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市场调查报告书
商品编码
1813430
2032 年状态监测设备市场预测:按设备类型、监测流程、技术、应用、最终用户和地区进行的全球分析Condition Monitoring Equipment Market Forecasts to 2032 - Global Analysis By Equipment Type, Monitoring Process, Technology, Application, End User and By Geography |
根据 Stratistics MRC 的数据,全球状态监测设备市场预计在 2025 年达到 27.9 亿美元,到 2032 年将达到 48.5 亿美元,预测期内的复合年增长率为 8.2%。
状态监测系统由旨在持续评估机械运作状况的仪器和技术组成。这些设备监测振动、热量、压力和润滑等因素,以识别异常或劣化的早期征兆。透过提供预测性洞察,各行各业可以预防意外故障、提高效率并规划及时维护。这种主动方法可以提高安全性、最大限度地降低维修成本、延长设备寿命,并确保製造、能源和运输等不同行业的无缝性能。
根据思科预测,到2022年底,支援物联网应用的机器对机器(M2M)连线将占全球285亿台连网型设备的一半以上。
工业 4.0 和物联网技术的采用日益增多
随着工业自动化的发展势头强劲,企业越来越多地将智慧感测器和物联网平台整合到维护工作流程中。这些技术能够实现即时数据收集、预测分析和远距离诊断,从而提高营运效率。工业4.0计划正在推动对支援机器学习和云端连接的状态监控系统的需求。製造商正在优先考虑数位转型,以减少停机时间并优化资产性能。向智慧工厂的转变正在加速製造业、能源业和交通运输业等行业部署先进的监测工具。因此,基于物联网的状态监测正成为现代工业策略的基石。
技术纯熟劳工短缺
现代监控系统非常复杂,需要软体平台、讯号处理和设备诊断的专业训练。人才短缺减缓了实施速度,并限制了状态监测技术的潜力。中小企业尤其难以吸引和留住技术人才,这阻碍了扩充性。为了克服这项挑战,企业必须投资于人才培养和跨职能培训专案。如果没有强大的人才储备,各产业对先进监控解决方案的采用可能会不均衡。
无线和云端基础的监控的进步
无线感测器网路和云端运算领域的最新创新正在改变设备健康状况的追踪和管理方式。这些系统无需复杂的布线,并可在远端或危险环境中灵活部署。云端平台提供可扩展的资料储存和分析功能,支援跨多个设施的集中监控。与人工智慧和机器学习的整合可提供预测性洞察和自动警报,从而降低维护成本。改进的连接性也促进了行动存取和维护团队之间的即时协作。这些发展为石油天然气、采矿业和智慧基础设施等领域的状态监测开闢了新的途径。
技术快速淘汰
感测器设计、分析软体和连接标准的技术创新日新月异,可能在几年内就使现有系统过时。随着新技术的涌现,公司可能面临高昂的升级成本和相容性问题。通讯协定和硬体规格的频繁变化可能会扰乱长期规划和筹资策略。规模较小的供应商可能难以跟上步伐,导致市场整合和多样性下降。此外,旧有系统可能缺乏对新功能的支持,并且与现代平台的整合有限。这种持续的演变为寻求稳定、面向未来解决方案的买家带来了风险。
COVID-19的影响
疫情扰乱了製造营运和供应链,延误了状态监测系统的安装和维护计画。出行限制和劳动力短缺影响了现场服务的可用性,并减缓了新的部署。然而,这场危机也凸显了远距离诊断和预测性维护的价值,尤其是在关键基础设施领域。随着企业适应远距办公环境,对非接触式监控和云端基础平台的需求激增。医疗保健、公共产业和物流等行业加快了对智慧维护工具的投资,以确保业务连续性。疫情后的復苏预计将进一步推动智慧维护技术的采用,而韧性和自动化将成为重中之重。
预计振动监测系统部分将成为预测期内最大的部分
振动监测系统领域预计将在预测期内占据最大的市场份额,这得益于其在旋转机械和关键资产中的广泛应用。这些系统能够及早发现机械故障,例如不平衡、错位和轴承磨损。其可靠性和成本效益使其成为製造业、发电业以及石油和天然气等行业的首选。感测器精度和数据分析的不断改进正在提升诊断能力。与无线和云端平台的整合正在扩展其在偏远和恶劣环境中的应用。随着预测性维护成为主流,振动监测仍然是一项基础技术。
预计物联网监控平台部分将在预测期内实现最高的复合年增长率。
物联网监控平台细分市场预计将在预测期内实现最高成长率,因为它们能够提供即时洞察和远端存取。这些系统利用云端运算、边缘分析和人工智慧来优化设备效能并减少停机时间。扩充性和互通性使其成为多站点营运和复杂资产网路的理想选择。对智慧工厂和数数位双胞胎日益增长的需求正在刺激汽车、航太和公共产业等领域的采用。增强的网路安全和数据整合能力解决了数位转型方面的担忧。随着各行各业对预测智慧的采用,物联网平台正成为下一代维护策略的核心。
由于工业化进程加快、基础设施建设不断扩展以及製造业活动强劲,预计亚太地区将在预测期内占据最大的市场份额。中国、印度和日本等国家正大力投资智慧工厂计画和自动化。该地区能源和交通运输行业的成长推动了对可靠状态监控解决方案的需求。政府推动数位化和资产安全的政策也进一步推动了市场成长。当地製造商越来越多地采用预测性维护来提高生产力并降低营运成本。
由于早期采用先进技术且研发实力雄厚,北美预计将在预测期内呈现最高的复合年增长率。该地区对资产可靠性和营运效率的关注正在推动对预测性维护工具的投资。航太、石油天然气和公共产业等关键产业正在采用物联网和人工智慧驱动的监控平台。职场安全和设备性能的监管标准正在推动主动维护策略。科技公司与工业企业之间的合作正在加速感测器设计和分析领域的创新。
According to Stratistics MRC, the Global Condition Monitoring Equipment Market is accounted for $2.79 billion in 2025 and is expected to reach $4.85 billion by 2032 growing at a CAGR of 8.2% during the forecast period. Condition monitoring equipment consists of instruments and technologies designed to continuously assess the operational state of machines. These devices monitor factors like vibration, heat, pressure, and lubrication to identify irregularities or early signs of deterioration. By providing predictive insights, they enable industries to prevent unexpected breakdowns, improve efficiency, and schedule timely maintenance. This proactive approach enhances safety, minimizes repair costs, prolongs equipment life, and ensures seamless performance across diverse sectors such as manufacturing, energy, and transportation.
According to Cisco, by the end of 2022, machine-to-machine (M2M) connections supporting IoT applications accounted for more than half of the world's 28.5 billion connected devices.
Increasing adoption of Industry 4.0 and IoT technologies
As industrial automation gains momentum, companies are increasingly integrating smart sensors and IoT platforms into their maintenance workflows. These technologies enable real-time data collection, predictive analytics, and remote diagnostics, enhancing operational efficiency. Industry 4.0 initiatives are driving demand for condition monitoring systems that support machine learning and cloud connectivity. Manufacturers are prioritizing digital transformation to reduce downtime and optimize asset performance. The shift toward intelligent factories is accelerating the deployment of advanced monitoring tools across sectors like manufacturing, energy, and transportation. As a result, IoT-enabled condition monitoring is becoming a cornerstone of modern industrial strategy.
Lack of skilled workforce
The complexity of modern monitoring systems requires specialized training in software platforms, signal processing, and equipment diagnostics. This talent gap slows implementation and limits the full potential of condition monitoring technologies. Smaller firms, in particular, face challenges in recruiting and retaining skilled personnel, which can hinder scalability. To overcome this, companies must invest in workforce development and cross-functional training programs. Without a robust talent pipeline, adoption of advanced monitoring solutions may remain uneven across industries.
Advancements in wireless and cloud-based monitoring
Recent innovations in wireless sensor networks and cloud computing are transforming how equipment health is tracked and managed. These systems eliminate the need for complex wiring, enabling flexible deployment in remote or hazardous environments. Cloud platforms offer scalable data storage and analytics, supporting centralized monitoring across multiple facilities. Integration with AI and machine learning allows for predictive insights and automated alerts, reducing maintenance costs. Enhanced connectivity also facilitates mobile access and real-time collaboration among maintenance teams. These developments open new avenues for condition monitoring in sectors like oil & gas, mining, and smart infrastructure.
Rapid technological obsolescence
The fast pace of innovation in sensor design, analytics software, and connectivity standards can render existing systems outdated within a few years. Companies may face high upgrade costs or compatibility issues when newer technologies emerge. Frequent changes in protocols and hardware specifications can disrupt long-term planning and procurement strategies. Smaller vendors may struggle to keep pace, leading to market consolidation and reduced diversity. Additionally, legacy systems may lack support for newer features, limiting integration with modern platforms. This constant evolution poses risks for buyers seeking stable, future-proof solutions.
Covid-19 Impact
The pandemic disrupted manufacturing operations and supply chains, delaying installations and maintenance schedules for condition monitoring systems. Travel restrictions and workforce shortages impacted field service availability and slowed new deployments. However, the crisis highlighted the value of remote diagnostics and predictive maintenance, especially in critical infrastructure. Demand for contactless monitoring and cloud-based platforms surged as companies adapted to remote work environments. Sectors like healthcare, utilities, and logistics accelerated investment in smart maintenance tools to ensure operational continuity. Post-pandemic recovery is expected to further boost adoption, with resilience and automation becoming top priorities.
The vibration monitoring systems segment is expected to be the largest during the forecast period
The vibration monitoring systems segment is expected to account for the largest market share during the forecast period, due to its widespread use in rotating machinery and critical assets. These systems offer early detection of mechanical faults such as imbalance, misalignment, and bearing wear. Their reliability and cost-effectiveness make them a preferred choice across industries like manufacturing, power generation, and oil & gas. Continuous improvements in sensor accuracy and data analytics are enhancing diagnostic capabilities. Integration with wireless and cloud platforms is expanding their applicability in remote and harsh environments. As predictive maintenance becomes mainstream, vibration monitoring remains a foundational technology.
The IoT-enabled monitoring platforms segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the IoT-enabled monitoring platforms segment is predicted to witness the highest growth rate, driven by their ability to deliver real-time insights and remote accessibility. These systems leverage cloud computing, edge analytics, and AI to optimize equipment performance and reduce downtime. Their scalability and interoperability make them ideal for multi-site operations and complex asset networks. Rising demand for smart factories and digital twins is fueling adoption across sectors like automotive, aerospace, and utilities. Enhanced cybersecurity and data integration features are addressing concerns around digital transformation. As industries embrace predictive intelligence, IoT platforms are becoming central to next-gen maintenance strategies.
During the forecast period, the Asia Pacific region is expected to hold the largest market share due to rapid industrialization, infrastructure expansion, and strong manufacturing activity. Countries like China, India, and Japan are investing heavily in smart factory initiatives and automation. The region's growing energy and transportation sectors are driving demand for reliable condition monitoring solutions. Government policies promoting digitalization and equipment safety are further supporting market growth. Local manufacturers are increasingly adopting predictive maintenance to improve productivity and reduce operational costs.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, fuelled by early adoption of advanced technologies and strong R&D capabilities. The region's focus on asset reliability and operational efficiency is driving investment in predictive maintenance tools. Key industries such as aerospace, oil & gas, and utilities are embracing IoT and AI-powered monitoring platforms. Regulatory standards around workplace safety and equipment performance are encouraging proactive maintenance strategies. Collaborations between tech firms and industrial players are accelerating innovation in sensor design and analytics.
Key players in the market
Some of the key players profiled in the Condition Monitoring Equipment Market include SKF Group, Azima DLI, Emerson Electric Co., Schaeffler Group, Honeywell International Inc., Meggitt PLC, General Electric (GE), Bruel & Kjaer Vibro, Siemens AG, FLIR Systems Inc., ABB Ltd., AMETEK Inc., Rockwell Automation Inc., Parker Hannifin Corp., and National Instruments Corp.
In July 2025, Emerson announced a strategic partnership with product engineering and digital services leader Tata Technologies to innovate integrated testing and validation solutions for global OEMs in the automotive, aerospace and commercial vehicle sectors.
In May 2025, SKF announced a partnership with wave energy technology development company Carnegie Clean Energy Limited to deliver Carnegie's CETO's Power Take-Off (PTO) system. CETO is a unique, fully submerged, point absorber type wave energy technology where a submerged buoy sits a few metres below the surface of the ocean and moves with the ocean's waves.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.