Predictive Maintenance Market to Reach US$ 45.5 Billion at a CAGR of 21.1% by 2032

Predictive Maintenance Market Is Thriving, Driven By the Widespread Adoption of Artificial Intelligence (AI)and Machine Learning (ML) Technologies

ROCKVILLE, MARYLAND, UNITED STATES, October 5, 2023 /EINPresswire.com/ -- As per the analysis, the Predictive Maintenance Market Size in the United States is poised to take the lead in the global market. Projections suggest that the U.S. will secure a market value of approximately US$ 15.8 Million by the year 2032. This growth can be primarily attributed to the presence of well-established industry players within the region.

Furthermore, the global predictive maintenance market is expected to witness significant expansion, with an absolute dollar growth estimated at US$ 39.3 Billion by 2032. The driving force behind this growth is the escalating demand for reducing operation and maintenance costs. Besides, aerospace and defense, energy and utilities, manufacturing, oil & gas transportation, healthcare, and life sciences are other sectors generating significant demand for predictive maintenance. Players in the market are also taking various efforts to strengthen the industry.

For more insights into the Market, Request a Sample of this Report:
https://www.factmr.com/connectus/sample?flag=S&rep_id=7492

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

Competition Analysis:

Key players in the global predictive maintenance market adopt various strategies to enhance their reach across the globe. Strategies such as; partnerships, collaborations, and acquisitions, among others, are some of those methods.  Recent developments in the industry are :

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.

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.

Key Players:

-IBM
-Microsoft Corporation
-Schneider Electric SE
-Hitachi, Ltd.
-General Electric Company

Factors Driving the Growth of the Predictive Maintenance Market:

Expanding Utilization of Modern Technologies to Amplify Market Expansion:

The continuous evolution of machine-to-machine (M2M) communication, big data analytics, and artificial intelligence has ushered in innovative approaches for extracting insights through AI-driven methods. Big data and data visualization play a pivotal role in unlocking fresh perspectives through offline analysis and batch processing.

Enterprises are integrating contemporary methodologies into their established logical frameworks to automate data interpretation and gain real-time insights from the data generated by IoT devices. These modern techniques provide organizations with advanced tools to dissect real-time data and identify diverse applications for IoT. Consequently, the market is poised to witness significant growth in the forecast period.

Market players are introducing groundbreaking products, expected to bolster the industry in the foreseeable future. For instance, in May 2022, Sensata Technologies, a US-based company, unveiled a novel asset monitoring solution enabling predictive maintenance for rotary assets and delivering actionable insights to plant managers. Such product launches are anticipated to drive market expansion in the forecast period.

Real-Time Condition Monitoring as a Catalyst for Market Expansion:

Continual advancements in big data and M2M communication enable real-time condition monitoring. Real-time data inputs from sensors, detectors, and regulatory parameters not only detect potential asset deterioration but also empower organizations to take immediate corrective actions. These dynamics are expected to contribute to market growth in the forthcoming period.

Asset management is gaining momentum across diverse sectors. Solution providers harnessing machine learning (ML) and artificial intelligence (AI) can transform vast volumes of customer-related data generated by IoT into actionable insights.

Innovative product launches by industry players are projected to drive market growth in the forecast period. For example, in July 2020, Altain introduced Altair Knowledge Studio—an ML and Predictive Maintenance Solution featuring Python code generation for predictive modeling, seamless data export to Altair Monarch (a leading data preparation tool), and support for R code 4.0 and higher. These developments are expected to augment the market's size in the coming period.

Get Customization on this Report for Specific Research Solutions:
https://www.factmr.com/connectus/sample?flag=RC&rep_id=7492

Key Segments Profiled in the Predictive Maintenance Market:

By 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
-Other Verticals (Agriculture, Telecom, Media, and Retail)

By Deployment Mode :
-Cloud-based 
-On-Premise

By Component :
-Predictive Maintenance Software
-Predictive Maintenance Services

By Region :
-North America
-Europe
-Asia Pacific
-Middle East and Africa
-Latin America

Check out more related studies published by Fact.MR Research:

Fleet Maintenance Software Market: The fleet maintenance software market is predicted to grow at an impressive CAGR of 9.2% during the forecast period covering 2022 to 2032. The fleet maintenance software market share is estimated to reach a value of nearly US$ 30.9 Billion by 2032, expanding from US$ 11.6 Billion in 2021.

Cloud-based Predictive Analytics Platform Market: The rise of big data and the focus on data that is more voluminous, which comes in more varieties and arrives more quickly, have led to the growth of the cloud-based predictive analytics platform market.

About Us:

We are a trusted research partner of 80% of fortune 1000 companies across the globe. We are consistently growing in the field of market research with more than 1000 reports published every year. The dedicated team of 400-plus analysts and consultants is committed to achieving the utmost level of our client’s satisfaction.

Contact:
US Sales Office:
11140 Rockville Pike
Suite 400
Rockville, MD 20852
United States

S. N. Jha
Fact.MR
+1 628-251-1583
email us here

Legal Disclaimer:

EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.