Deployment across Large Enterprises to remain Dominant in Predictive Maintenance Market: Fact.MR Report

 Development in big data and M2M communication allow condition monitoring in real-time. The real-time inputs from selectors, detectors, and other regulatory parameters would not only identify embryonic asset loss but also assist organizations in real-time and take prompt actions.

On the contrary, a lack of expertise and frequent maintenance is expected to hamper the market growth. Also, upgradation requirement is another cause limiting the market growth in the forecast period. However, the proliferation of customer channels and changing landscape of customer intelligence are expected to act as a significant counter to the impeding causes and boost the market growth during the forecast period.

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Key Takeaways from the Market Study

  • By deployment mode, the cloud segment is expected to dominate the predictive maintenance market while exhibiting a CAGR of 21.1% during the forecast period.
  • Based on organization size, the large enterprises segment is predicted to lead the predictive maintenance market and exhibit a CAGR of 21.4% by 2032
  • The predictive maintenance market in the U.S is projected to garner US$ 15.8 Billion by 2032
  • The predictive maintenance market in the U.K is anticipated to garner a market value of US$ 2 Billion during the forecast period
  • The Japanese predictive maintenance market is anticipated to garner US$ 2.6 Billion by 2032
  • The predictive maintenance in South Korea is projected to display a CAGR of 19.5% from 2022-to 2032

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Competition Analysis

Key players in the global predictive maintenance market include Microsoft Corporation, IBM, Schneider Electric SE, General Electric Company, and Hitachi, Ltd. Recent developments in the industry are:

  • In May 2022, Hitachi Ltd. announced the launch of Lumada Inspection Insights. Pioneered by Hitachi Energy and Hitachi Vantara, Lumada Inspection Insights allows customers to mechanize asset inspection, and support sustainability goals. The new solution addresses various causes of failures by implementing AI and Machine Learning to assess assets, risks, and the spectrum of image types.
  • In July 2021, Schneider Electric rolled out EcoStruxure ™ TriconexTM Safet View. It is assiduity’s first binary safety-and-cybersecurity-certified bypass and alarm operation software that enables drivers to see both the bypass status that affects the position of threat reduction in place, and the critical admonitions demanded to operate the factory safely when pitfalls are high.
  • In May 2022, Schneider Electric announced the launch of its new SureSeT MV switchgear offering for the market in North America. The new solution offers various benefits. The newly integrated characteristics offer insights into day-to-day operations for remote access and control of equipment health, predictive maintenance, and operational efficiency.

Key Segments Profiled in the Predictive Maintenance Market

  • Global Predictive Maintenance Market by Organization Size :
    • Predictive Maintenance for Large Enterprises
    • Predictive Maintenance for Small and Medium-Sized Enterprises
  • Global Predictive Maintenance Market by Vertical :
    • Predictive Maintenance in Government and Defense
    • Predictive Maintenance in Manufacturing
    • Predictive Maintenance in Energy and Utilities
    • Predictive Maintenance in Transportation and Logistics
    • Predictive Maintenance in Healthcare and Life Sciences
    • Predictive Maintenance in Other Verticals (Agriculture, Telecom, Media, and Retail)
  • Global Predictive Maintenance Market by Deployment Mode :
    • Cloud Predictive Maintenance
    • On-Premise Predictive Maintenance
  • Global Predictive Maintenance Market by Component :
    • Predictive Maintenance Software
    • Predictive Maintenance Services
  • Global Predictive Maintenance Market by Region :
    • North America
    • Europe
    • Asia Pacific
    • Middle East and Africa
    • Latin America

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More Valuable Insights 
Fact.MR, in its new offering, presents an unbiased analysis of the global predictive maintenance market, presenting a historical analysis from 2015 to 2021 and forecast statistics for the period of 2022-2032.

The study reveals essential insights on the basis of Organization Size (Large Enterprises, Small and Medium-Sized Enterprises), By Vertical (Government and Defense, Manufacturing, Energy and Utilities, Transportation and Logistics, Healthcare and Life Sciences, Others), By Deployment Mode (Cloud, On-Premises), By Component (Software, Services), and Region (North America, Latin America, Asia Pacific, Europe and the Middle East & Africa).

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