
Automotive Predictive Maintenance Market: Current Analysis and Forecast (2022-2028)
Description
Automotive Predictive Maintenance Market: Current Analysis and Forecast (2022-2028)
The automotive predictive maintenance market refers to the use of advanced technologies, such as machine learning and artificial intelligence, to predict and prevent equipment failures in vehicles. The goal of predictive maintenance is to minimize downtime, reduce maintenance costs, and improve vehicle safety and performance. The market for predictive maintenance in the automotive industry is growing, driven by the increasing demand for connected vehicles and the need to improve operational efficiency and reliability. Key players in the market include companies offering predictive maintenance solutions, such as IBM, Siemens, and GE.
The automotive predictive maintenance market is expected to grow at a steady rate of around 22% owing to the growing adoption of IoT-based systems and connected cars and increasing investment in research and development of predictive maintenance technologies. Major companies in the market offer applications with technologically advanced features. For instance, Bosch's IoT solutions for predictive maintenance utilize sensors and data analytics to predict potential failures and reduce maintenance costs.
The automotive predictive maintenance market refers to the use of advanced technologies, such as machine learning and artificial intelligence, to predict and prevent equipment failures in vehicles. The goal of predictive maintenance is to minimize downtime, reduce maintenance costs, and improve vehicle safety and performance. The market for predictive maintenance in the automotive industry is growing, driven by the increasing demand for connected vehicles and the need to improve operational efficiency and reliability. Key players in the market include companies offering predictive maintenance solutions, such as IBM, Siemens, and GE.
The automotive predictive maintenance market is expected to grow at a steady rate of around 22% owing to the growing adoption of IoT-based systems and connected cars and increasing investment in research and development of predictive maintenance technologies. Major companies in the market offer applications with technologically advanced features. For instance, Bosch's IoT solutions for predictive maintenance utilize sensors and data analytics to predict potential failures and reduce maintenance costs.
- Based on vehicle type, the market is segmented into passenger vehicle and commercial vehicle. The passenger vehicles category is to witness a higher CAGR during the forecast period. The growth of passenger vehicles can be attributed to several factors, including increasing disposable income and standards of living, allowing people to purchase personal vehicles, urbanization, and the growth of cities leading to increasing demand for personal transportation. Additionally, Improved infrastructure and widespread availability of financing options, make it easier for people to own a vehicle. These factors have collectively led to an increased demand for passenger vehicles, driving their growth globally
- On the basis of end users, the market is categorized into fleet owners, insurers, and others. Among these, the fleet owners category is to witness a higher CAGR during the forecast period. The growth of passenger vehicles can be attributed to several factors such as increased demand for goods and services. The growing demand for goods and services has led to an increase in the number of deliveries, leading to an increase in the number of fleet owners. Additionally, overall economic growth has led to increase in demand for goods and services, which in turn has led to an increase in the number of fleet owners.
- Based on hardware type, the automotive predictive maintenance market has been classified into ADAS, onboard diagnosis, and others. ADAS has the highest growth among the others categories. The growth of Advanced Driver Assistance Systems (ADAS) can be attributed to several factors which include increased demand for safety. With the rise in road accidents and fatalities, there is a growing demand for technology that can enhance vehicle safety and prevent accidents. ADAS systems provide additional safety features, such as collision avoidance, lane departure warning, and adaptive cruise control, which have led to an increased demand for these systems. Additionally, Governments across the world are implementing regulations that require vehicles to be equipped with certain safety features, such as electronic stability control and anti-lock brakes. This has driven the growth of ADAS systems.
- For a better understanding of the market adoption of the automotive predictive maintenance industry, the market is analyzed based on its worldwide presence in the countries such as North America (U.S., Canada, Rest of North America), Europe (Germany, U.K., France, Spain, Italy, Rest of Europe), Asia-Pacific (China, Japan, India, Rest of Asia-Pacific), Rest of World. North America led the market in 2021 owing to the growing demand for connected vehicles and increasing awareness of the benefits of predictive maintenance. In addition, Government support and favorable policies for the adoption of advanced technologies in the automotive industry. Moreover, the increase in demand for electric vehicles is driving the need for more sophisticated predictive maintenance solutions to ensure their smooth operation. The factors contributing to this growth are the strong presence of key players in the region such as General Electric, IBM, and Microsoft. In North America, several companies are innovating in the field of automotive predictive maintenance, some of the companies and their respective innovations include Bosc which developed the Predictive Maintenance Solution that utilizes machine learning algorithms to predict component failures and optimize maintenance schedules for industrial equipment.
- Some of the major players operating in the market include BorgWarner Inc.; Siemens AG; HARMAN International; IBM Corporation; ZF Friedrichshafen AG; Robert Bosch GmbH; Rockwell Automation, Inc; SAP SE; Continental AG; and Aptiv.
Table of Contents
161 Pages
- 1 MARKET INTRODUCTION
- 1.1. Market Definitions
- 1.2. Main Objective
- 1.3. Stakeholders
- 1.4. Limitation
- 2 RESEARCH METHODOLOGY OR ASSUMPTION
- 2.1. Research Process of the Automotive Predictive Maintenance Market
- 2.2. Research Methodology of the Automotive Predictive Maintenance Market
- 2.3. Respondent Profile
- 3 MARKET SYNOPSIS
- 4 EXECUTIVE SUMMARY
- 5 IMPACT OF COVID-19 ON THE AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET
- 6 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET REVENUE (USD BN), 2020-2028F
- 7 MARKET INSIGHTS BY END USERS
- 7.1. Fleet Owners
- 7.2. Insurers
- 7.3. Others
- 8 MARKET INSIGHTS BY VEHICLE TYPE
- 8.1. Passenger Vehicles
- 8.2. Commercial Vehicles
- 9 MARKET INSIGHTS BY HARDWARE TYPE
- 9.1. ADAS
- 9.2. On-board Diagnosis
- 9.3. Others
- 10 MARKET INSIGHTS BY REGION
- 10.1. North America
- 10.1.1. U.S.
- 10.1.2. Canada
- 10.1.3. Rest of North America
- 10.2. Europe
- 10.2.1. Germany
- 10.2.2. U.K.
- 10.2.3. France
- 10.2.4. Italy
- 10.2.5. Spain
- 10.2.6. Rest of Europe
- 10.3. Asia-Pacific
- 10.3.1. China
- 10.3.2. Japan
- 10.3.3. India
- 10.3.4. Rest of Asia-Pacific
- 10.4. Rest of World
- 11 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET DYNAMICS
- 11.1. Market Drivers
- 11.2. Market Challenges
- 11.3. Impact Analysis
- 12 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET OPPORTUNITIES
- 13 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET TRENDS
- 14 DEMAND AND SUPPLY-SIDE ANALYSIS
- 14.1. Demand Side Analysis
- 14.2. Supply Side Analysis
- 15 VALUE CHAIN ANALYSIS
- 16 COMPETITIVE SCENARIO
- 16.1. Competitive Landscape
- 16.1.1. Porters Fiver Forces Analysis
- 17 COMPANY PROFILED
- 17.1. BorgWarner Inc.
- 17.2. Siemens AG
- 17.3. HARMAN International
- 17.4. IBM Corporation
- 17.5. ZF Friedrichshafen AG
- 17.6. Robert Bosch GmbH
- 17.7. Rockwell Automation, Inc
- 17.8. SAP SE
- 17.9. Continental AG
- 17.10. Aptiv
- 18 DISCLAIMER
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