • 营运成本、能源支出和竞争压力不断上升，即时需要人工智慧驱动的自动化技术来即时优化流程并减少浪费。
  • 人工智慧代理和边缘运算的成熟将使工厂车间能够进行即时自主决策，消除云端延迟，同时实现传统系统无法实现的预测性维护和自我优化能力。
  • 受企业对独立于供应商、模组化、硬体无关且可快速部署和更新的解决方案的需求所推动，全球软体定义自动化市场预计将从 2024 年到 2032 年实现超过 15% 的复合年增长率。

成长限制因素 - 流程自动化市场，2024-2032 年

  • 人工智慧平台、边缘基础设施和系统整合的高昂前期成本构成了财务障碍，尤其对于中小企业而言；同时，投资回收期的不确定性和复杂的投资回报率 (ROI) 计算也可能使经营团队难以做出正确的决定。
  • 超过 50% 的流程工业客户依赖几十年前的 DCS/SCADA 系统，这些系统使用专有通讯协定，与现代 AI 和软体定义解决方案不相容，需要昂贵的维修或复杂的整合方法。
  • 近 50% 的流程工业客户面临资料分散、系统不连通、资料品质不佳、感测器测量资料缺失等问题，这阻碍了人工智慧模型的训练，并妨碍了自主解决方案的有效部署。
  • 由于数位化连接，工业系统的攻击面不断扩大，而缺乏现代安全功能则会带来安全风险，这使得各组织对可能受到攻击的自动驾驶系统保持警惕。
  • 许多行业从业人员对人工智慧系统持谨慎态度，担心它们会取代他们的工作而不是帮助他们，而且抵制数位转型的组织文化即使技术可用，也会造成采用障碍。

竞争格局－流程自动化市场，2024-2032年

自动驾驶市场的竞争特征是主要企业和大型控制系统供应商之间快速的技术创新。

弗若斯特沙利文公司已确定以下主要参与者：

  • 艾默生——透过“超越专案”，该公司将把其控制系统与 AspenTech 的人工智慧层集成，以实现自我优化自动化。
  • 西门子股份公司—凭藉其 Xcelerator 平台引领数位双胞胎市场，该平台整合了 AI Copilot，用于模型驱动的操作。
  • 施耐德电机—正在开发 EcoStruxure Automation Expert，这将实现与供应商无关的即插即用架构。
  • 霍尼韦尔—将预测性维护市场洞察融入其「Forge自动驾驶环境」。
  • 横河马达 - 扩展 OpreX IA2IA 架构，整合机器人和开放平台，以实现资料驱动的流程自主性。
  • AspenTech 与埃克森美孚合作，推动开放自动化标准和石油与天然气产业自主化计画。

这些公司正朝着统一的愿景迈进，即采用软体定义、云端原生技术来建构自主的工业生态系统。它们的策略方向强调模组化人工智慧平台、开放原始码协作和基于SaaS的预测控制，从而推动工业人工智慧、数位双胞胎和预测性维护领域的市场整合。

常见问题：

  • 1. 预计到 2032 年，製程自动化产业的市场规模将达到多少？
    • 预计製程自动化市场将从 2024 年的 481.3 亿美元成长到 2032 年的 1,842.9 亿美元，复合年增长率为 18.3%。
  • 2. 工业人工智慧将如何为製程自动化的未来做出贡献？
    • 工业人工智慧能够实现即时自主决策、预测性维护和自我优化，从而显着提高营运效率。
  • 3.数位双胞胎在工业运作中扮演什么角色？
    • 数位双胞胎创建实体资产的虚拟副本，并提供持续的模拟和分析，以改善资产生命週期管理和流程最佳化。
  • 4. 自动化操作需求不断成长的原因是什么？
    • 透过人工智慧和边缘运算，自动驾驶减少了对人为干预的依赖，有助于缓解劳动力短缺并提高营运韧性。
  • 5. 预测性维护如何影响生产效率？
    • 预测性维护市场利用人工智慧和物联网来预测设备故障、最大限度地减少停机时间并降低维护成本。
  • 6. 流程自动化市场面临哪些挑战？
    • 挑战包括前期成本高、难以与旧有系统整合、资料碎片化、网路安全风险以及对数位转型的抵制。
  • 7. 哪些产业最积极采用流程自动化技术？
    • 重点产业包括石油天然气、化学、製药、发电和采矿。
  • 8. 哪些技术趋势将推动软体定义自动化的发展？
    • 模组化、与供应商无关的平台，无需依赖硬体即可快速部署和更新，这是关键驱动因素。
  • 9.市场领导如何脱颖而出？
    • 艾默生、西门子、施耐德电气和霍尼韦尔等公司正专注于人工智慧平台、数位双胞胎和可扩展的云端边缘架构。
  • 10. 边缘运算对流程自动化意味着什么？
    • 边缘运算能够实现低延迟的本地人工智慧决策，提高工厂车间的反应速度和自主性。

目录

策略要务

  • 为什么经济成长变得越来越困难？
  • The Strategic Imperative 8（TM）
  • 三大策略要务对流程自动化市场未来发展的影响

成长机会分析

  • 流程自动化变革的必要性
  • 流程自动化中的共生智慧愿景
  • 流程自动化基础
  • 工艺装置自主性的五个阶段
  • 成长驱动因素
  • 成长限制因素
  • 市场定义
  • 市场规模及预测
  • 市场趋势

成长机会领域

  • 成长机会 1：人工智慧驱动的自主流程优化平台
  • 成长机会 2：边缘人工智慧预测性维护应用
  • 成长机会 3：流程工业的数位双胞胎市场

附录与未来发展

  • 成长机会带来的益处和影响
  • 下一步
  • 免责声明
简介目录
Product Code: MH72-32

Symbiotic Intelligence and Autonomous Operations Herald Transformational Growth in Process Industries

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.

Table of Contents

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

Growth Opportunity Analysis

  • The Need for Change in Process Automation
  • A Vision for Symbiotic Intelligence in Process Automation
  • Building Blocks of Process Automation
  • 5 Levels of Process Plant Autonomy
  • Growth Drivers
  • Growth Restraints
  • Market Definition
  • Market Sizing and Forecast
  • The Pulse of the Market

Growth Opportunity Universe

  • Growth Opportunity 1: AI-Driven Autonomous Process Optimization Platforms
  • Growth Opportunity 2: Edge AI Predictive Maintenance Applications
  • Growth Opportunity 3: Process Industry Digital Twin Marketplaces

Appendix & Next Steps

  • Benefits and Impacts of Growth Opportunities
  • Next Steps
  • Legal Disclaimer