The global predictive maintenance market size was valued at USD 7.9 Billion in 2020 and is projected to reach USD 21.45 Billion by 2028, growing at a CAGR of 33% from 2021 to 2028.
Predictive maintenance (PdM) is a preventive maintenance method based on predictive analytics technology. The solutions are placed to monitor and detect equipment failures or anomalies, but they are only activated when a severe failure is imminent. This aids in the deployment of limited resources, the maximization of device or equipment uptime, the enhancement of quality and supply chain procedures, and the overall satisfaction of all stakeholders involved. Traditional and sophisticated approaches are used to monitor equipment, allowing maintenance of the gear to be scheduled before a failure occurs. These procedures include various testing and monitoring technologies for vibration monitoring, electrical insulation, infrared thermography, temperature monitoring, ultrasonic leak detection, and oil analysis. To analyze an asset's performance in real-time, most countries use predictive maintenance for condition monitoring. Predictive maintenance is a plan for monitoring equipment performance and condition that decreases the chance of failure under standard operating settings. The goal is to predict a loss and then strive to avert it through corrective maintenance. Whether or not they are required to foresee the need for maintenance, traditional methods depend on historical data regarding equipment performance and previous breakdowns or simply generating periodic maintenance schedules. On the other hand, modern predictive maintenance solutions constantly monitor equipment behavior to collect data in real-time and utilize advanced neural networks and artificial algorithms to decide and raise an alert when an equipment breakdown is likely to occur.
The need to maximize asset uptime and minimize maintenance costs, as a result of IoT adoption and the requirement to extend the lifespan of aging industrial gear, are the significant reasons driving the worldwide predictive maintenance market growth. Furthermore, as the need for insights from the installation of new technologies grows, so does the demand for predictive maintenance. Again, the growing demand to reduce maintenance costs and downtime is driving the market. Companies are using AI and ML technologies to analyze IoT data with greater precision, accuracy, and speed than traditional business intelligence solutions. With the introduction of predictive maintenance, businesses may generate operational forecasts up to 20 times faster and more accurately than threshold-based monitoring systems. Unplanned downtime caused by equipment failure can cost money in various industries, including industrial production and offshore oil and gas. AI-powered IoT solutions provide organizations with predictive maintenance apps that predict equipment breakdown in advance. Predictive maintenance solutions are gaining traction as industrial customers become more conscious of the rising maintenance costs and downtime caused by unexpected machinery failures. However, market development is limited by implementation hurdles, data security concerns, and a trained worker shortage. To install AI-based IoT technologies and skillsets, trained personnel must handle the most current software systems. As a result, existing employees must be instructed on how to operate new and improved methods. Furthermore, enterprises are quick to adopt new technology; however, they face a shortage of highly educated and proficient people. As the majority of global vendors organize predictive maintenance initiatives, the requirement for highly skilled personnel grows. Companies must develop competence in areas such as cybersecurity, networking, and application development. Real-time condition monitoring to aid in fast response will present the industry with a variety of growth prospects. Improved asset management is becoming increasingly important in practically every industry. Because IoT creates a massive amount of data from connected devices, solution providers equipped with AI and ML can collect and transform massive customer-related data into relevant insights. AI may also be connected with IoT devices to optimize many elements of service delivery, such as predictive maintenance and quality assessment, with no human intervention required. Real-time inputs from sensors, actuators, and other control factors would not only predict embryonic asset breakdowns. Still, they would also enable businesses to monitor in real-time and take prompt action.
This study delivers a comprehensive analysis of components, vertical, and region. The component segment includes solution and service. The solution segment held the largest market share. The increased need for customized solutions might be ascribed to the high demand for integrated solutions. Furthermore, as the popularity and awareness of these solutions have grown, so needs application-specific solutions from numerous industrial verticals. Integrated solutions are custom-made, while standalone solutions are standard/ready-made solutions provided by market participants. Standalone solutions do not allow for customization. However, because of their low cost, standalone solutions are often used by small and medium-sized businesses. Because of the growing demand for a single solution with numerous capabilities, integrated solutions are becoming more popular than standalone solutions. The vertical segment includes Manufacturing, Energy & Utilities, Healthcare, Automotive, Aerospace and Defense, Transportation. The Manufacturing segment holds the largest market share. The increasing need for maintenance of manufacturing equipment such as industrial robots, machinery, elevators, and pumps to reduce overall downtime is driving the adoption of predictive maintenance solutions and services in the manufacturing sector. Furthermore, increased production automation, combined with Industry 4.0, is expected to drive demand for these solutions to secure high-end equipment from harm.
The market has been divided into Europe, South America, North America, Asia Pacific, the Middle East, and Africa. North America holds the largest market in the market. Technological advancements across sectors increased IoT connectivity, and quick adoption of new technologies, and particularly machine learning, are some of the reasons driving the region's predictive maintenance market growth. Europe has the second-largest market share for preventative maintenance. Some of the factors driving market growth include increased IoT connection, more investment in predictive maintenance, and expansion in the automotive sector. The presence of enterprises such as Robert Bosch GmbH, Schneider Electric SA, and SAP SE in the region is driving preventive maintenance solutions.
The prominent players of the global preventive maintenance market are Oracle Corporation, Microsoft Corporation, XMPro, IBM Corporation, Axiomtek Co. Ltd, RapidMiner, SAP SE, Hitachi, Ltd, and Comtrade. IBM unveiled a new suite of IIOT (industrial internet of things) solutions for predictive maintenance in March 2019, utilizing advanced analytics and artificial intelligence technology. The answer will reduce the risk of physical asset failure connected with manufacturing robots, vehicles, turbines, electrical transformers, elevators, and mining equipment. Oracle announced the release of Oracle IoT Asset Monitoring Cloud Service Release 19.1.5 in March 2019. This version includes a digital twin simulator that can generate asset sensor simulations. The simulator can be used to design and test data patterns for sensors connected to an asset. Hitachi, Ltd. launched an AI-Assisted Predictive Maintenance Service for Petrochemical Plants in October 2018 to detect real-time operational issues. This assists petrochemical facilities in improving operational efficiency and maintenance duties. SAP announced the availability of the SAP Asset Strategy and Performance Management Solution in February 2018. This product expands on SAP's Leonardo IoT technology's capabilities. SAP Asset Strategy & Performance Management is the most recent addition to SAP's cloud asset management solutions, including SAP Asset Intelligence Network, SAP Predictive Engineering Insights, and SAP Predictive Maintenance and Service.
Preventive Maintenance Market Analysis and Forecast, Component
Preventive Maintenance Market Analysis and Forecast, Vertical
Preventive Maintenance Market Analysis and Forecast, Region
Report Description:
1. Introduction
1.1. Objectives of the Study
1.2. Market Definition
1.3. Research Scope
1.4. Currency
1.5. Key Target Audience
2. Research Methodology and Assumptions
3. Executive Summary
4. Premium Insights
4.1. Porter’s Five Forces Analysis
4.2. Value Chain Analysis
4.3. Top Investment Pockets
4.3.1. Market Attractiveness Analysis By Component
4.3.2. Market Attractiveness Analysis By Vertical
4.3.3. Market Attractiveness Analysis By Region
4.4. Industry Trends
5. Market Dynamics
5.1. Market Evaluation
5.2. Drivers
5.2.1. Increase in requirement for asset uptime
5.2.2. Growing demand for predictive maintenance
5.2.3. Increasing desire to reduce maintenance costs and downtime.
5.3. Restraints
5.3.1. Implementation challenges
5.3.2. Data security concerns
5.3.3. Skilled labor shortage
5.4. Opportunities
5.4.1. Real-time condition monitoring
5.4.2. Better asset management
6. Global Predictive Maintenance Market Analysis and Forecast, By Component
6.1. Segment Overview
6.2. Solution
6.3. Service
7. Global Predictive Maintenance Market Analysis and Forecast, By Vertical
7.1. Segment Overview
7.2. Manufacturing
7.3. Energy & Utilities
7.4. Healthcare
7.5. Automotive
7.6. Aerospace and Defense
7.7. Transportation
8. Global Predictive Maintenance Market Analysis and Forecast, By Regional Analysis
8.1. Segment Overview
8.2. North America
8.2.1. U.S.
8.2.2. Canada
8.2.3. Mexico
8.3. Europe
8.3.1. Germany
8.3.2. France
8.3.3. U.K.
8.3.4. Italy
8.3.5. Spain
8.4. Asia-Pacific
8.4.1. Japan
8.4.2. China
8.4.3. India
8.5. South America
8.5.1. Brazil
8.6. Middle East and Africa
8.6.1. UAE
8.6.2. South Africa
9. Global Predictive Maintenance Market-Competitive Landscape
9.1. Overview
9.2. Market Share of Key Players in Global Predictive Maintenance Market
9.2.1. Global Company Market Share
9.2.2. North America Company Market Share
9.2.3. Europe Company Market Share
9.2.4. APAC Company Market Share
9.3. Competitive Situations and Trends
9.3.1. Product Launches and Developments
9.3.2. Partnerships, Collaborations, and Agreements
9.3.3. Mergers & Acquisitions
9.3.4. Expansions
10. Company Profiles
10.1. Oracle Corporation
10.1.1. Business Overview
10.1.2. Company Snapshot
10.1.3. Company Market Share Analysis
10.1.4. Company Product Portfolio
10.1.5. Recent Developments
10.1.6. SWOT Analysis
10.2. Microsoft Corporation
10.2.1. Business Overview
10.2.2. Company Snapshot
10.2.3. Company Market Share Analysis
10.2.4. Company Product Portfolio
10.2.5. Recent Developments
10.2.6. SWOT Analysis
10.3. XMPro
10.3.1. Business Overview
10.3.2. Company Snapshot
10.3.3. Company Market Share Analysis
10.3.4. Company Product Portfolio
10.3.5. Recent Developments
10.3.6. SWOT Analysis
10.4. IBM Corporation
10.4.1. Business Overview
10.4.2. Company Snapshot
10.4.3. Company Market Share Analysis
10.4.4. Company Product Portfolio
10.4.5. Recent Developments
10.4.6. SWOT Analysis
10.5. Axiomtek Co. Ltd
10.5.1. Business Overview
10.5.2. Company Snapshot
10.5.3. Company Market Share Analysis
10.5.4. Company Product Portfolio
10.5.5. Recent Developments
10.5.6. SWOT Analysis
10.6. RapidMiner
10.6.1. Business Overview
10.6.2. Company Snapshot
10.6.3. Company Market Share Analysis
10.6.4. Company Product Portfolio
10.6.5. Recent Developments
10.6.6. SWOT Analysis
10.7. SAP SE
10.7.1. Business Overview
10.7.2. Company Snapshot
10.7.3. Company Market Share Analysis
10.7.4. Company Product Portfolio
10.7.5. Recent Developments
10.7.6. SWOT Analysis
10.8. Hitachi, Ltd
10.8.1. Business Overview
10.8.2. Company Snapshot
10.8.3. Company Market Share Analysis
10.8.4. Company Product Portfolio
10.8.5. Recent Developments
10.8.6. SWOT Analysis
10.9. Comtrade
10.9.1. Business Overview
10.9.2. Company Snapshot
10.9.3. Company Market Share Analysis
10.9.4. Company Product Portfolio
10.9.5. Recent Developments
10.9.6. SWOT Analysis
List of Table
1. Global Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
2. Global Solution, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
3. Global Service, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
4. Global Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
5. Global Manufacturing, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
6. Global Energy & Utilities, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
7. Global Healthcare, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
8. Global Automotive, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
9. Global Aerospace and Defense, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
10. Global Transportation, Predictive Maintenance Market, By Region, 2018-2028 (USD Billion)
11. North America Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
12. North America Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
13. U.S. Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
14. U.S. Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
15. Canada Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
16. Canada Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
17. Mexico Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
18. Mexico Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
19. Europe Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
20. Europe Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
21. Germany Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
22. Germany Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
23. France Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
24. France Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
25. U.K. Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
26. U.K. Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
27. Italy Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
28. Italy Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
29. Spain Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
30. Spain Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
31. Asia Pacific Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
32. Asia Pacific Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
33. Japan Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
34. Japan Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
35. China Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
36. China Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
37. India Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
38. India Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
39. South America Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
40. South America Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
41. Brazil Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
42. Brazil Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
43. Middle East and Africa Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
44. Middle East and Africa Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
45. UAE Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
46. UAE Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
47. South Africa Predictive Maintenance Market, By Component, 2018-2028 (USD Billion)
48. South Africa Predictive Maintenance Market, By Vertical, 2018-2028 (USD Billion)
List of Figures
1. Global Predictive Maintenance Market Segmentation
2. Global Predictive Maintenance Market: Research Methodology
3. Market Size Estimation Methodology: Bottom-Up Approach
4. Market Size Estimation Methodology: Top-Down Approach
5. Data Triangulation
6. Porter’s Five Forces Analysis
7. Value Chain Analysis
8. Global Predictive Maintenance Market Attractiveness Analysis By Component
9. Global Predictive Maintenance Market Attractiveness Analysis By Vertical
10. Global Predictive Maintenance Market Attractiveness Analysis By Region
11. Global Predictive Maintenance Market: Dynamics
12. Global Predictive Maintenance Market Share By Component(2021 & 2028)
13. Global Predictive Maintenance Market Share By Vertical (2021 & 2028)
14. Global Predictive Maintenance Market Share by Regions (2021 & 2028)
15. Global Predictive Maintenance Market Share by Company (2020)
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