JERSEY CITY , N.J., Feb. 17, 2023 /PRNewswire/ — Verified Market Research recently published a report, “Predictive Maintenance Market” By Technology (Cloud-based, On Premise), By Component (Software, Services), By Application (Heavy Machinery, Small Machinery), By End-User (Government and Defense, Manufacturing, Energy and Utilities), and By Geography. According to Verified Market Research, the Global Predictive Maintenance Market size was valued at USD 3,881.47 Million in 2020 and is projected to reach USD 21,782.00 Million by 2028, growing at a CAGR of 24.45% from 2023 to 2028.
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Browse in-depth TOC on “Predictive Maintenance Market“
202 – Pages
126 – Tables
37 – Figures
Global Predictive Maintenance Market Overview
Predictive maintenance applications based on AI-based IoT solutions allow businesses to forecast equipment breakdowns ahead of time. Predictive maintenance solutions are gaining popularity as industrial clients become more conscious of the rising maintenance costs and downtime caused by unexpected machinery failures. Enterprises may use predictive maintenance-based systems to discover trends in continuous streams of data and forecast equipment breakdown. The ability to create predictions based on real-time analysis of underlying data allows for needs-based maintenance and, as a result, a decrease in downtime. Intelligent monitoring nodes are used in dedicated condition monitoring systems to apply adaptive and static rules to real-time condition data to deliver quick and local warnings. Local nodes also connect with a centralized website, allowing employees to evaluate real-time data as it happens.
Furthermore, interpreting sensor data necessitates a combination of real-time analysis and an in-memory database to provide faster data access than hard disc storage, promoting the adoption of real-time condition monitoring. However, companies may use the data to figure out their competitors’ business strategies and manufacturing schedules automatically, as well as hack and take control of devices. The growth in security and privacy problems is due to a lack of resources to apply AI techniques to IoT devices. Among the IoT’s security difficulties include insufficient authentication and authorization, unreliable network services, a lack of transport encryption, security configuration issues, and inadequate physical protection.
Key Developments
- June 2020, PTC has improved its ThingWorx Industrial IoT platform to speed up deployments of industrial IoT across the company value chain.
- February 2019, IBM has unveiled a new portfolio of IoT solutions that combine AI and sophisticated analytics to help asset-intensive enterprises, such as MARTA, optimize maintenance practices.
- February 2019, PTC has released a new version of ThingWorx, their award-winning Industrial Internet of Things (IIoT) solution platform.
- April 11, 2019, Schneider Electric, a global leader in energy management and automation, today announced the launch of Schneider Electric Exchange, the world’s first cross-industry open ecosystem dedicated to addressing real-world sustainability and efficiency concerns.
Key Players
The major players in the market are IBM, Robert Bosch GmbH, Software AG among others.
Verified Market Research has segmented the Global Predictive Maintenance Market On the basis of Technology, Component, Application, End-User, and Geography.
- Predictive Maintenance Market, By Technology
- Cloud-based
- On Premise
- Predictive Maintenance Market, By Component
- Software
- Services
- Predictive Maintenance Market, By End-User
- Government and Defense
- Manufacturing
- Energy and Utilities
- Transportation and Logistics
- Healthcare and Life Sciences
- Others
- Predictive Maintenance Market, By Application
- Heavy Machinery
- Small Machinery
- Others
- Predictive Maintenance Market By Geography
- North America
- U.S
- Canada
- Mexico
- Europe
- Germany
- France
- U.K
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- Rest of Asia Pacific
- ROW
- Middle East & Africa
- Latin America
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Top Computerized Maintenance Management System Software to track and control assets
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