Overview and Scope
Operational predictive maintenance (OPM) refers to a proactive maintenance strategy that utilizes data analytics, machine learning, and predictive modeling techniques to anticipate equipment failures or maintenance needs before they occur. The goal of OPM is to minimize downtime, reduce maintenance costs, and optimize the efficiency and reliability of equipment and processes.
Sizing and Forecast
The operational predictive maintenance market size has grown exponentially in recent years. It will grow from $5.78 billion in 2023 to $7.31 billion in 2024 at a compound annual growth rate (CAGR) of 26.5%. The growth in the historic period can be attributed to cost savings from reduced downtime and maintenance costs, improved asset reliability and performance, enhanced safety and risk mitigation, regulatory compliance requirements, growing awareness of predictive maintenance benefits.
The operational predictive maintenance market size is expected to see exponential growth in the next few years. It will grow to $18.62 billion in 2028 at a compound annual growth rate (CAGR) of 26.3%. The growth in the forecast period can be attributed to expansion into new industries and applications, demand for proactive maintenance solutions, market penetration in emerging economies, predictive maintenance adoption, increased focus on sustainability and energy efficiency initiatives. Major trends in the forecast period include integration of IoT sensors and data analytics, adoption of machine learning algorithms, expansion of applications across industries, development of cloud-based platforms, integration with enterprise asset management systems.
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Segmentation & Regional Insights
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
North America was the largest region in the operational predictive maintenance market in 2023. The regions covered in the operational predictive maintenance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Major Driver Impacting Market Growth
The increasing number of IoT (Internet of Things) devices is expected to propel the growth of the operational predictive maintenance market going forward. IoT devices refer to nonstandard computing hardware such as sensors, actuators, or appliances that connect wirelessly to a network and can transmit data. It arises because of the widespread availability of high-speed internet connectivity, increasing industrial automation and supply chain management, and data analytics capabilities. IoT devices play a critical role in operational predictive maintenance by enabling real-time monitoring, data analytics, early issue detection, condition-based maintenance, predictive insights, and continuous improvement, ultimately assisting organizations in optimizing asset performance, lowering costs, and increasing operating efficiency. For instance, in August 2022, according to Akamai Technologies Inc., a US-based internet company, IoT connections are expected to increase from 15.1 billion in 2021 to 23.3 billion IoT connections in 2025. Therefore, the increasing number of IoT devices drives the operational predictive maintenance market.
Key Industry Players
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
The operational predictive maintenance market report table of contents includes:
1. Executive Summary
2. Operational Predictive Maintenance Market Characteristics
3. Operational Predictive Maintenance Market Trends And Strategies
4. Operational Predictive Maintenance Market – Macro Economic Scenario
5. Global Operational Predictive Maintenance Market Size and Growth
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32. Global Operational Predictive Maintenance Market Competitive Benchmarking
33. Global Operational Predictive Maintenance Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Operational Predictive Maintenance Market
35. Operational Predictive Maintenance Market Future Outlook and Potential Analysis
36. Appendix
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