IMARC Group, a leading market research company, has recently releases report titled “Predictive Maintenance Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028.” The study provides a detailed analysis of the industry, including the global predictive maintenance market size, growth, share, trends, and forecasts. The report also includes competitor and regional analysis and highlights the latest advancements in the market.

Industry Overview of Predictive Maintenance

Predictive maintenance refers to a technique that relies on condition-monitoring tools and systems to monitor equipment performance during operation. It incorporates the internet of things (IoT), artificial intelligence (AI), and integrated systems to connect various assets and systems, enabling the sharing and analysis of critical data. Additionally, it encompasses predictive maintenance sensors, industrial controls, and business systems like enterprise asset management (EAM) and enterprise resource planning (ERP) software. By utilizing condition monitoring equipment, it examines and evaluates asset performance, recording data such as temperature, vibrations, and conductivity. This data allows engineers to predict equipment or asset failure, enabling timely replacement or repair. Ultimately, predictive maintenance reduces maintenance costs, extends equipment lifespan, enhances productivity, and gains popularity due to its safety compliance and preemptive corrective actions worldwide.

How Big Is the Predictive Maintenance Market?

The global predictive maintenance market size reached US$ 8.0 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 35.9 Billion by 2028, exhibiting a growth rate (CAGR) of 27.54% during 2023-2028.

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What are the growth prospects and trends in the predictive maintenance industry?

The current market is experiencing a surge in demand for predictive maintenance, primarily driven by the automation of operations in diverse industrial assets. This trend has a positive impact on the market. Furthermore, the use of machine-to-machine (M2M) communication and cloud technology to analyze a wide range of data obtained from industrial and business assets is creating a favorable market environment.

Technicians are increasingly adopting predictive maintenance to plan and prepare for repairs, ensuring smooth production cycles and minimizing unplanned downtime. Moreover, businesses are embracing predictive maintenance to achieve a tangible return on investment (ROI) and extend the lifespan of aging industrial machinery.

Additionally, the integration of predictive maintenance with remote monitoring enables advanced inspections and accurate predictions of component and equipment failures, driving market growth. In the healthcare sector, predictive maintenance is employed to enhance the reliability of healthcare infrastructure, which is further contributing to market expansion.

What is included in market segmentation?

The report has segmented the market into the following categories:

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

Who are the key players operating in the industry?

The report covers the major market players including:

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., Uptake Technologies Inc.

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