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.

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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.

 According to UnivDatos Market Insights (UMI)’ research report “Global Automotive Predictive Maintenance Market”, the market is expected to witness robust growth during the forecast period (2022-2028). This is mainly due to the increasing demand for connected cars, the growing need for predictive maintenance solutions to improve the reliability and performance of vehicles and the rapid advancement of technology in the automotive industry.

Based on vehicle type, the market is segmented into passenger vehicle and commercial vehicle. There are several factors that contribute to the significant share of the commercial vehicle segment in the automotive predictive maintenance market such as high utilization rate, maintenance cost savings, and increasing demand for fleet management. Commercial vehicles, such as trucks and buses, are typically driven for longer hours and have a higher utilization rate than passenger vehicles, making predictive maintenance more critical for these vehicles. Additionally, predictive maintenance can help optimize maintenance schedules and reduce downtime, leading to cost savings for commercial vehicle operators.

On the basis of end users, the market is categorized into fleet owners, insurers, and others. Among these, the insurers will hold a significant market share in 2021. There are several factors that contribute to the significant share of the insurance segment such as government regulations often mandate the purchase of certain types of insurance, such as health insurance and car insurance. Additionally, the growth of digital distribution channels, such as online portals and mobile apps, is making it easier for consumers to purchase insurance products, which is helping to drive demand. Moreover, As people become more prosperous, they are more likely to purchase insurance products to protect their assets and financial well-being. Overall, these factors are contributing to the growth of the insurance segment and its significant share in the financial services industry.

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APAC to Grow at the Highest CAGR during the forecast period

The Asia-Pacific (APAC) region is anticipated to grow at the highest CAGR during the forecast period due to factors such as increasing demand for vehicles, rapid industrialization, and growth in the manufacturing sector. The region is also home to several large automobile manufacturers and suppliers, who are actively investing in new technologies, such as predictive maintenance, to improve their production processes and efficiency. Additionally, favorable government initiatives and policies aimed at promoting the adoption of advanced technologies in the automotive industry are further driving the growth of the predictive maintenance market in the APAC region. Moreover, The APAC region has a large and rapidly growing consumer market, which creates opportunities for predictive maintenance solutions to be adopted in various industries.

According to UnivDatos Market Insights (UMI)’, the key players with a considerable market share in the Automotive Predictive Maintenance market are BorgWarner Inc.; Siemens AG; HARMAN International; IBM Corporation; ZF Friedrichshafen AG; Robert Bosch GmbH; Rockwell Automation, Inc; SAP SE; Continental AG; and Aptiv.

“Global Automotive Predictive Maintenance Market” provides comprehensive qualitative and quantitative insights on the industry potential, key factors impacting sales and purchase decisions, hotspots, and opportunities available for the market players. Moreover, the report also encompasses the key strategic imperatives for success for competitors along with strategic factorial indexing measuring competitors’ capabilities on different parameters. This will help companies in the formulation of go-to-market strategies and identifying the blue ocean for its offerings.    

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Market Segmentation:

1.       By Vehicle Type (Passenger Vehicle and Commercial Vehicle)

2.       By Hardware Type (ADAS, On-board Diagnosis, and Others)

3.       By End Users (Fleet Owners, Insurers, And Others)

4.       By Region (North America, Europe, Asia-Pacific, Rest of the World)

5.       By Company (BorgWarner Inc.; Siemens AG; HARMAN International; IBM Corporation; ZF Friedrichshafen AG; Robert Bosch GmbH; Rockwell Automation, Inc; SAP SE; Continental AG; and Aptiv)

Key questions answered in the study:

1.       What are the current and future trends of the global automotive predictive maintenance industry?

2.       How the industry has been evolving in terms of vehicle type, hardware type, and end users?

3.       How the competition has been shaping across the countries followed by their comparative factorial indexing?

4.       What are the key growth drivers and challenges for the global automotive predictive maintenance industry?

5.       What is the customer orientation, purchase behavior, and expectations from the global automotive predictive maintenance suppliers across various region and countries?

Table Of Content-

1 MARKET INTRODUCTION

2 RESEARCH METHODOLOGY OR ASSUMPTION

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

8 MARKET INSIGHTS BY VEHICLE TYPE

9 MARKET INSIGHTS BY HARDWARE TYPE

10 MARKET INSIGHTS BY REGION

11 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET DYNAMICS

12 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET OPPORTUNITIES

13 AUTOMOTIVE PREDICTIVE MAINTENANCE MARKET TRENDS

14 DEMAND AND SUPPLY-SIDE ANALYSIS

15 VALUE CHAIN ANALYSIS

16 COMPETITIVE SCENARIO

17 COMPANY PROFILED

18 DISCLAIMER

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