The growing adoption of IoT in industrial operations is a significant driver for the predictive maintenance market, as it enables real-time monitoring and data collection from equipment and machinery across various industries. IoT sensors continuously capture critical operational data such as temperature, vibration, pressure, and wear, which is then analyzed using advanced predictive algorithms to identify potential equipment failures before they occur. This proactive approach allows businesses to optimize maintenance schedules, reduce unexpected downtime, extend equipment lifespan, and lower operational costs. As industries increasingly adopt IoT for smart manufacturing, energy management, and supply chain optimization, predictive maintenance becomes essential for ensuring efficiency, productivity, and asset reliability in IoT-enabled environments.
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Data Bridge Market Research analyzes that the U.S. Predictive Maintenance Market is expected to reach USD 98.62 billion by 2034 from USD 5.67 billion in 2023, growing with a CAGR of 29.9% in the forecast period of 2024 to 2034.
Key Findings of the Study
Growing Demand for Big Data and Analytics Solutions
The growing demand for big data and analytics solutions is significantly shaping the predictive maintenance market, as organizations increasingly recognize the value of data-driven insights in optimizing operational efficiency. By leveraging advanced analytics, companies can process vast amounts of real-time data from IoT sensors and other sources, enabling them to identify patterns, predict equipment failures, and make informed maintenance decisions. This proactive approach minimizes unplanned downtime, reduces maintenance costs, and enhances overall asset performance, driving further investment in big data technologies. As industries continue to adopt data analytics as a core component of their maintenance strategies, the predictive maintenance market is expected to experience substantial growth, fueled by the need for improved reliability and operational effectiveness.
Report Scope and Market Segmentation
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Report Metric
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Details
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Forecast Period
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2024 to 2034
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Base Year
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2023
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Historic Years
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2022 (Customizable from 2016-2022)
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Quantitative Units
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Revenue in USD Thousands
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Segments Covered
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Offering (Solution and Services), Deployment Mode (Cloud and On-Premise), Application (Transmission Check-Up, Oil Change, Tire Inspection, Coolant Replacement, Brake, Engine Air Filter, Cabin Filter, and Belt Change), Enterprise Size (Large Size Organizations and Small & Medium Sized Organization), Vehicle Type (Passenger Car, Commercial Vehicle, and Off Road Vehicle), End User (Fleet Owners, FMS, Manufacturers, FMC, and Individual)
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Market Players Covered
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AISIN CORPORATION (Japan), PHINIA Inc. (China), KPIT (India), Microsoft (U.S.), Aptiv (Ireland), Continental AG (Germany), Robert bosch gmbh (Germany), Siemens ag (Germany), SAP se (Germany), ZF friedrichshafen ag (Germany), Valeo corporation (France), IBM (U.S.), Teletrac navman (U.S.), Garrett motion inc. (U.S.), pstream Security Ltd. (United Kingdom), Verizon (U.S.), Infineon Technologies AG (Germany), Uptake technologies inc. (U.S.), Fluke Corporation (U.S.), PTC (U.S.), Rockwell Automation (U.S.), Embitel (India), Altair Engineering Inc. (U.S.), Honeywell International Inc. (U.S.), NEC Corporation (Japan), Emerson (U.S.), C3.AI (U.S.), Progress (U.S.), Fiix by Rockwell Automation Inc. (U.S.), and Ansys (U.S.) among others
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Data Points Covered in the Report
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In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.
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Segment Analysis
The U.S. predictive maintenance market is segmented into six notable segments based on offering, deployment mode, application, enterprise size, vehicle type, and end user.
- On the basis of offering, the U.S. predictive maintenance market is segmented into solution and services
In 2024, solution is expected to dominate the U.S. predictive maintenance market
In 2024, the solution segment is expected to dominate the market with a 65.08% market share due to the widespread adoption of advanced software and IoT technologies that enable real-time monitoring and data-driven insights. These solutions provide greater efficiency and scalability, allowing automotive companies to implement predictive maintenance more effectively across fleets or individual vehicles.
- On the basis of deployment mode, the U.S. predictive maintenance market is segmented cloud and on-premise
In 2024, cloud is expected to dominate the U.S. predictive maintenance market
In 2024, cloud is expected to dominate the market with a 66.08% market share due to its scalability, flexibility, and cost-effectiveness, allowing automotive companies to easily access and analyze large volumes of data without significant upfront investments in infrastructure. Additionally, cloud solutions enable real-time updates and remote access, facilitating enhanced collaboration and quicker decision-making across teams.
- On the basis of application, the U.S. predictive maintenance market is segmented into transmission check-up, oil change, tire inspection, coolant replacement, brake, engine air filter, cabin filter, belt change and others. In 2024, transmission check-up is expected to dominate the market with a 19.87% market share
- On the basis of enterprise size, the U.S. predictive maintenance market is segmented into large size organizations and small & medium sized organization. In 2024, large size organizations are expected to dominate the market with a 62.51% market share
- On the basis of vehicle type, the U.S. predictive maintenance market is segmented into passenger car, commercial vehicle, and off road vehicle. In 2024, passenger car are expected to dominate the market with a 62.60% market share
- On the basis of end user, the U.S. predictive maintenance market is segmented into fleet owners, FMS, manufacturers, FMC, individual, and others. In 2024, fleet owners are expected to dominate the market with a 37.04% market share
Major Players
Data Bridge Market Research analyzes AISIN CORPORATION (Japan), PHINIA Inc. (China), KPIT (India), Microsoft (U.S.), and Aptiv (Ireland) as the major companies operating in the U.S. Predictive maintenance market.
Market Development
- In January 2024, Infineon Technologies AG and Aurora Labs have teamed up to introduce AI-powered predictive maintenance solutions for the automotive sector, aimed at boosting the safety and reliability of essential components like steering, braking, and airbags. This partnership enhances Infineon’s predictive maintenance offerings by leveraging AI-driven real-time monitoring and failure response with AURIX TC4x microcontrollers, enabling automotive manufacturers to improve vehicle safety and performance over the long term
- In February 2020, PTC has partnered with Senseye to integrate its predictive maintenance software, Senseye PdM, with the ThingWorx Industrial IoT platform, allowing users to automatically monitor assets and anticipate machine failures. This collaboration strengthens PTC's predictive maintenance capabilities, enabling ThingWorx users to quickly access insights from their machine data, which in turn enhances operational efficiency, minimizes unplanned downtime, and reduces maintenance costs
For more detailed information about the U.S. Predictive maintenance market report, click here – https://www.databridgemarketresearch.com/jp/reports/us-predictive-maintenance-market
