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Increasing Number Of IoT Devices Propels Operational Predictive Maintenance Market: An Emerging Driver Transforming The Operational Predictive Maintenance Market Landscape
Operational Predictive Maintenance Market
What Is the Projected Growth of the Operational Predictive Maintenance Market?
The size of the operational predictive maintenance market has witnessed an exponential increase in the recent past. The market value is projected to escalate from $7.31 billion in 2024 to $9.24 billion in 2025, reflecting a compound annual growth rate (CAGR) of 26.4%. The historic growth spurt in the market is owed to factors such as decreased downtime and maintenance expenses, improvement in asset reliability and productivity, amplified safety precautions and risk reduction, complying with regulatory mandates, and an increased understanding of the advantages of predictive maintenance.
In the coming years, the market size of operational predictive maintenance is set to undergo significant expansion. The expected escalation will bring the market to $23.57 billion in 2029, with a CAGR of 26.4%. This surge during the predicted period is due to diversification into new industries and applications, the rising demand for preemptive maintenance solutions, market intrusion in budding economies, embracing predictive maintenance, and heightened concentration on sustainability and energy efficiency efforts. Key trends during this period include the incorporation of IoT sensors and data analytic methods, the use of machine learning algorithms, broadening of applications throughout industries, the creation of cloud-based platforms, and integration into enterprise asset management systems.
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What Are the Different Operational Predictive Maintenance Market Segments?
The operational predictive maintenance market covered in this report is segmented -
1) By Type: Software, Services
2) By Deployment Model: Cloud, On-Premise
3) By Technology: Machine Learning, Deep Learning, Big Data And Analytics
4) By End User: Public Sector, Automotive, Manufacturing, Healthcare, Energy And Utility, Transportation, Other End Users
Subsegments:
1) By Software: Predictive Analytics Software, Machine Learning Software, Data Integration Tools, Asset Management Software, Real-Time Monitoring Software
2) By Services: Implementation Services, Consulting Services, Training and Support Services, Maintenance and Upgrades, Managed Services
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What Are the Primary Drivers Shaping the Operational Predictive Maintenance Market?
The surge in the number of Internet of Things (IoT) devices is being projected to fuel the expansion of the operational predictive maintenance market in the future. These IoT devices, usually uncommon computing hardware like sensors, actuators, or appliances, use wireless connections to a network to transfer data. The rise in these devices is due to the prevalent access to high-speed internet, an uptick in industrial automation and supply chain management, and the capacity for data analytics. They are instrumental in operational predictive maintenance, facilitating real-time monitoring, data analysis, early problem identification, condition-based maintenance, predictive insights, and steady enhancement. This assists businesses in enhancing asset performance, reducing expenses, and boosting operational efficiency. As reported by the GSM Association, a non-profit industry entity in the UK, we anticipate a surge in global IoT connections to 23.3 billion by 2025, a substantial increase from the 15.1 billion connections reported in 2021. As a result, the growing number of IoT devices is propelling the operational predictive maintenance market.
Which Companies Are Leading in the Operational Predictive Maintenance Market?
Major companies operating in the operational predictive maintenance market are Google LLC, Microsoft Corporation, Robert Bosch GmbH, Hitachi Ltd., Amazon Web Services Inc., The International Business Machines Corporation, General Electric Company, Schneider Electric SE, SAP SE, Svenska Kullagerfabriken AB, Rockwell Automation Inc., SAS Institute Inc., Micro Focus, Splunk Inc., PTC Inc., Software AG, TIBCO Software Inc., C3.ai Inc., Softweb Solutions Inc., Fiix Software, Uptake Technologies Inc., eMaint Enterprises LLC, Seebo Interactive Ltd., Asystom, Ecolibrium Energy
What Are the Major Trends Shaping the Operational Predictive Maintenance Market?
Leading operational predictive maintenance market firms are emphasizing on technological evolution such as analytics powered by AI and instant monitoring to enrich the dependability and productivity of their equipment. This technology-driven maintenance approach allows businesses to anticipate maintenance requirements and lessen the occurrences of operational interference. Machine intelligence scrutinizes sensor data to expose patterns which signal potential problems and hence facilitate preventive maintenance actions to enhance output and avert malfunctions. As an example, in June 2024, Hitachi Industrial Equipment Systems Co., Ltd., a company based in Japan which deals in manufacturing and marketing of industrial equipment and pieces, introduced the "Predictive Diagnosis Service" specifically for air compressors. The unique service, based on machine learning and long-distance monitoring, is designed to identify and block likely drawbacks. By fusing real-time information and skilled maintenance, this service betters the performance of operations, curtails halt time, and mitigates adverse effects on the environment.
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What Are the Top Revenue-Generating Geographies in the Operational Predictive Maintenance Market?
North America was the largest region in the operational predictive maintenance market in 2024. The regions covered in the operational predictive maintenance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
Frequently Asked Questions:
1. What Is the Market Size and Growth Rate of the Operational Predictive Maintenance Market?
2. What is the CAGR expected in the Operational Predictive Maintenance Market?
3. What Are the Key Innovations Transforming the Operational Predictive Maintenance Industry?
4. Which Region Is Leading the Operational Predictive Maintenance Market?
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