The global predictive maintenance market reached a value of US$ 5.95 Billion in 2021. Looking forward, IMARC Group expects the market to reach a value of US$ 28.44 Billion by 2027, exhibiting a CAGR of 27.60% during 2022-2027. Keeping in mind the uncertainties of COVID-19, we are continuously tracking and evaluating the direct as well as the indirect influence of the pandemic on different end use industries. These insights are included in the report as a major market contributor.

Predictive maintenance is a technology that relies on condition-monitoring tools and devices to track the functioning of equipment during an operation. It has sensors for recording a wide range of data, such as temperature, vibrations, and conductivity, which enables an engineer to predict the failure of an asset while allowing it to be repaired or replaced in advance. It helps maximize the life of an asset and reduce maintenance costs and equipment downtime. As a result, predictive maintenance finds extensive applications in the manufacturing, energy and utilities, aerospace, defense, transportation and logistics, and healthcare industries worldwide. Predictive Maintenance Market Trends:
At present, there is a rise in the utilization of machine-to-machine (M2M) communication and cloud technology to investigate the information derived from industrial assets across the globe. This, along with the growing employment of artificial intelligence (AI) technology to transform a considerable volume of data produced by various components of the internet of things (IoT) ecosystem into meaningful insights, represents one of the key factors driving the market. Besides this, increasing investments in predictive maintenance to extend the lifespan of aging industrial machinery is propelling the growth of the market around the world. In addition, the rising demand for predictive maintenance to track remote working and asset management is offering lucrative growth opportunities to industry investors and key market players. Moreover, the growing applications of predictive maintenance in X-ray, tomography and mammography to improve decision-making capabilities and operational efficiencies are positively influencing the market. Apart from this, the increasing adoption of real-time streaming analytics technology in various organizations to process and analyze data records continuously is bolstering the growth of the market.

Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global predictive maintenance market, along with forecasts at the global, regional and country level from 2022-2027. Our report has categorized the market based on component, technique, deployment type, organization size and industry vertical.

Breakup by Component:

Solution
Service

Breakup by Technique: Vibration Monitoring
Electrical Testing
Oil Analysis
Ultrasonic Leak Detectors
Shock Pulse
Infrared
Others

Breakup by Deployment Type:

Cloud-based
On-premises

Breakup by Organization Size:

Small and Medium-sized Enterprises
Large Enterprises

Breakup by Industry Vertical:

Manufacturing
Energy and Utilities
Aerospace and Defense
Transportation and Logistics
Government
Healthcare
Others

Breakup by Region: North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa

Competitive Landscape:
The competitive landscape of the industry has also been examined along with the profiles of the key players being Asystom, C3.ai Inc., General Electric Company, Google LLC (Alphabet Inc.), Hitachi Ltd., International Business Machines Corporation, Microsoft Corporation, PTC Inc., SAP SE, Software AG, Tibco Software Inc. and Uptake Technologies Inc. Key Questions Answered in This Report:
How has the global predictive maintenance market performed so far and how will it perform in the coming years?
What has been the impact of COVID-19 on the global predictive maintenance market?
What are the key regional markets?
What is the breakup of the market based on the component?
What is the breakup of the market based on the technique?
What is the breakup of the market based on the deployment type?
What is the breakup of the market based on the organization size?
What is the breakup of the market based on the industry vertical?
What are the various stages in the value chain of the industry?
What are the key driving factors and challenges in the industry?
What is the structure of the global predictive maintenance market and who are the key players?
What is the degree of competition in the industry?