Predictive Maintenance Market 2024 - By Size, Segmentation, Application, Outlook And Opportunities Analysis By 2033

The Business Research Company has updated its global market reports, featuring the latest data for 2024 and projections up to 2033

The Business Research Company offers in-depth market insights through Predictive Maintenance Global Market Report 2024, providing businesses with a competitive advantage by thoroughly analyzing the market structure, including estimates for numerous segments and sub-segments.

Market Size And Growth Forecast:
The predictive maintenance market size has grown exponentially in recent years. It will grow from $7.36 billion in 2023 to $9.49 billion in 2024 at a compound annual growth rate (CAGR) of 28.8%. The growth in the historic period can be attributed to equipment downtime reduction, cost savings, regulatory compliance and safety standards.

The predictive maintenance market size is expected to see exponential growth in the next few years. It will grow to $25.68 billion in 2028 at a compound annual growth rate (CAGR) of 28.3%. The growth in the forecast period can be attributed to integration with enterprise systems, predictive analytics for complex systems, focus on proactive maintenance strategies. Major trends in the forecast period include digital twin technology, cross-industry collaboration, advancements in sensor technologies, advanced analytics and machine learning, cloud-based solutions.

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Market Segmentation:
The predictive maintenance market covered in this report is segmented -
1) By Component: Solutions, Service
2) By Deployment Mode: On-premises, Cloud
3) By Stakeholder: MRO, OEM/ODM, Technology Integrators
4) By Application: Heavy Machinery, Small Machinery, Other Applications
5) By End User: Aerospace & Defense, Automotive & Transportation, Energy & Utilities, Healthcare, IT & Telecommunication, Manufacturing, Oil & Gas, Other End Users

Major Driver - Rising Focus On Predictive Maintenance To Minimize Equipment Downtime And Cut Maintenance Costs
The growing demand to reduce maintenance costs, equipment failure and downtime is significantly contributing to the growth of the predictive maintenance market. Equipment downtime refers to the duration in which particular equipment is not in operation due to unplanned equipment failure. Frequent equipment failure and unplanned downtime of large equipment are hampering the business operations due to a temporary halt of production activities, idle staff time, financial penalties, and others. For instance, according to the study published in Senseye Ltd., a UK-based provider of AI-driven predictive maintenance software, in June 2021, each production plant is losing $172 million per annum due to unplanned downtime. Thus, these manufacturing units are investing in advanced technologies to mitigate the probable unprecedented downtime of machinery in the plant. Therefore, growing demand to reduce maintenance costs, equipment failure, and downtime is expected to boost demand for predictive maintenance during the forecast period.

Competitive Landscape:
Major companies operating in the predictive maintenance market report are Google LLC, Microsoft Corporation, Hitachi Ltd., Amazon Web Services Inc., Siemens AG, General Electric Company, International Business Machines Corporation, Cisco Systems Inc., Oracle Corporation, Schneider Electric SE, OPEX Group Ltd., SAP SE, Hewlett Packard Enterprise Company, SAS Institute Inc., Splunk Inc., Larsen & Toubro Infotech Limited, PTC Inc., TIBCO Software Inc., Fluke Corporation, Software AG, Banner Engineering Corporation, Altair Engineering Inc., C3.ai Inc., Axiomtek Co Ltd., SparkCognition Inc., Uptake Technologies Inc., RapidMiner Inc., Dingo Inc., Factory Five Racing Inc., Senseye Ltd., Aspen Technology Inc., Dassault Systèmes SE, Rockwell Automation Inc., Honeywell International Inc.

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Top Trend - Advancements In Predictive Maintenance With The Introduction Of AI-Powered Solutions
Major companies operating in the predictive maintenance market are increasing their focus on introducing advanced solutions, such as the Asset Risk Predictor, to gain a competitive edge in the market. Asset Risk Predictor is a predictive maintenance solution that uses advanced analytics to assess and forecast the risk of equipment failure, helping industrial organizations optimize maintenance strategies and minimize downtime. For instance, in September 2023, Rockwell Automation Inc., a US-based automation company, launched its first artificial intelligence (AI) predictive maintenance software, Asset Risk Predictor. It uses artificial intelligence (AI) sensor data, machine recipes, and operational environments to predict asset health, which helps users spot and eliminate failures before they happen. The tool is capable of learning the signs of equipment failure and can predict breakdowns up to days in advance, allowing users to react to potential failures faster by automatically creating work orders in their computerized maintenance management system (CMMS).

The Table Of Content For The Market Report Include:
1. Executive Summary
2. Predictive Maintenance Market Characteristics
3. Predictive Maintenance Market Trends And Strategies
4. Predictive Maintenance Market - Macro Economic Scenario
5. Predictive Maintenance Market Size And Growth
…..
27. Predictive Maintenance Market Competitor Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
30. Appendix

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