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 observed in the historical period can be attributed to the reduction of equipment downtime, cost savings, and adherence to 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 anticipated growth in the forecast period can be credited to the integration with enterprise systems, the application of predictive analytics for complex systems, and an emphasis on proactive maintenance strategies. Noteworthy trends expected in the forecast period encompass the adoption of digital twin technology, cross-industry collaboration, advancements in sensor technologies, the implementation of advanced analytics and machine learning, as well as the utilization of cloud-based solutions.
The significant drive to reduce maintenance costs, equipment failure, and downtime is a key factor contributing to the growth of the predictive maintenance market. Equipment downtime, which refers to the period during which specific equipment is not operational due to unplanned failure, poses challenges to business operations. Frequent equipment failures and unplanned downtime of large equipment can disrupt production activities, lead to idle staff time, incur financial penalties, and more. A study published by Senseye Ltd., a UK-based provider of AI-driven predictive maintenance software, in June 2021 revealed that each production plant loses an estimated $172 million annually due to unplanned downtime. Consequently, manufacturing units are investing in advanced technologies to mitigate the potential adverse effects of machinery downtime in the plant. Therefore, the growing demand to reduce maintenance costs, equipment failure, and downtime is anticipated to drive the demand for predictive maintenance throughout the forecast period.
The increasing adoption of the Internet of Things (IoT) is expected to propel further growth in the predictive maintenance market. IoT is a networked system of interconnected computing devices, mechanical and electronic machinery with unique identities (UIDs), capable of transferring data without requiring human-to-human or human-to-computer interaction. IoT devices in predictive maintenance facilitate real-time monitoring of equipment, data collection for analysis, proactive identification of potential issues, reduction of downtime, and optimization of maintenance schedules to enhance operational efficiency. According to the State of IoT - Spring 2022 report by IoT Analytics in May 2022, there were 12.2 billion active endpoints in 2021, marking an 8% increase in the total number of IoT connections. The IoT industry is projected to experience an 18% increase to reach 14.4 billion active connections in 2022. Hence, the growing adoption of IoT serves as a driving force for the predictive maintenance market.
The increasing adoption of advanced technology emerges as a prominent trend in the predictive maintenance market. Leading companies in this sector are directing their efforts towards delivering technologically advanced solutions to meet the evolving demands of end customers, thereby solidifying their market positions. These companies are integrating next-generation technologies, including IoT, AI (artificial intelligence), ML (machine learning), thermography, and cloud computing, into their services to align with the growing market need for enhanced maintenance capabilities. An illustration of this trend is evident in the actions of Avanseus, a Singapore-based provider of predictive maintenance and intelligent monitoring solutions. In December 2021, Avanseus introduced an AI-based predictive maintenance solution within the operations of Bharti Airtel, a prominent Indian communications company. This solution leverages machine learning algorithms and artificial intelligence to proactively predict and prevent incidents in the network, supporting the pursuit of zero-fault, zero-touch networks.
Major players in the predictive maintenance market are intensifying their focus on introducing innovative solutions, such as the Asset Risk Predictor, to gain a competitive advantage. The Asset Risk Predictor employs advanced analytics to assess and forecast the risk of equipment failure, aiding industrial organizations in optimizing maintenance strategies and minimizing downtime. A case in point is the move by Rockwell Automation Inc., a US-based automation company, which, in September 2023, launched its inaugural artificial intelligence (AI) predictive maintenance software, Asset Risk Predictor. This software utilizes AI sensor data, machine recipes, and operational environments to predict asset health, enabling users to detect and address potential failures before they occur. The tool's capability to recognize signs of equipment failure allows it to predict breakdowns days in advance, facilitating quicker reactions by automatically generating work orders in the computerized maintenance management system (CMMS).
In June 2022, Siemens, a Germany-based technology company with a focus on industry, infrastructure, transport, and healthcare, acquired Senseye, a UK-based predictive maintenance solution provider, for an undisclosed amount. This acquisition positioned Senseye as a subsidiary of Siemens, bolstering Siemens' presence in the digital services portfolio.
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.
North America was the largest region in the predictive maintenance market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the predictive maintenance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the predictive maintenance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Predictive maintenance is categorized into solutions and services. Predictive maintenance solutions refer to custom-designed software or platforms for asset management, tailored to unique business requirements and operating on Internet of Things (IoT) technology. These solutions are deployed on both on-premise and cloud infrastructure, catering to stakeholders such as MRO, OEM/ODM, and technology integrators. They find applications in heavy machinery, small machinery, and various industries, including aerospace & defense, automotive & transportation, energy & utilities, healthcare, IT & telecommunication, manufacturing, oil & gas, and others.
The predictive maintenance market research report is one of a series of new reports that provides predictive maintenance market statistics, including the predictive maintenance industry global market size, regional shares, competitors with a predictive maintenance market share, detailed predictive maintenance market segments, market trends and opportunities, and any further data you may need to thrive in the predictive maintenance industry. This predictive maintenance market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.
The predictive maintenance market includes revenues earned by entities by providing services such as monitoring equipment, failure mode, and condition. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 3-5 business days.
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 anticipated growth in the forecast period can be credited to the integration with enterprise systems, the application of predictive analytics for complex systems, and an emphasis on proactive maintenance strategies. Noteworthy trends expected in the forecast period encompass the adoption of digital twin technology, cross-industry collaboration, advancements in sensor technologies, the implementation of advanced analytics and machine learning, as well as the utilization of cloud-based solutions.
The significant drive to reduce maintenance costs, equipment failure, and downtime is a key factor contributing to the growth of the predictive maintenance market. Equipment downtime, which refers to the period during which specific equipment is not operational due to unplanned failure, poses challenges to business operations. Frequent equipment failures and unplanned downtime of large equipment can disrupt production activities, lead to idle staff time, incur financial penalties, and more. A study published by Senseye Ltd., a UK-based provider of AI-driven predictive maintenance software, in June 2021 revealed that each production plant loses an estimated $172 million annually due to unplanned downtime. Consequently, manufacturing units are investing in advanced technologies to mitigate the potential adverse effects of machinery downtime in the plant. Therefore, the growing demand to reduce maintenance costs, equipment failure, and downtime is anticipated to drive the demand for predictive maintenance throughout the forecast period.
The increasing adoption of the Internet of Things (IoT) is expected to propel further growth in the predictive maintenance market. IoT is a networked system of interconnected computing devices, mechanical and electronic machinery with unique identities (UIDs), capable of transferring data without requiring human-to-human or human-to-computer interaction. IoT devices in predictive maintenance facilitate real-time monitoring of equipment, data collection for analysis, proactive identification of potential issues, reduction of downtime, and optimization of maintenance schedules to enhance operational efficiency. According to the State of IoT - Spring 2022 report by IoT Analytics in May 2022, there were 12.2 billion active endpoints in 2021, marking an 8% increase in the total number of IoT connections. The IoT industry is projected to experience an 18% increase to reach 14.4 billion active connections in 2022. Hence, the growing adoption of IoT serves as a driving force for the predictive maintenance market.
The increasing adoption of advanced technology emerges as a prominent trend in the predictive maintenance market. Leading companies in this sector are directing their efforts towards delivering technologically advanced solutions to meet the evolving demands of end customers, thereby solidifying their market positions. These companies are integrating next-generation technologies, including IoT, AI (artificial intelligence), ML (machine learning), thermography, and cloud computing, into their services to align with the growing market need for enhanced maintenance capabilities. An illustration of this trend is evident in the actions of Avanseus, a Singapore-based provider of predictive maintenance and intelligent monitoring solutions. In December 2021, Avanseus introduced an AI-based predictive maintenance solution within the operations of Bharti Airtel, a prominent Indian communications company. This solution leverages machine learning algorithms and artificial intelligence to proactively predict and prevent incidents in the network, supporting the pursuit of zero-fault, zero-touch networks.
Major players in the predictive maintenance market are intensifying their focus on introducing innovative solutions, such as the Asset Risk Predictor, to gain a competitive advantage. The Asset Risk Predictor employs advanced analytics to assess and forecast the risk of equipment failure, aiding industrial organizations in optimizing maintenance strategies and minimizing downtime. A case in point is the move by Rockwell Automation Inc., a US-based automation company, which, in September 2023, launched its inaugural artificial intelligence (AI) predictive maintenance software, Asset Risk Predictor. This software utilizes AI sensor data, machine recipes, and operational environments to predict asset health, enabling users to detect and address potential failures before they occur. The tool's capability to recognize signs of equipment failure allows it to predict breakdowns days in advance, facilitating quicker reactions by automatically generating work orders in the computerized maintenance management system (CMMS).
In June 2022, Siemens, a Germany-based technology company with a focus on industry, infrastructure, transport, and healthcare, acquired Senseye, a UK-based predictive maintenance solution provider, for an undisclosed amount. This acquisition positioned Senseye as a subsidiary of Siemens, bolstering Siemens' presence in the digital services portfolio.
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.
North America was the largest region in the predictive maintenance market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the predictive maintenance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the predictive maintenance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Predictive maintenance is categorized into solutions and services. Predictive maintenance solutions refer to custom-designed software or platforms for asset management, tailored to unique business requirements and operating on Internet of Things (IoT) technology. These solutions are deployed on both on-premise and cloud infrastructure, catering to stakeholders such as MRO, OEM/ODM, and technology integrators. They find applications in heavy machinery, small machinery, and various industries, including aerospace & defense, automotive & transportation, energy & utilities, healthcare, IT & telecommunication, manufacturing, oil & gas, and others.
The predictive maintenance market research report is one of a series of new reports that provides predictive maintenance market statistics, including the predictive maintenance industry global market size, regional shares, competitors with a predictive maintenance market share, detailed predictive maintenance market segments, market trends and opportunities, and any further data you may need to thrive in the predictive maintenance industry. This predictive maintenance market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.
The predictive maintenance market includes revenues earned by entities by providing services such as monitoring equipment, failure mode, and condition. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
This product will be delivered within 3-5 business days.
Table of Contents
1. Executive Summary2. Predictive Maintenance Market Characteristics3. Predictive Maintenance Market Trends and Strategies32. Global Predictive Maintenance Market Competitive Benchmarking33. Global Predictive Maintenance Market Competitive Dashboard34. Key Mergers and Acquisitions in the Predictive Maintenance Market
4. Predictive Maintenance Market - Macro Economic Scenario
5. Global Predictive Maintenance Market Size and Growth
6. Predictive Maintenance Market Segmentation
7. Predictive Maintenance Market Regional and Country Analysis
8. Asia-Pacific Predictive Maintenance Market
9. China Predictive Maintenance Market
10. India Predictive Maintenance Market
11. Japan Predictive Maintenance Market
12. Australia Predictive Maintenance Market
13. Indonesia Predictive Maintenance Market
14. South Korea Predictive Maintenance Market
15. Western Europe Predictive Maintenance Market
16. UK Predictive Maintenance Market
17. Germany Predictive Maintenance Market
18. France Predictive Maintenance Market
19. Italy Predictive Maintenance Market
20. Spain Predictive Maintenance Market
21. Eastern Europe Predictive Maintenance Market
22. Russia Predictive Maintenance Market
23. North America Predictive Maintenance Market
24. USA Predictive Maintenance Market
25. Canada Predictive Maintenance Market
26. South America Predictive Maintenance Market
27. Brazil Predictive Maintenance Market
28. Middle East Predictive Maintenance Market
29. Africa Predictive Maintenance Market
30. Predictive Maintenance Market Competitive Landscape and Company Profiles
31. Predictive Maintenance Market Other Major and Innovative Companies
35. Predictive Maintenance Market Future Outlook and Potential Analysis
36. Appendix
Executive Summary
Predictive Maintenance Global Market Report 2024 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses on predictive maintenance market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
Reasons to Purchase
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- Understand customers based on the latest market shares.
- Benchmark performance against key competitors.
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- Report will be updated with the latest data and delivered to you with an Excel data sheet for easy data extraction and analysis.
- All data from the report will also be delivered in an excel dashboard format.
Where is the largest and fastest growing market for predictive maintenance? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? This report answers all these questions and many more.
The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include:
- The impact of sanctions, supply chain disruptions, and altered demand for goods and services due to the Russian Ukraine war, impacting various macro-economic factors and parameters in the Eastern European region and its subsequent effect on global markets.
- The impact of higher inflation in many countries and the resulting spike in interest rates.
- The continued but declining impact of COVID-19 on supply chains and consumption patterns.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.
Report Scope
Markets Covered: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
Key Companies Mentioned: Google LLC; Microsoft Corporation; Hitachi Ltd.; Amazon Web Services Inc.; Siemens AG
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes
Delivery Format: PDF, Word and Excel Data Dashboard
Companies Mentioned
- 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.
Methodology
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