Global Predictive Maintenance Market by Component (Software, Services); by Deployment Type (Cloud, On-premise); by Technique (Electrical Testing, Vibration Monitoring, Oil Analysis, Others); by End User Industry (Energy and Utilities, Government and Defense, Transportation and Logistics, Manufacturing, Healthcare and Life Sciences, others); and by Region (North America, Europe, Asia Pacific, Latin America, MEA), - Global Forecasts 2021 to 2027

The Global Predictive Maintenance Market was valued USD 4.1Bn in 2020 and is expected to reach USD 21.2 Bn by 2027, with a growing CAGR of 26.1% during the forecast period.

The Global Predictive Maintenance Market Definition:

Predictive maintenance also termed conditional maintenance or condition-based maintenance is a machinery monitoring and performance controlling system. Predictive maintenance-based solutions help enterprises identify patterns in continuous data streams to predict equipment failures.

The predictive maintenance depends on sensors to detect the equipment condition during normal operations to avoid failures. The sensors detect and supply data to the system in real-time which is then used to analyze the need for asset maintenance.

The Global Predictive Maintenance Market Snapshot:

Predictive Maintenance Market

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The Global Predictive Maintenance Market Dynamics:

The predictive maintenance market is accounted to grow at a significant rate in the forecast period. The growth is attributed to the need to increase uptime of assets and minimize maintenance costs. The Occupational Health and Safety Administration (OSHA), a government agency, has a set of stringent rules, regulations, and guidelines to be followed regarding the predictive maintenance in the industrial manufacturing plants. Therefore, predictive maintenance is a crucial thing to apply in a workplace. Moreover, increasing prevalence of sensors in machinery, vehicles, production plants, among others hard equipment spaces are boosting up the global predictive maintenance market in the forecast period. For instance, in March 2019, Senseye, a leading provider of predictive maintenance analytics, announced a launch of its award-winning monitoring and prognosis software. This software is expected to be available as a base application on MindSphere, Siemens' open cloud-based Internet of Things (IoT) operating system. The software analyses the possible damage automatically with the help of sensors installed in the machinery.

Furthermore, physical equipment can be digitized and be monitored by artificial intelligence. AI-based IoT solutions provide predictive maintenance applications that allow enterprises to predict equipment failures in advance. For instance, in February 2018, the IBM announced a new portfolio of Internet of Things (IoT) solutions that combines with advanced analytics and artificial intelligence to assist in improving maintenance strategies.

The Global Predictive Maintenance Market Segmentation:

  • By Component
    • Software
      • Integrated
      • Standalone
    • Services
      • Managed Services
      • Professional Services
  • By Deployment Type
    • Cloud
      • Public Cloud
      • Private Cloud
      • Hybrid Cloud
    • On-premise          
  • By Technique
    • Vibration Monitoring
    • Oil Analysis
    • Electrical Testing
    • Others (Shock Pulse, Ultrasonic Leak Detectors, Infrared)
  • By End User Industry
    • Energy and Utilities
    • Government and Defense
    • Transportation and Logistics
    • Manufacturing
    • Healthcare and Life Sciences
    • Others (Telecom, Agriculture, Retail, and Media)
  • By Region
    • Asia Pacific
    • North America
    • Latin America
    • Europe
    • Middle East & Africa

Company Profiles and Competitive Intelligence

The key players operating in the predictive maintenance market are:

  1. Bosch Software Innovations GmbH
  2. IBM Corporation
  3. Honeywell International, Inc.
  4. Microsoft
  5. Hitachi Ltd.
  6. Software AG
  7. General Electric
  8. Engineering Consultants Group, Inc.
  9. Software AG
  10. Expert Microsystems, Inc.
  11. Rockwell Automation, Inc.
  12. Google
  13. C3 IoT
  14. Uptake
  15. Softweb Solutions
  16. TIBCO Software Inc.
  17. Asystom
  18. Uptake Technologies Inc.
  19. Ecolibrium Energy
  20. Fiix Software
  21. Opeational Excellence (Opex) Group Ltd
  22. Reliability Solutions Sp. zo.o.
  23. Dingo
  24. Sigma Industrial Precision
  25. SparkCognition
  26. Oracle
  27. HPE
  28. Rapidminer, Inc.
  29. AWS
  30. SKF Group
  31. Micro Focus
  32. Splunk
  33. Senseye Ltd
  34. Altair
  35. RapidMiner
  36. Warwick Analytics
  37. ReliaSol
  38. Seebo
  39. Softweb Solutions, Inc.
  40. T-Systems International GmbH
  41. Dell Technologies
  42. Fluke Corporation

The unique insight provided by this report also includes the following:

  1. In-Depth Value Chain Analysis
  2. Sector Snapshot
  3. Opportunity Mapping
  4. Key Players Positioning Matrix
  5. Strategies Adopted-Benchmarking Heat Map
  6. Market Trends
  7. Regulatory Scenario
  8. Covid-19 Impact Analysis
  9. Product Comparison
  10. Pre & Post COVID 19 Impact On Predictive Maintenance Market
  11. Competitive Landscape

Based on deployment type, the cloud deployment type segment is expanding at a significant growth rate during the forecast period owing to advantages provided by cloud deployment segment

The cloud-based predictive maintenance segment was expected to dominate the overall preventive maintenance market size in 2020 and will remain dominant during the forecast period mainly owing to their benefits, such as cost-effectiveness, easy maintenance of generated data, effective management, and scalability. According to Globaltrademag, the level of physical security at the data centers of large-sized cloud computing providers, cloud deployments are often more secure compared to on-premise deployments.

Based on the end user industry, the manufacturing accounted for a largest market share in the overall predictive maintenance market size owing to the increasing demand for equipment maintenance challenges, followed by the energy and utility sector

The manufacturing sector dominates the global predictive maintenance market share in 2020 owing to escalating maintenance challenges for manufacturing equipment such as pumps, machines, industrial robots, elevators, etc., and the enhanced usage of predictive maintenance solutions. For instance, since August 2021, the BMW automobile company is implementing cloud-based predictive maintenance solutions across its global network for its production systems to enhance their efficiency and sustainability.

Based on regions, the predictive maintenance market in North America accounted for the largest share in 2020 owing to extensive presence of manufacturing and energy & utility industries, followed by Asia Pacific and Europe

Geographically, the North American region was accounted to hold the largest market share in the year 2020. The reason behind North America being the largest market segment is the extensive presence of energy & utility and manufacturing sectorial plants leading to an increased usage of predictive maintenance solutions and services in the region. According to the Terra Staffing Group report March 2021, there has been a decline in manufacturing in the U.S. during the covid-19 outbreak but is anticipated to grow significantly in the coming few years, thus driving the regional growth.

Moreover, the Asia Pacific region is accounted to grow at the highest growth rate owing to the enormous investments by both private and public organizations to enhance the maintenance solution. In August 2021, Baker Hughes' Bently Nevada, a major company in asset protection and condition monitoring shared a plan to open a remote monitoring center (RMC) in Singapore. This would be the first RMC for Bently Nevada in the Asia Pacific region and the eighth in the world to support services in English, Mandarin, and Malay.

The report also provides an in-depth analysis of predictive maintenance market dynamics such as drivers, restraints opportunities and challenges


  • Growing usage of emerging technologies to achieve valuable insights
  • Increasing needs to lessen the maintenance cost and downtime


  • High primary investments
  • Lack of skilled workforce


  • Real-time condition monitoring to help take immediate actions
  • Increases the need for remote monitoring and management of assets and business processes owing to COVID19 outbreak

Note: Challenges along with in-depth market dynamics analysis is mentioned in the report.

COVID-19 Impact on the Predictive maintenance Market Analysis

The impact of COVID-19 has greatly affected the predictive maintenance market. The global ICT spending was estimated to decline by 4%-5% owing to covid-19 impact. The hardware sector is predicted to have the most impact.  The slowdown has caused both positive and negative impact on the predictive maintenance market. Some of the production plants have completely shut down causing a negative impact on predictive maintenance market. Whereas, some companies try to maintain the machinery in running quality as there is a lack of personnel and disrupted supply chain during the shutdown due to covid-19 outbreak.

Many companies are starting to use advanced artificial intelligence systems, smart sensors, and other Industrial Internet of Things (IIoT) solutions to trace the health and efficiency of crucial equipment used in manufacturing processes and avoid costly production downtime. Preventive maintenance solutions allow businesses to handle routine monitoring, simple machine troubleshooting, and other tasks that can make up for limited availability during the COVID-19 epidemic.

The report also provides an in-depth analysis of key trends in the predictive maintenance market

Sr. No. Trends Impact
1 The increasing stringency in regulations regarding the incorporation of predictive maintenance solutions in the industry plants is accounted to propel the predictive maintenance market growth Positive
2 The increasing prevalence of incorporating artificial intelligence and machine learning in the predictive maintenance software and solutions is anticipated to boost the global predictive maintenance market in the forecast period Positive

The report also provides an in-depth analysis of recent news developments and investments

  1. In May 2019, NXP Semiconductors N.V. announced a strategic collaboration with Microsoft to bring out edge-to-cloud machine learning solutions for predictive maintenance market. The collaboration is aimed to bring Machine Learning (ML) and Artificial Intelligence (AI) capabilities to detect abnormality for Azure IoT users.
  2. In March 2019, TIBCO Software Inc. announced its successful acquisition over SnappyData, a high performance in-memory data platform for mixed workload applications. The acquisition is aimed to benefit the TIBCO connected intelligence platform with an unified data fabric which was expected to enhance data management, data science, analytics, and streaming.

Frequently Asked Questions (FAQs)

The global predictive maintenance market was valued at USD 4.1 Bn in 2020 and is anticipated to reach USD 21.2 Bn by 2027.

The predictive maintenance market is estimated to grow at a Compound Annual Growth Rate (CAGR) of 26.1% during the forecast period.

In the base year 2020, North America accounted for largest market share in the predictive maintenance market

A few key players include, but not limited to: Bosch Software Innovations GmbH, IBM Corporation, Honeywell International, Inc., Microsoft, Hitachi Ltd., Software AG, General Electric, Engineering Consultants Group, Inc., Software AG, Expert Microsystems, Inc., Rockwell Automation, Inc., Google, C3 IoT, Uptake, and Softweb Solutions.

Yes, the report contains detailed COVID-19 analysis for predictive maintenance market.

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  1. Introduction
    1. Product outline
    2. Predictive maintenance market definition
    3. Different types of predictive maintenance  
    4. Analysis of predictive maintenance  ecosystem
    5. Supply chain analysis
    6. Covid -19 impact
    7. Market dynamics
      1. Drivers
      2. Restraints
      3. Opportunities
      4. Threats
    8. Technology overview
  2. Technology and Regulatory Landscape for Predictive Maintenance    
    1. Regulations and standards
  3. Predictive Maintenance  Market Pricing Analysis
    1. Prices of predictive maintenance   
  4. Predictive Maintenance  Market by Component
    1. Software
      1. Integrated
      2. Standalone
    2. Services
      1. Managed Services
      2. Professional Services
  5. Predictive maintenance  Market  by Deployment Type
    1. Cloud
      1. Public Cloud
      2. Private Cloud
      3. Hybrid Cloud
    2. On-premise
  6. Predictive maintenance  Market  by Technique
    1. Vibration Monitoring
    2. Oil Analysis
    3. Electrical Testing
    4. Others(Shock Pulse, Ultrasonic Leak Detectors, Infrared)
  7. Predictive maintenance  Market by End User Industry
    1. Energy and Utilities
    2. Government and Defense
    3. Transportation and Logistics
    4. Manufacturing
    5. Healthcare and Life Sciences
    6. Others (Telecom, Agriculture, Retail, and Media)
  8. Regional Analysis
    1. North America
      1. US
      2. Canada
      3. Mexico
    2. Europe
      1. Germany
      2. UK
      3. France
      4. Norway
      5. Italy
      6. Spain
      7. Netherlands
      8. Rest Of Europe
    3. Asia Pacific
      1. China
      2. India
      3. Japan
      4. Australia
      5. New Zealand
      6. Rest Of Asia Pacific
    4. Middle East and Africa
    5. South America
  9. Key Strategic Insights
    1. New applications
    2. Emerging technologies
    3. Opportunity mapping
    4. Critical success factors
    5. Environmental impact and sustainability issues
    6. Consumer preferences
  10. Key Market Trends / Recent Developments
  11. Competitive Scenario
    1. Competitive Strategies of Key Players
      1. Mergers and Acquisitions
      2. Investments
      3. Joint Ventures
      4. New Product launches
    2. Strength of product portfolio
    3. Ranking of Key Players
    4. Presence of players by Geographies
  12. Key Global Players
    1. Bosch Software Innovations GmbH
    2. IBM Corporation
    3. Honeywell International, Inc.
    4. Microsoft
    5. Hitachi Ltd.
    6. Software AG
    7. General Electric
    8. Engineering Consultants Group, Inc.
    9. Software AG
    10. Expert Microsystems, Inc.
    11. Rockwell Automation, Inc.
    12. Google
    13. C3 IoT
    14. Uptake
    15. Softweb Solutions

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