Global Automotive Predictive Maintenance Market

Automotive Predictive Maintenance Comprehensive Study by Application (Engine Performance, Exhaust Systems, Transmission Function, Structural Stability), Component (Software (Standalone and Web-based), Services (Professional and Managed)), End User (Individuals, Manufacturers (OEMs), Insurance Providers, Dealers & Service Partners, Fleet Owners) Players and Region - Global Market Outlook to 2028

Automotive Predictive Maintenance Market by XX Submarkets | Forecast Years 2023-2028  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
Global Automotive Predictive Maintenance Market Overview:
Predictive maintenance has a lot of potential in Industry 4.0, which emphasizes proactive maintenance to keep operations running smoothly. Predictive maintenance is impossible without regular monitoring of equipment in normal operating conditions to guarantee that they are being used to their full potential. It has also had an impact on the car sector, with engine performance, exhaust systems, gearbox operation, and structural stability all benefiting from vehicle predictive maintenance. Automotive predictive maintenance is especially important for optimizing engine performance since it analyses and predicts ambient conditions, fuel usage, and other variables for optimal performance.

AttributesDetails
Study Period2018-2028
Base Year2022
Forecast Period2023-2028
Historical Period2018-2022
UnitValue (USD Million)
Customization ScopeAvail customization with purchase of this report. Add or modify country, region & or narrow down segments in the final scope subject to feasibility


Influencing Trend:
Integration of big data and IoT in automotive predictive maintenance to manage downtime

Market Growth Drivers:
Increased focus on improving the operational efficiency of vehicles at optimum cost and Engine performance growing rapidly

Challenges:
Lack of skilled workforce for maintenance work

Restraints:
Threat of data security and privacy of organizations

Opportunities:
Rise in research & development activities by automotive predictive maintenance market players and Increasing number of automotive manufacturing companies

Competitive Landscape:
The companies are now exploring the market by adopting mergers & acquisitions, expansions, investments, new developments in existing products and collaborations as their preferred strategies. The players are also exploring new geographies and industries through expansions and acquisitions so as to avail a competitive advantage through combined synergies.
Some of the key players profiled in the report are Harman International Industries, Inc (United States), IMS (United Kingdom), Rockwell Automation, Inc. (United States), Delphi Technologies (United Kingdom), Siemens AG (Germany), IBM Corporation (United States), Microsoft Corporation (United States), Robert Bosch GmbH (Germany), SAP SE (Germany) and Teletrac Navman (United States). Analyst at AMA Research see Global Vendors to retain maximum share of Global Automotive Predictive Maintenance market by 2028. Considering Market by Component, the sub-segment i.e. Software (Standalone and Web-based) will boost the Automotive Predictive Maintenance market. Considering Market by End User, the sub-segment i.e. Individuals will boost the Automotive Predictive Maintenance market.

Latest Market Insights:
In December 2018, SAP SE launched a new software, SAP Intelligent Asset Management (IAM), which can provide predictive maintenance and asset intelligence for asset operation and maintenance.

In May 2019, BMW AG, a multinational manufacturer of automobiles, integrated the IBM Watson cloud platform into its vehicles through the creation of apps with predictive maintenance or advanced analytics based on vehicle tear and wear.

What Can be Explored with the Automotive Predictive Maintenance Market Study
 Gain Market Understanding
 Identify Growth Opportunities
 Analyze and Measure the Global Automotive Predictive Maintenance Market by Identifying Investment across various Industry Verticals
 Understand the Trends that will drive Future Changes in Automotive Predictive Maintenance
 Understand the Competitive Scenario
- Track Right Markets
- Identify the Right Verticals

Research Methodology:
The top-down and bottom-up approaches are used to estimate and validate the size of the Global Automotive Predictive Maintenance market.
In order to reach an exhaustive list of functional and relevant players various industry classification standards are closely followed such as NAICS, ICB, SIC to penetrate deep in important geographies by players and a thorough validation test is conducted to reach most relevant players for survey in Automotive Predictive Maintenance market.
In order to make priority list sorting is done based on revenue generated based on latest reporting with the help of paid databases such as Factiva, Bloomberg etc.
Finally the questionnaire is set and specifically designed to address all the necessities for primary data collection after getting prior appointment by targeting key target audience that includes Venture Capitalists and Private Equity Firms, New Entrants/Investors, Analysts and Strategic Business Planners, Government Regulatory and Research Organizations, Automotive Predictive Maintenance Provider and End-Use Industries.
This helps us to gather the data related to players revenue, operating cycle and expense, profit along with product or service growth etc.
Almost 70-80% of data is collected through primary medium and further validation is done through various secondary sources that includes Regulators, World Bank, Association, Company Website, SEC filings, OTC BB, USPTO, EPO, Annual reports, press releases etc.

Report Objectives / Segmentation Covered

By Application
  • Engine Performance
  • Exhaust Systems
  • Transmission Function
  • Structural Stability
By Component
  • Software (Standalone and Web-based)
  • Services (Professional and Managed)

By End User
  • Individuals
  • Manufacturers [OEMs]
  • Insurance Providers
  • Dealers & Service Partners
  • Fleet Owners

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Increased focus on improving the operational efficiency of vehicles at optimum cost
      • 3.2.2. Engine performance growing rapidly
    • 3.3. Market Challenges
      • 3.3.1. Lack of skilled workforce for maintenance work
    • 3.4. Market Trends
      • 3.4.1. Integration of big data and IoT in automotive predictive maintenance to manage downtime
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Automotive Predictive Maintenance, by Application, Component, End User and Region (value and price ) (2017-2022)
    • 5.1. Introduction
    • 5.2. Global Automotive Predictive Maintenance (Value)
      • 5.2.1. Global Automotive Predictive Maintenance by: Application (Value)
        • 5.2.1.1. Engine Performance
        • 5.2.1.2. Exhaust Systems
        • 5.2.1.3. Transmission Function
        • 5.2.1.4. Structural Stability
      • 5.2.2. Global Automotive Predictive Maintenance by: Component (Value)
        • 5.2.2.1. Software (Standalone and Web-based)
        • 5.2.2.2. Services (Professional and Managed)
      • 5.2.3. Global Automotive Predictive Maintenance by: End User (Value)
        • 5.2.3.1. Individuals
        • 5.2.3.2. Manufacturers [OEMs]
        • 5.2.3.3. Insurance Providers
        • 5.2.3.4. Dealers & Service Partners
        • 5.2.3.5. Fleet Owners
      • 5.2.4. Global Automotive Predictive Maintenance Region
        • 5.2.4.1. South America
          • 5.2.4.1.1. Brazil
          • 5.2.4.1.2. Argentina
          • 5.2.4.1.3. Rest of South America
        • 5.2.4.2. Asia Pacific
          • 5.2.4.2.1. China
          • 5.2.4.2.2. Japan
          • 5.2.4.2.3. India
          • 5.2.4.2.4. South Korea
          • 5.2.4.2.5. Taiwan
          • 5.2.4.2.6. Australia
          • 5.2.4.2.7. Rest of Asia-Pacific
        • 5.2.4.3. Europe
          • 5.2.4.3.1. Germany
          • 5.2.4.3.2. France
          • 5.2.4.3.3. Italy
          • 5.2.4.3.4. United Kingdom
          • 5.2.4.3.5. Netherlands
          • 5.2.4.3.6. Rest of Europe
        • 5.2.4.4. MEA
          • 5.2.4.4.1. Middle East
          • 5.2.4.4.2. Africa
        • 5.2.4.5. North America
          • 5.2.4.5.1. United States
          • 5.2.4.5.2. Canada
          • 5.2.4.5.3. Mexico
    • 5.3. Global Automotive Predictive Maintenance (Price)
  • 6. Automotive Predictive Maintenance: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2022)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Harman International Industries, Inc (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. IMS (United Kingdom)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Rockwell Automation, Inc. (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Delphi Technologies (United Kingdom)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Siemens AG (Germany)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. IBM Corporation (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Microsoft Corporation (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Robert Bosch GmbH (Germany)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. SAP SE (Germany)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Teletrac Navman (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
  • 7. Global Automotive Predictive Maintenance Sale, by Application, Component, End User and Region (value and price ) (2023-2028)
    • 7.1. Introduction
    • 7.2. Global Automotive Predictive Maintenance (Value)
      • 7.2.1. Global Automotive Predictive Maintenance by: Application (Value)
        • 7.2.1.1. Engine Performance
        • 7.2.1.2. Exhaust Systems
        • 7.2.1.3. Transmission Function
        • 7.2.1.4. Structural Stability
      • 7.2.2. Global Automotive Predictive Maintenance by: Component (Value)
        • 7.2.2.1. Software (Standalone and Web-based)
        • 7.2.2.2. Services (Professional and Managed)
      • 7.2.3. Global Automotive Predictive Maintenance by: End User (Value)
        • 7.2.3.1. Individuals
        • 7.2.3.2. Manufacturers [OEMs]
        • 7.2.3.3. Insurance Providers
        • 7.2.3.4. Dealers & Service Partners
        • 7.2.3.5. Fleet Owners
      • 7.2.4. Global Automotive Predictive Maintenance Region
        • 7.2.4.1. South America
          • 7.2.4.1.1. Brazil
          • 7.2.4.1.2. Argentina
          • 7.2.4.1.3. Rest of South America
        • 7.2.4.2. Asia Pacific
          • 7.2.4.2.1. China
          • 7.2.4.2.2. Japan
          • 7.2.4.2.3. India
          • 7.2.4.2.4. South Korea
          • 7.2.4.2.5. Taiwan
          • 7.2.4.2.6. Australia
          • 7.2.4.2.7. Rest of Asia-Pacific
        • 7.2.4.3. Europe
          • 7.2.4.3.1. Germany
          • 7.2.4.3.2. France
          • 7.2.4.3.3. Italy
          • 7.2.4.3.4. United Kingdom
          • 7.2.4.3.5. Netherlands
          • 7.2.4.3.6. Rest of Europe
        • 7.2.4.4. MEA
          • 7.2.4.4.1. Middle East
          • 7.2.4.4.2. Africa
        • 7.2.4.5. North America
          • 7.2.4.5.1. United States
          • 7.2.4.5.2. Canada
          • 7.2.4.5.3. Mexico
    • 7.3. Global Automotive Predictive Maintenance (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Automotive Predictive Maintenance: by Application(USD Million)
  • Table 2. Automotive Predictive Maintenance Engine Performance , by Region USD Million (2017-2022)
  • Table 3. Automotive Predictive Maintenance Exhaust Systems , by Region USD Million (2017-2022)
  • Table 4. Automotive Predictive Maintenance Transmission Function , by Region USD Million (2017-2022)
  • Table 5. Automotive Predictive Maintenance Structural Stability , by Region USD Million (2017-2022)
  • Table 6. Automotive Predictive Maintenance: by Component(USD Million)
  • Table 7. Automotive Predictive Maintenance Software (Standalone and Web-based) , by Region USD Million (2017-2022)
  • Table 8. Automotive Predictive Maintenance Services (Professional and Managed) , by Region USD Million (2017-2022)
  • Table 9. Automotive Predictive Maintenance: by End User(USD Million)
  • Table 10. Automotive Predictive Maintenance Individuals , by Region USD Million (2017-2022)
  • Table 11. Automotive Predictive Maintenance Manufacturers [OEMs] , by Region USD Million (2017-2022)
  • Table 12. Automotive Predictive Maintenance Insurance Providers , by Region USD Million (2017-2022)
  • Table 13. Automotive Predictive Maintenance Dealers & Service Partners , by Region USD Million (2017-2022)
  • Table 14. Automotive Predictive Maintenance Fleet Owners , by Region USD Million (2017-2022)
  • Table 15. South America Automotive Predictive Maintenance, by Country USD Million (2017-2022)
  • Table 16. South America Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 17. South America Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 18. South America Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 19. Brazil Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 20. Brazil Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 21. Brazil Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 22. Argentina Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 23. Argentina Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 24. Argentina Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 25. Rest of South America Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 26. Rest of South America Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 27. Rest of South America Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 28. Asia Pacific Automotive Predictive Maintenance, by Country USD Million (2017-2022)
  • Table 29. Asia Pacific Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 30. Asia Pacific Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 31. Asia Pacific Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 32. China Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 33. China Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 34. China Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 35. Japan Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 36. Japan Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 37. Japan Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 38. India Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 39. India Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 40. India Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 41. South Korea Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 42. South Korea Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 43. South Korea Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 44. Taiwan Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 45. Taiwan Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 46. Taiwan Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 47. Australia Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 48. Australia Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 49. Australia Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 50. Rest of Asia-Pacific Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 51. Rest of Asia-Pacific Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 52. Rest of Asia-Pacific Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 53. Europe Automotive Predictive Maintenance, by Country USD Million (2017-2022)
  • Table 54. Europe Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 55. Europe Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 56. Europe Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 57. Germany Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 58. Germany Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 59. Germany Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 60. France Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 61. France Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 62. France Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 63. Italy Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 64. Italy Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 65. Italy Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 66. United Kingdom Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 67. United Kingdom Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 68. United Kingdom Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 69. Netherlands Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 70. Netherlands Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 71. Netherlands Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 72. Rest of Europe Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 73. Rest of Europe Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 74. Rest of Europe Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 75. MEA Automotive Predictive Maintenance, by Country USD Million (2017-2022)
  • Table 76. MEA Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 77. MEA Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 78. MEA Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 79. Middle East Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 80. Middle East Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 81. Middle East Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 82. Africa Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 83. Africa Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 84. Africa Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 85. North America Automotive Predictive Maintenance, by Country USD Million (2017-2022)
  • Table 86. North America Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 87. North America Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 88. North America Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 89. United States Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 90. United States Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 91. United States Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 92. Canada Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 93. Canada Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 94. Canada Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 95. Mexico Automotive Predictive Maintenance, by Application USD Million (2017-2022)
  • Table 96. Mexico Automotive Predictive Maintenance, by Component USD Million (2017-2022)
  • Table 97. Mexico Automotive Predictive Maintenance, by End User USD Million (2017-2022)
  • Table 98. Company Basic Information, Sales Area and Its Competitors
  • Table 99. Company Basic Information, Sales Area and Its Competitors
  • Table 100. Company Basic Information, Sales Area and Its Competitors
  • Table 101. Company Basic Information, Sales Area and Its Competitors
  • Table 102. Company Basic Information, Sales Area and Its Competitors
  • Table 103. Company Basic Information, Sales Area and Its Competitors
  • Table 104. Company Basic Information, Sales Area and Its Competitors
  • Table 105. Company Basic Information, Sales Area and Its Competitors
  • Table 106. Company Basic Information, Sales Area and Its Competitors
  • Table 107. Company Basic Information, Sales Area and Its Competitors
  • Table 108. Automotive Predictive Maintenance: by Application(USD Million)
  • Table 109. Automotive Predictive Maintenance Engine Performance , by Region USD Million (2023-2028)
  • Table 110. Automotive Predictive Maintenance Exhaust Systems , by Region USD Million (2023-2028)
  • Table 111. Automotive Predictive Maintenance Transmission Function , by Region USD Million (2023-2028)
  • Table 112. Automotive Predictive Maintenance Structural Stability , by Region USD Million (2023-2028)
  • Table 113. Automotive Predictive Maintenance: by Component(USD Million)
  • Table 114. Automotive Predictive Maintenance Software (Standalone and Web-based) , by Region USD Million (2023-2028)
  • Table 115. Automotive Predictive Maintenance Services (Professional and Managed) , by Region USD Million (2023-2028)
  • Table 116. Automotive Predictive Maintenance: by End User(USD Million)
  • Table 117. Automotive Predictive Maintenance Individuals , by Region USD Million (2023-2028)
  • Table 118. Automotive Predictive Maintenance Manufacturers [OEMs] , by Region USD Million (2023-2028)
  • Table 119. Automotive Predictive Maintenance Insurance Providers , by Region USD Million (2023-2028)
  • Table 120. Automotive Predictive Maintenance Dealers & Service Partners , by Region USD Million (2023-2028)
  • Table 121. Automotive Predictive Maintenance Fleet Owners , by Region USD Million (2023-2028)
  • Table 122. South America Automotive Predictive Maintenance, by Country USD Million (2023-2028)
  • Table 123. South America Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 124. South America Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 125. South America Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 126. Brazil Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 127. Brazil Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 128. Brazil Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 129. Argentina Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 130. Argentina Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 131. Argentina Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 132. Rest of South America Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 133. Rest of South America Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 134. Rest of South America Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 135. Asia Pacific Automotive Predictive Maintenance, by Country USD Million (2023-2028)
  • Table 136. Asia Pacific Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 137. Asia Pacific Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 138. Asia Pacific Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 139. China Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 140. China Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 141. China Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 142. Japan Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 143. Japan Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 144. Japan Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 145. India Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 146. India Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 147. India Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 148. South Korea Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 149. South Korea Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 150. South Korea Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 151. Taiwan Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 152. Taiwan Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 153. Taiwan Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 154. Australia Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 155. Australia Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 156. Australia Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 157. Rest of Asia-Pacific Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 158. Rest of Asia-Pacific Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 159. Rest of Asia-Pacific Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 160. Europe Automotive Predictive Maintenance, by Country USD Million (2023-2028)
  • Table 161. Europe Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 162. Europe Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 163. Europe Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 164. Germany Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 165. Germany Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 166. Germany Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 167. France Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 168. France Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 169. France Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 170. Italy Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 171. Italy Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 172. Italy Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 173. United Kingdom Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 174. United Kingdom Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 175. United Kingdom Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 176. Netherlands Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 177. Netherlands Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 178. Netherlands Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 179. Rest of Europe Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 180. Rest of Europe Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 181. Rest of Europe Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 182. MEA Automotive Predictive Maintenance, by Country USD Million (2023-2028)
  • Table 183. MEA Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 184. MEA Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 185. MEA Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 186. Middle East Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 187. Middle East Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 188. Middle East Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 189. Africa Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 190. Africa Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 191. Africa Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 192. North America Automotive Predictive Maintenance, by Country USD Million (2023-2028)
  • Table 193. North America Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 194. North America Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 195. North America Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 196. United States Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 197. United States Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 198. United States Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 199. Canada Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 200. Canada Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 201. Canada Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 202. Mexico Automotive Predictive Maintenance, by Application USD Million (2023-2028)
  • Table 203. Mexico Automotive Predictive Maintenance, by Component USD Million (2023-2028)
  • Table 204. Mexico Automotive Predictive Maintenance, by End User USD Million (2023-2028)
  • Table 205. Research Programs/Design for This Report
  • Table 206. Key Data Information from Secondary Sources
  • Table 207. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Automotive Predictive Maintenance: by Application USD Million (2017-2022)
  • Figure 5. Global Automotive Predictive Maintenance: by Component USD Million (2017-2022)
  • Figure 6. Global Automotive Predictive Maintenance: by End User USD Million (2017-2022)
  • Figure 7. South America Automotive Predictive Maintenance Share (%), by Country
  • Figure 8. Asia Pacific Automotive Predictive Maintenance Share (%), by Country
  • Figure 9. Europe Automotive Predictive Maintenance Share (%), by Country
  • Figure 10. MEA Automotive Predictive Maintenance Share (%), by Country
  • Figure 11. North America Automotive Predictive Maintenance Share (%), by Country
  • Figure 12. Global Automotive Predictive Maintenance share by Players 2022 (%)
  • Figure 13. Global Automotive Predictive Maintenance share by Players (Top 3) 2022(%)
  • Figure 14. Global Automotive Predictive Maintenance share by Players (Top 5) 2022(%)
  • Figure 15. BCG Matrix for key Companies
  • Figure 16. Harman International Industries, Inc (United States) Revenue, Net Income and Gross profit
  • Figure 17. Harman International Industries, Inc (United States) Revenue: by Geography 2022
  • Figure 18. IMS (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 19. IMS (United Kingdom) Revenue: by Geography 2022
  • Figure 20. Rockwell Automation, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 21. Rockwell Automation, Inc. (United States) Revenue: by Geography 2022
  • Figure 22. Delphi Technologies (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 23. Delphi Technologies (United Kingdom) Revenue: by Geography 2022
  • Figure 24. Siemens AG (Germany) Revenue, Net Income and Gross profit
  • Figure 25. Siemens AG (Germany) Revenue: by Geography 2022
  • Figure 26. IBM Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 27. IBM Corporation (United States) Revenue: by Geography 2022
  • Figure 28. Microsoft Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 29. Microsoft Corporation (United States) Revenue: by Geography 2022
  • Figure 30. Robert Bosch GmbH (Germany) Revenue, Net Income and Gross profit
  • Figure 31. Robert Bosch GmbH (Germany) Revenue: by Geography 2022
  • Figure 32. SAP SE (Germany) Revenue, Net Income and Gross profit
  • Figure 33. SAP SE (Germany) Revenue: by Geography 2022
  • Figure 34. Teletrac Navman (United States) Revenue, Net Income and Gross profit
  • Figure 35. Teletrac Navman (United States) Revenue: by Geography 2022
  • Figure 36. Global Automotive Predictive Maintenance: by Application USD Million (2023-2028)
  • Figure 37. Global Automotive Predictive Maintenance: by Component USD Million (2023-2028)
  • Figure 38. Global Automotive Predictive Maintenance: by End User USD Million (2023-2028)
  • Figure 39. South America Automotive Predictive Maintenance Share (%), by Country
  • Figure 40. Asia Pacific Automotive Predictive Maintenance Share (%), by Country
  • Figure 41. Europe Automotive Predictive Maintenance Share (%), by Country
  • Figure 42. MEA Automotive Predictive Maintenance Share (%), by Country
  • Figure 43. North America Automotive Predictive Maintenance Share (%), by Country
List of companies from research coverage that are profiled in the study
  • Harman International Industries, Inc (United States)
  • IMS (United Kingdom)
  • Rockwell Automation, Inc. (United States)
  • Delphi Technologies (United Kingdom)
  • Siemens AG (Germany)
  • IBM Corporation (United States)
  • Microsoft Corporation (United States)
  • Robert Bosch GmbH (Germany)
  • SAP SE (Germany)
  • Teletrac Navman (United States)
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May 2023 168 Pages 88 Tables Base Year: 2022 Coverage: 15+ Companies; 18 Countries

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Global Automotive Predictive Maintenance Market Quantitative research analysis
Global Automotive Predictive Maintenance Market Qualitative Industry Analysis
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Top performing companies in the Global Automotive Predictive Maintenance market are Harman International Industries, Inc (United States), IMS (United Kingdom), Rockwell Automation, Inc. (United States), Delphi Technologies (United Kingdom), Siemens AG (Germany), IBM Corporation (United States), Microsoft Corporation (United States), Robert Bosch GmbH (Germany), SAP SE (Germany) and Teletrac Navman (United States), to name a few.
"Integration of big data and IoT in automotive predictive maintenance to manage downtime" is seen as one of major influencing trends for Automotive Predictive Maintenance Market during projected period 2022-2028.

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