According to a new report by Expert Market Research titled, “Global Predictive Maintenance Market Analysis, Growth, Size, Share, Report and Forecast 2024-2032″, the global predictive maintenance market reached a value of USD 4.83 billion in 2023. Aided by growing application of new technologies to gain valuable insights and increasing need to reduce the maintenance and downtime, the market is projected to further grow at a CAGR of 29.10% between 2024 and 2032 to reach a value of USD 22.3 billion by 2032.
Predictive maintenance, at its core, is a proactive maintenance strategy that utilises data analysis tools and techniques, such as artificial intelligence and machine learning, to predict when equipment failure might occur. This approach enables businesses to take corrective actions in advance, ensuring optimal operations and minimising disruptions. The primary goal is to allow timely maintenance, thus averting costly unplanned outages and extending the equipment’s life.
Integration of advanced technologies into maintenance strategies has become of the growing predictive maintenance market trends. Industries are recognising the power of data-driven insights to make informed decisions. Whether it is in manufacturing units, energy plants, or transportation hubs, the role of predictive algorithms and real-time analytics is becoming more pivotal, paving the way for more intelligent and cost-effective maintenance solutions.
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Further fuelling the predictive maintenance market growth is the continuous evolution of the Internet of Things (IoT). IoT devices, when integrated with predictive maintenance solutions, offer real-time monitoring of equipment health, providing invaluable insights into performance metrics. This seamless integration results in enhanced operational efficiency, resource optimisation, and significant cost savings for enterprises.
A strong demand for predictive maintenance from sectors that have high capital investments in machinery and equipment increasingly contributes to the predictive maintenance market size. Industries such as aerospace, energy, and manufacturing are adopting these advanced maintenance strategies as the cost implications of equipment failures in these sectors is expected to be monumental.
The predictive maintenance market analysis highlights the transformative impact of digitalisation across industries. Enterprises are actively seeking platforms and solutions that seamlessly blend sensor-based data, machine learning algorithms, and analytics tools. This quest for integrated platforms is not merely to detect anomalies but to forecast failures, plan interventions, and optimise asset performance throughout its lifecycle.
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Market Segmentation
The market can be divided based on component, deployment mode, organization size, application, and region.
Market Breakup by Component
• Solutions
• Services
Market Breakup by Deployment Mode
• Cloud
• On-Premises
Market Breakup by Organization Size
• Small and Medium-Sized Enterprises
• Large Enterprises
Market Breakup by Application
• Government and Defence
• Manufacturing
• Energy and Utilities
• Transportation and Logistics
• Healthcare and Life Sciences
• Others
Market Breakup by Region
• North America
• Europe
• Asia Pacific
• Latin America
• Middle East and Africa
Competitive Landscape
The EMR report looks into the market shares, plant turnarounds, capacities, investments, and mergers and acquisitions, among other major developments, of the leading companies operating in the global predictive maintenance market. Some of the major players explored in the report by Expert Market Research are as follows:
• Microsoft Corporation
• Hitachi, Ltd.
• Schneider Electric SE
• General Electric Company
• SAP SE
• International Business Machines Corporation
• Others
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