According to the latest market study on “Predictive Maintenance Market Forecast to 2028 – COVID-19 Impact and Global Analysis – by Component, Deployment Type, Technique and Industry,” the market is expected to grow from US$ 5,316.99 million in 2021 to US$ 26,588.00 million by 2028; it is anticipated to grow at a CAGR of 27.4% from 2022 to 2028.
Industry 4.0 is revolutionizing the way companies make, improve, and sell their products. Aerospace, defense, transportation, and many other industries are implementing the latest technologies, including the Internet of Things (IoT), cloud computing and analytics, artificial intelligence (AI), and machine learning (ML), to improve processes and overall operations. Companies in the oil & gas industry are significantly adopting technologies, such as IoT and advanced analytics to enhance operational efficiencies, cut costs, and optimize manual processes. Oil and gas companies experience several unplanned incidences, such as pipe leakage and energy grid failure, which cost millions to them.
The predictive maintenance market is analyzed on the basis of component, deployment type, technique, and industry. Based on component, the market is segmented into solutions and services. Based on deployment type, the market is bifurcated into cloud and on-premise. Based on technique, the market is segmented into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. Based on industry, the predictive maintenance market is segmented into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, oil & gas, and others.
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Predictive Maintenance Market: Competitive Landscape
- General Electric Company
- Hitachi, Ltd.
- IBM Corporation
- Microsoft Corporation
- PTC Inc.
- SAS Institute, Inc.
- Schneider Electric SE
- Software AG
- Syncron AB
- TOSL Engineering Limited
Market Insights – Predictive Maintenance Market
In the manufacturing industry, manufacturers had to rely on a reactive maintenance model to repair only after the failure of a particular unit, which caused a high maintenance cost and paralyzed long periods of unscheduled downtime. Hence, these factors inevitably led to a lower quality output produced. With predictive maintenance models integrated into IoT and IIoT, manufacturing industry players can significantly reduce costs by eliminating the need for unnecessarily frequent maintenance. Hence, manufacturing companies are comprehensively integrating predictive maintenance models to identify and predict potential problems given the specific information extracted from each unit, thereby maintaining overall manufacturing health in the process.
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Deployment Type-Based Insights
The predictive maintenance market, by deployment type, is segmented into cloud and on-premise. Cloud is expected to remain the largest segment during the forecast period. The cloud segment is growing considerably due to several advantageous characteristics, such as scalability and cost-effectiveness, which are expected to propel the growth of the predictive maintenance market during the forecast period. The growth of this segment can also be attributed to faster data processing and direct IT control, the efficient use of resources, and the cost-effectiveness of cloud models.
Predictive maintenance enables these companies to rely on Industrial Internet of Things (IIoT)-enabled technologies, such as sensor data, and use predictive analytics for real-time equipment inspections, which helps reduce maintenance costs and unplanned equipment downtime. These factors are collectively driving the growth of predictive maintenance market size globally.
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Based on geography, the predictive maintenance market is segmented into North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and South America (SAM).
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