Pune, March 25, 2025 (GLOBE NEWSWIRE) -- Predictive Maintenance Market Size Analysis:
“The Predictive Maintenance Market was valued at USD 8.53 billion in 2023 and is projected to reach USD 105.66 billion by 2032, expanding at a CAGR of 32.32% during the forecast period of 2024-2032.”
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Major Players Analysis Listed in this Report are:
- IBM (Maximo, Watson IoT)
- ABB (Ability, Condition Monitoring)
- Schneider Electric (EcoStruxure, Asset Advisor)
- AWS (IoT SiteWise, AWS IoT Greengrass)
- Google (Cloud AI, Vertex AI)
- Microsoft (Azure IoT Hub, Dynamics 365 Remote Monitoring)
- Hitachi (Lumada, Hitachi Vantara)
- SAP (SAP Predictive Maintenance, SAP Leonardo)
- SAS Institute (SAS Visual Analytics, SAS Analytics)
- Software AG (Cumulocity IoT, Software AG IoT Suite)
- TIBCO Software (TIBCO Spotfire, TIBCO Cloud Integration)
- Altair (Altair Smart Learning, Altair Smart Maintenance)
- Oracle (Oracle IoT Cloud, Oracle Autonomous Database)
- Splunk (Splunk Enterprise, Splunk IT Service Intelligence)
- C3.ai (C3 Predictive Maintenance, C3 AI Suite)
- Emerson (Plantweb, Emerson AMS Device Manager)
- GE (Predix, Asset Performance Management)
- Honeywell (Honeywell Forge, Honeywell Connected Plant)
- Siemens (MindSphere, Siemens Predictive Services)
- PTC (ThingWorx, Vuforia)
- Dingo (Dingo Predictive Maintenance, Dingo Pro)
- Uptake (Uptake Fleet, Uptake Insights)
- Samotics (SAM4, Samotics Edge)
- WaveScan (WaveScan Maintenance Solution, WaveScan Analytics)
- Quadrical Ai (AI Predictive Maintenance, Quadrical Platform)
- UpKeep (UpKeep Maintenance Management, UpKeep Analytics)
- Limble (Limble CMMS, Limble Analytics)
- SenseGrow (SenseGrow Predictive, SenseGrow IoT)
- Presage Insights (Presage Maintenance, Presage Analytics)
- Falcon Labs (Falcon Insights, Falcon Cloud Solutions)
Predictive Maintenance Market Report Scope:
| Report Attributes | Details |
| Market Size in 2023 | USD 8.53 Billion |
| Market Size by 2032 | USD 105.66 Billion |
| CAGR | CAGR of 32.32% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Key Regional Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Key Growth Drivers | • Advancements in IoT and Sensor Integration Fueling Growth of the Predictive Maintenance Market • The Role of Data Availability and Cloud Computing in Enhancing Predictive Maintenance Capabilities |
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Predictive Maintenance Market Surges with AI and IoT Advancements, Driving Cost Savings and Efficiency
The predictive maintenance field serves as a huge following field that has been increasing due to the advancements in machine learning, IoT, and data analysis which allows organizations to improve their maintenance strategies. Compared with reactive maintenance methods, predictive maintenance can lower costs of maintenance by up to 40% and can reduce equipment downtime by 50%. Manufacturing, energy, and transportation (to name a few) companies benefit from greater reliability and efficiency. Adoption is fueled by the push for operational efficiency and digital transformation, with innovations like that of Hitachi’s AI-powered diagnostic services at the helm. New technologies, AI, 5G, and smarter sensors will make these solutions even more tradable and vital across industries.
The U.S. market was valued at USD 3.0 billion in 2023 and is projected to reach USD 25.97 billion by 2032, expanding at a CAGR of 27.1% during the forecast period of 2024-2032.
The growth of the Predictive Maintenance market in the U.S. is driven by the increasing adoption of IoT and AI-powered analytics in industrial sectors, helping businesses reduce downtime and maintenance costs. Additionally, the rising focus on asset optimization and the growing demand for cloud-based predictive maintenance solutions are fueling market expansion.
By Component: Solutions Segment Leads, While Services Register Fastest Growth
In 2023, the solutions segment dominated the market and held the largest share of more than 83% in the Predictive Maintenance Market owing to the rising adoption of AI-based predictive analytics platforms and cloud-based solutions. They offer real-time monitoring, asset condition assessment, and fault detection solutions that increase efficiency in different industries.
The Services segment is anticipated to post the fastest CAGR through 2024–2032, as organizations look for professional advisory, integration, and maintenance assistance. Enterprise solution providers require customized predictive maintenance solution marketing; thus, demand for professional and managed services is continually rising —a major trend that can be observed.
By Organization Size: Large Enterprises Hold Major Share, SMEs Witness Fastest Growth
The large Enterprises segment dominated the market and accounted for 72% of the revenue share due to their high investments in AI-driven analytics, advanced IoT sensors, and cloud infrastructure thereby optimizing maintenance processes. Predictive maintenance is critical in larger-scale sectors such as manufacturing, energy, and transportation to keep operations running smoothly and avoid high costs.
The Small & Medium-Sized Enterprises segment is expected to register the fastest CAGR during the forecast period, which is increasingly switching to cost-effective, scalable, and cloud-based predictive maintenance solutions.
By Deployment Model: Cloud-Based Solutions Dominate, Hybrid Deployment Gains Traction
The cloud-based dominated the market and accounted for a significant revenue share in 2023, The advantage of flexibility, cost-savings, and remote monitoring of cloud technology. By leveraging these solutions, organizations can capture, analyze, and act on machine data in real-time which in turn empowers organizations to enhance their maintenance strategies.
Hybrid Cloud is expected to register the fastest CAGR during the forecast period, as industries opt for on-premise security along with cloud deployment for scalability. This approach offers more control over the security of data whilst utilizing the power of cloud-based predictive analytics.
By Monitoring Technique: Vibration Monitoring Dominates, Oil Analysis Registers Fastest Growth
The vibration Monitoring segment dominated the market and accounted for a significant revenue share in 2023, due to its prominence in the manufacturing, energy, and automotive industries and effective in detecting mechanical imbalances and potential failure before it actualizes. This reduces unplanned downtimes and allows the machine to be used at its optimum capacity.
The oil analysis is expected to register the fastest CAGR during the forecast period, which is expected to grow at the fastest CAGR due to the growing demand for fluid monitoring, particularly in heavy machinery, transport, and industrial applications. It is an efficient lubrication management technique that decreases friction-induced failures.
Predictive Maintenance Market Segmentation:
By Component
- Solution
- Integrated
- Standalone
- Service
- Integration and Deployment
- Support & Maintenance
- Training & Consulting
By Deployment Model
- Cloud
- On-premise
By Enterprise Size
- Small & Medium Enterprises
- Large Enterprises
By Monitoring Technique
- Torque Monitoring
- Vibration Monitoring
- Oil Analysis
- Thermography
- Corrosion Monitoring
- Others
By End-use
- Aerospace & Defense
- Automotive & Transportation
- Energy & Utilities
- Healthcare
- IT & Telecommunications
- Manufacturing
- Others
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North America Leads, While Asia-Pacific Emerges as the Fastest-Growing Market
North America dominated the market and accounted for 39% of revenue share, due to the high adoption of Industry 4.0, the strong presence of AI-driven technology providers, and government support for the digital transformation of manufacturing processes. The market is projected to have a strong demand in the U.S. and Canada, due to the high investments & initiatives in smart manufacturing, energy efficiency, and industrial automation.
Asia-Pacific is expected to register the fastest CAGR during the forecast period, driven by more industrialization of the region and advancing governments in smart cities AI-driven predictive maintenance is increasingly being adopted in China, India, and Japan to improve manufacturing efficiency, transportation, and infrastructure.
Recent News
- In August 2024, ABB introduced Trendex, a cloud-based digital tool designed to enhance the ABB Ability Predictive Maintenance for Grinding platform. This innovation provides users with high-resolution event data before and after faults, enabling quicker diagnostics and reducing downtime in mineral processing operations.
Table of Contents – Major Key Points
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
6. Competitive Landscape
7. Predictive Maintenance Market Segmentation, By Component
8. Predictive Maintenance Market Segmentation, By Monitoring Technique
9. Predictive Maintenance Market Segmentation, By End-use
10. Predictive Maintenance Market Segmentation, By Deployment Model
11. Predictive Maintenance Market Segmentation, By Enterprise Size
12. Regional Analysis
13. Company Profiles
14. Use Cases and Best Practices
15. Conclusion
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