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2024158

預測性維護感測器市場預測至2034年—按感測器類型、組件、部署模式、應用、最終用戶和地區分類的全球分析

Predictive Maintenance Sensors Market Forecasts to 2034 - Global Analysis By Sensor Type (Vibration Sensors, Temperature Sensors, Pressure Sensors, Acoustic Sensors, and Infrared Sensors), Component, Deployment, Application, End User, and By Geography

出版日期: 2026年04月17日 | 出版商:

Stratistics Market Research Consulting | 英文 | 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，全球預測性維護感測器市場規模將達到 128 億美元，並在預測期內以 16.2% 的複合年成長率成長，到 2034 年將達到 426 億美元。

預測性維護感測器是指安裝在工業機械、生產設備和關鍵基礎設施資產上的振動、溫度、壓力、聲音發射、紅外線和超音波檢測裝置。這些感測器持續收集設備健康狀況的即時數據，然後由人工智慧分析徵兆進行處理，以檢測機械故障、軸承劣化、潤滑問題、不平衡和腐蝕加劇的早期徵兆。這使得製造業、石油天然氣、發電和交通基礎設施產業的維護團隊能夠在關鍵故障發生之前製定糾正措施。

透過工業4.0實現維修革命

工業4.0數位化專案以數據驅動的預測性維護策略取代了基於時間的預防性維護計劃，隨著越來越多的製造商在先前未監控的設備上安裝無線感測器節點，以提供持續的機器狀態遙測數據，從而基於人工智慧分析進行故障預測，因此對感測器部署的需求顯著增加。預測性維護項目的顯著成果，包括維護成本降低25-30%和設備壽命延長20-40%，為資本密集型製造企業投資此類項目提供了強力的論證。

無線感測器的電池續航力限制

在高溫、振動和電磁干擾等惡劣工業環境中，無線工業IoT感測器節點的電池壽命有限，這導致維護負擔加重，並造成連續監測覆蓋範圍的中斷。因此，必須定期更換感測器電池，這不僅增加了持續維護成本，而且在危險或難以接近的地點進行電池更換作業時，還會造成常規監測中斷。

可再生能源資產監測

預測性維護感測器在風力發電機、太陽能逆變器和電池儲能系統中的應用，代表著一個快速成長的市場機會。可再生能源資產業者需要對地理位置分散的設施進行持續的機械和電氣健康監測。雖然現場維護成本高昂，但早期故障檢測能夠顯著降低災難性故障和渦輪機停機的風險，從而直接影響發電收入。

數據過載給分析帶來挑戰

大規模感測器部署產生的大量連續儀器遙測數據，遠遠超出工業營運團隊的人工數據審核能力，導致分析工作異常複雜。將原始感測器數據轉化為可執行的維護建議，需要投資先進的人工智慧平台，這除了初始的感測器硬體採購成本外，還會帶來額外的成本障礙。對於缺乏人工智慧分析能力的企業而言，這限制了預測性維護專案整體價值的實現。

新冠疫情的影響：

由於新冠疫情導致現場維護團隊運轉率減少，迫切需要遠端設備狀態監測功能，以便在現場訪問受限期間也能管理預測性維護計畫。疫情期間備件價值鏈的中斷凸顯了早期故障偵測的重要性，這使得在故障發生前有更長的零件採購時間。疫情後工業自動化投資熱潮將預測性維護納入智慧工廠計畫的標準組成部分，從而推動了感測器市場的強勁成長。

在預測期內，紅外線感測器細分市場預計將佔據最大的市場佔有率。

預計在預測期內，紅外線感測器細分市場將佔據最大的市場佔有率。這主要得益於其在預測性維護感測器領域的高普及率，而這又得益於其廣泛的熱成像應用，例如電氣面板檢測、機械軸承溫度監測、工業製程溫度控管以及建築能源審計。工業紅外線熱像儀硬體成本的下降以及應用範圍從專業應用擴展到日常設備監控，都進一步鞏固了該細分市場在銷售方面的主導地位。

預計在預測期內，硬體領域將呈現最高的複合年成長率。

在預測期內，硬體領域預計將呈現最高的成長率。這主要歸功於以下幾個方面：工業感測器節點在以往未受監控的設備上的部署顯著增加；隨著預測性維護計劃從試點部署擴展到企業級設備監控，硬體採購需求大幅成長；以及MEMS振動感測器、無線通訊模組和邊緣AI晶片的快速小型化和成本降低，使得在更廣泛的設備中經濟高效地部署感測器成為可能。

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。這主要歸功於美國龐大的資本密集型製造業、石油天然氣和發電基礎設施，其預測性維護感測器的高普及率，Honeywell、艾默生、亞德諾半導體和德克薩斯等領先的感測器技術公司在國內創造的巨額收入，以及強大的工業IoT投資文化推動了感測器在各個工業領域的應用。

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。這主要歸因於以下因素：中國、日本、韓國和印度正在實施大規模智慧製造項目，這些項目需要廣泛部署設備健康監測感測器；可再生能源設備的快速成長需要持續的資產監測；以及中國和韓國國內工業IoT感測器的發展，建構了具有競爭力的供應生態系統，從而推動了區域感測器市場的擴張。

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
- 對主要企業進行SWOT分析（最多3家公司）
區域細分
- 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
競爭性標竿分析
- 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

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11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12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13章：公司簡介

Siemens AG
ABB Ltd.
Emerson Electric Co.
Honeywell International
Schneider Electric
General Electric
Rockwell Automation
Bosch Sensortec
STMicroelectronics
Texas Instruments
Analog Devices
National Instruments
Eaton Corporation
Omron Corporation
Yokogawa Electric
Endress+Hauser
Parker Hannifin

簡介目錄圖表

Product Code: SMRC35369

According to Stratistics MRC, the Global Predictive Maintenance Sensors Market is accounted for $12.8 billion in 2026 and is expected to reach $42.6 billion by 2034 growing at a CAGR of 16.2% during the forecast period. Predictive maintenance sensors refer to vibration, temperature, pressure, acoustic emission, infrared, and ultrasonic sensing devices deployed on industrial machinery, production equipment, and critical infrastructure assets to continuously collect real-time equipment health data that AI-powered analytics platforms process to detect early signatures of developing mechanical faults, bearing degradation, lubrication failures, imbalance conditions, and corrosion progression, enabling maintenance teams to schedule corrective interventions before catastrophic failure events occur across manufacturing, oil and gas, power generation, and transportation infrastructure.

Market Dynamics:

Driver:

Industry 4.0 Maintenance Revolution

Industry 4.0 digitalization programs replacing time-based preventive maintenance schedules with data-driven predictive maintenance strategies are generating substantial sensor deployment demand as manufacturers instrument previously unmonitored equipment with wireless sensor nodes providing the continuous machine health telemetry required for AI analytics-based failure prediction. Documented maintenance cost reductions of 25 to 30 percent and equipment lifespan extensions of 20 to 40 percent from predictive maintenance programs create compelling investment justifications across capital-intensive manufacturing operations.

Restraint:

Wireless Sensor Battery Limitations

Battery life limitations of wireless industrial IoT sensor nodes in extreme industrial environment deployment conditions including high temperature, vibration, and electromagnetic interference create maintenance burden and operational gaps in continuous monitoring coverage that require sensor battery replacement programs adding ongoing maintenance cost and creating periodic monitoring gaps during battery replacement procedures in hazardous or difficult-access equipment installation locations.

Opportunity:

Renewable Energy Asset Monitoring

Wind turbine, solar inverter, and battery storage system predictive maintenance sensor deployment represents a rapidly growing market opportunity as renewable energy asset operators require continuous mechanical and electrical health monitoring across geographically dispersed installations where on-site maintenance visits are expensive and early fault detection significantly reduces catastrophic failure risks and turbine downtime that directly impact energy generation revenue.

Threat:

Data Overload Analytics Challenges

Data overload from large-scale sensor deployments generating massive continuous equipment telemetry streams exceeds industrial operations team capacity for manual data review and creates analytical complexity that requires sophisticated AI platform investment to transform raw sensor data into actionable maintenance recommendations, creating a secondary cost barrier beyond initial sensor hardware procurement that constrains total predictive maintenance program value realization for organizations lacking AI analytics capabilities.

Covid-19 Impact:

COVID-19 reduced on-site maintenance team availability that created urgent demand for remote equipment health monitoring capabilities enabling predictive maintenance program management during restricted site access periods. Pandemic-era supply chain disruptions for replacement parts amplified the value of early fault detection enabling longer advance notice for parts procurement before failure. Post-pandemic industrial automation investment wave incorporating predictive maintenance as a standard component of smart factory programs sustains strong sensor market growth.

The infrared sensors segment is expected to be the largest during the forecast period

The infrared sensors segment is expected to account for the largest market share during the forecast period, due to broad thermal imaging application across electrical panel inspection, mechanical bearing temperature monitoring, industrial process heat management, and building energy audit applications that collectively generate the highest deployment volume within the predictive maintenance sensor category. Cost reduction of industrial infrared thermal camera hardware expanding deployment from specialized applications to routine equipment monitoring sustains segment revenue leadership.

The hardware segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the hardware segment is predicted to witness the highest growth rate, driven by massive expansion of industrial sensor node deployment across previously unmonitored equipment creating substantial hardware procurement demand as predictive maintenance programs scale from pilot installations to enterprise-wide equipment monitoring coverage, combined with rapid miniaturization and cost reduction of MEMS vibration sensors, wireless communication modules, and edge AI chips enabling economical sensor instrumentation of a broader equipment population.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to the United States hosting extensive capital-intensive manufacturing, oil and gas, and power generation infrastructure with high predictive maintenance sensor adoption, leading sensor technology companies including Honeywell, Emerson, Analog Devices, and Texas Instruments generating substantial domestic revenue, and strong industrial IoT investment culture driving sensor deployment across diverse industrial sectors.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to China, Japan, South Korea, and India implementing large-scale smart manufacturing programs requiring extensive equipment health monitoring sensor deployment, rapidly growing renewable energy installations requiring continuous asset monitoring, and domestic industrial IoT sensor development in China and South Korea creating competitive supply ecosystems driving regional sensor market expansion.

Key players in the market

Some of the key players in Predictive Maintenance Sensors Market include Siemens AG, ABB Ltd., Emerson Electric Co., Honeywell International, Schneider Electric, General Electric, Rockwell Automation, Bosch Sensortec, STMicroelectronics, Texas Instruments, Analog Devices, National Instruments, Eaton Corporation, Omron Corporation, Yokogawa Electric, Endress+Hauser, and Parker Hannifin.

Key Developments:

In March 2026, Emerson Electric Co. launched a new wireless vibration sensor platform with six-month battery life and integrated edge AI processing for rotating machinery fault detection requiring no external gateway hardware for deployment.

In February 2026, Analog Devices introduced a new MEMS vibration sensing IC combining accelerometer, temperature, and acoustic emission sensing in a single chip enabling cost-effective multi-parameter equipment monitoring at industrial scale.

In January 2026, Honeywell International expanded its Forge predictive maintenance platform with new AI models for wind turbine gearbox fault detection enabling renewable energy operators to predict bearing failures up to 30 days in advance.

Sensor Types Covered:

Vibration Sensors
Temperature Sensors
Pressure Sensors
Acoustic Sensors
Infrared Sensors

Components Covered:

Hardware
Software Platforms
Analytics Services

Deployments Covered:

Wireless Sensors
Wired Sensors

Applications Covered:

Equipment Monitoring
Asset Performance Management
Failure Detection
Condition Monitoring
Energy Optimization

End Users Covered:

Manufacturing
Oil & Gas
Energy & Utilities
Transportation
Aerospace

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 Predictive Maintenance Sensors Market, By Sensor Type

5.1 Vibration Sensors
5.2 Temperature Sensors
5.3 Pressure Sensors
5.4 Acoustic Sensors
5.5 Infrared Sensors

6 Global Predictive Maintenance Sensors Market, By Component

6.1 Hardware
6.2 Software Platforms
6.3 Analytics Services

7 Global Predictive Maintenance Sensors Market, By Deployment

7.1 Wireless Sensors
7.2 Wired Sensors

8 Global Predictive Maintenance Sensors Market, By Application

8.1 Equipment Monitoring
8.2 Asset Performance Management
8.3 Failure Detection
8.4 Condition Monitoring
8.5 Energy Optimization

9 Global Predictive Maintenance Sensors Market, By End User

9.1 Manufacturing
9.2 Oil & Gas
9.3 Energy & Utilities
9.4 Transportation
9.5 Aerospace

10 Global Predictive Maintenance Sensors Market, By Geography

10.1 North America
- 10.1.1 United States
- 10.1.2 Canada
- 10.1.3 Mexico
10.2 Europe
- 10.2.1 United Kingdom
- 10.2.2 Germany
- 10.2.3 France
- 10.2.4 Italy
- 10.2.5 Spain
- 10.2.6 Netherlands
- 10.2.7 Belgium
- 10.2.8 Sweden
- 10.2.9 Switzerland
- 10.2.10 Poland
- 10.2.11 Rest of Europe
10.3 Asia Pacific
- 10.3.1 China
- 10.3.2 Japan
- 10.3.3 India
- 10.3.4 South Korea
- 10.3.5 Australia
- 10.3.6 Indonesia
- 10.3.7 Thailand
- 10.3.8 Malaysia
- 10.3.9 Singapore
- 10.3.10 Vietnam
- 10.3.11 Rest of Asia Pacific
10.4 South America
- 10.4.1 Brazil
- 10.4.2 Argentina
- 10.4.3 Colombia
- 10.4.4 Chile
- 10.4.5 Peru
- 10.4.6 Rest of South America
10.5 Rest of the World (RoW)
- 10.5.1 Middle East
  - 10.5.1.1 Saudi Arabia
  - 10.5.1.2 United Arab Emirates
  - 10.5.1.3 Qatar
  - 10.5.1.4 Israel
  - 10.5.1.5 Rest of Middle East
- 10.5.2 Africa
  - 10.5.2.1 South Africa
  - 10.5.2.2 Egypt
  - 10.5.2.3 Morocco
  - 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

11.1 Industry Value Network and Supply Chain Assessment
11.2 White-Space and Opportunity Mapping
11.3 Product Evolution and Market Life Cycle Analysis
11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

12.1 Mergers and Acquisitions
12.2 Partnerships, Alliances, and Joint Ventures
12.3 New Product Launches and Certifications
12.4 Capacity Expansion and Investments
12.5 Other Strategic Initiatives

13 Company Profiles

13.1 Siemens AG
13.2 ABB Ltd.
13.3 Emerson Electric Co.
13.4 Honeywell International
13.5 Schneider Electric
13.6 General Electric
13.7 Rockwell Automation
13.8 Bosch Sensortec
13.9 STMicroelectronics
13.10 Texas Instruments
13.11 Analog Devices
13.12 National Instruments
13.13 Eaton Corporation
13.14 Omron Corporation
13.15 Yokogawa Electric
13.16 Endress+Hauser
13.17 Parker Hannifin

簡介目錄圖表

List of Tables

Table 1 Global Predictive Maintenance Sensors Market Outlook, By Region (2023-2034) ($MN)
Table 2 Global Predictive Maintenance Sensors Market Outlook, By Sensor Type (2023-2034) ($MN)
Table 3 Global Predictive Maintenance Sensors Market Outlook, By Vibration Sensors (2023-2034) ($MN)
Table 4 Global Predictive Maintenance Sensors Market Outlook, By Temperature Sensors (2023-2034) ($MN)
Table 5 Global Predictive Maintenance Sensors Market Outlook, By Pressure Sensors (2023-2034) ($MN)
Table 6 Global Predictive Maintenance Sensors Market Outlook, By Acoustic Sensors (2023-2034) ($MN)
Table 7 Global Predictive Maintenance Sensors Market Outlook, By Infrared Sensors (2023-2034) ($MN)
Table 8 Global Predictive Maintenance Sensors Market Outlook, By Component (2023-2034) ($MN)
Table 9 Global Predictive Maintenance Sensors Market Outlook, By Hardware (2023-2034) ($MN)
Table 10 Global Predictive Maintenance Sensors Market Outlook, By Software Platforms (2023-2034) ($MN)
Table 11 Global Predictive Maintenance Sensors Market Outlook, By Analytics Services (2023-2034) ($MN)
Table 12 Global Predictive Maintenance Sensors Market Outlook, By Deployment (2023-2034) ($MN)
Table 13 Global Predictive Maintenance Sensors Market Outlook, By Wireless Sensors (2023-2034) ($MN)
Table 14 Global Predictive Maintenance Sensors Market Outlook, By Wired Sensors (2023-2034) ($MN)
Table 15 Global Predictive Maintenance Sensors Market Outlook, By Application (2023-2034) ($MN)
Table 16 Global Predictive Maintenance Sensors Market Outlook, By Equipment Monitoring (2023-2034) ($MN)
Table 17 Global Predictive Maintenance Sensors Market Outlook, By Asset Performance Management (2023-2034) ($MN)
Table 18 Global Predictive Maintenance Sensors Market Outlook, By Failure Detection (2023-2034) ($MN)
Table 19 Global Predictive Maintenance Sensors Market Outlook, By Condition Monitoring (2023-2034) ($MN)
Table 20 Global Predictive Maintenance Sensors Market Outlook, By Energy Optimization (2023-2034) ($MN)
Table 21 Global Predictive Maintenance Sensors Market Outlook, By End User (2023-2034) ($MN)
Table 22 Global Predictive Maintenance Sensors Market Outlook, By Manufacturing (2023-2034) ($MN)
Table 23 Global Predictive Maintenance Sensors Market Outlook, By Oil & Gas (2023-2034) ($MN)
Table 24 Global Predictive Maintenance Sensors Market Outlook, By Energy & Utilities (2023-2034) ($MN)
Table 25 Global Predictive Maintenance Sensors Market Outlook, By Transportation (2023-2034) ($MN)
Table 26 Global Predictive Maintenance Sensors Market Outlook, By Aerospace (2023-2034) ($MN)