New York, April 12, 2023 (GLOBE NEWSWIRE) — The global automotive predictive maintenance market was valued at USD 18.9 billion in 2022. Between 2023 and 2032, this market is estimated to register the highest CAGR of 18.6% and will reach USD 100 billion by 2032. Automotive predictive maintenance is the use of advanced analytics and machine learning algorithms to anticipate and prevent vehicle issues before they arise.
This proactive approach helps reduce vehicle downtime, boost safety, and lower repair costs. Predictive maintenance solutions utilize real-time data from multiple sensors and sources like vehicle diagnostics, telemetry, and driver behavior to detect potential issues and anticipate when maintenance is needed. These solutions can detect anomalies, recognize patterns, and offer insights into the health of vehicles. Automotive predictive maintenance offers numerous advantages, such as improved vehicle dependability, increased safety, lower maintenance costs, and extended vehicle lifespan. By detecting and fixing minor issues before they become major problems, predictive maintenance helps avoid breakdowns, accidents, and expensive repairs.
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- By component, in 2022, the solution industry dominated the automotive predictive maintenance market with a 62% market share
- By technology, the IoT segment dominated the automotive predictive maintenance market with a 35% market share.
- By vehicle type, passenger cars are holding the largest share of the automotive predictive maintenance market
- By application, oil change dominates the automotive predictive maintenance market. It is a rapidly developing industry that utilizes advanced technologies to anticipate and prevent mechanical failures in vehicles.
- In 2022, North America dominated the market with the highest revenue share of 43%.
- APAC is expected to grow at a greater pace owing to due to increasing adoption of connected cars and development in countries such as China, India, and Japan.
Factors affecting the growth of the automotive predictive maintenance market industry
There are several factors that can have an impact on the growth of the automotive predictive maintenance market industry. Some of these factors include:
- Advancements in IoT Technology: The growing adoption of IoT and sensors within the automotive industry allows for real-time data collection on vehicles, which can be utilized for predictive maintenance.
- Increased Demand for Safety and Security: With growing concerns over road safety and security, there is an increasing need for predictive maintenance solutions that can help prevent breakdowns and accidents.
- Growth of the Automotive Industry: The overall expansion of the automotive sector and an increasing number of vehicles on the road are driving demand for predictive maintenance solutions.
- Shift towards connected vehicles: The rising demand for connected vehicles with advanced features like remote diagnostics and predictive maintenance is forecast to fuel the growth of the predictive maintenance market.
- Technological Advancements: The development of advanced technologies such as machine learning and artificial intelligence is expected to enhance the capabilities of predictive maintenance solutions and also propel market growth.
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The automotive predictive maintenance market has seen rapid growth in recent years and is projected to keep expanding in the years ahead. Predictive maintenance utilizes advanced analytics and data to anticipate when vehicle maintenance is needed before a breakdown occurs, helping reduce downtime and costs associated with repairs, as well as improve safety and dependability scores. One of the primary factors driving growth in this market is the growing adoption of connected cars and the Internet of Things (IoT) in the automotive industry.
Connected cars collect vast amounts of data on vehicle performance that can be used to identify potential issues before they become major ones. Utilizing advanced algorithms, these insights provide real-time visibility into vehicle health and predict when maintenance will be necessary. Another factor driving growth in this market is an increasing need for efficient and cost-effective maintenance solutions. Predictive maintenance helps companies avoid unscheduled downtime which can be expensive and disruptive. By anticipating when maintenance will be needed, businesses can schedule it at a convenient and economical time.
Furthermore, the rising demand for electric vehicles (EVs) is expected to fuel growth in the automotive predictive maintenance market. EVs feature fewer moving parts and require less upkeep compared to traditional gasoline-powered cars; however, their maintenance requirements differ, necessitating predictive maintenance to guarantee these vehicles run optimally. Overall, the automotive predictive maintenance market is expected to expand as more companies adopt this approach and technology continues to progress. By 2023, this market could reach billions of dollars in value, providing lucrative opportunities for companies within and outside of automotive manufacturing.
The largest share in the market will be dominated by North America with 43% of the market share owing to the reduced vehicle downtime, boost safety, and lower repair costs. North America holds a significant share of the global automotive predictive maintenance market due to the presence of major auto companies, the adoption of advanced technologies, and an increasing focus on vehicle safety and reliability. The United States leads North America’s automotive predictive maintenance market.
Europe is a major market for automotive predictive maintenance, driven by the region’s vibrant automotive industry, technological developments, and regulations to promote vehicle safety and emissions reduction. Germany, France, and the United Kingdom are the three leading markets in this regard in Europe. The Asia Pacific region is expected to experience rapid growth in the automotive predictive maintenance market, due to the increasing adoption of connected cars and development in countries such as China, India, and Japan. Furthermore, several major automotive manufacturers and suppliers are situated here which further fuels market expansion.
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Scope of the Report
|Market Value (2022)
|USD 18.9 Billion
|Market Size (2032)
|USD 100 Billion
|CAGR (from 2023 to 2032)
|North America Revenue Share
|2016 to 2022
|2023 to 2032
The downtime caused by maintenance and repairs must urgently be reduced due to the rising demand for automobiles. Predictive maintenance assists in identifying possible difficulties before they develop into larger concerns, so minimizing downtime and increasing productivity. The market for automotive predictive maintenance is expanding due to the increasing adoption of IoT and linked cars. Real-time data collection and transmission made possible by these technologies allows for the early identification of potential maintenance concerns in moving vehicles. The cost of unplanned maintenance and repairs can be decreased with the use of predictive maintenance. Early issue detection and resolution can significantly reduce the total cost of ownership by preventing expensive repairs and reducing downtime. The cost of unplanned maintenance and repairs can be decreased with the use of predictive maintenance.
Predictive maintenance solutions have an expensive initial cost that may be out of reach for small and medium-sized businesses. Predictive maintenance solutions must be implemented, which requires specific technical knowledge that may not be present in all enterprises. The accuracy and good security of the data gathered from multiple sources are crucial for predictive maintenance. The accuracy of predictive maintenance systems can be greatly impacted by poor data quality or security issues. There is a glaring lack of standardization in the automobile sector, which could cause issues with communication across various preventative maintenance programs. Predictive maintenance solutions adoption in the automobile sector can be significantly hampered by resistance to change, especially in conventional organizations that are wary of both new technologies and processes.
By identifying problems early on, predictive maintenance technologies give automakers the chance to reduce repair costs. Companies can avoid costly repairs or downtime by anticipating maintenance needs also taking preventative action to solve them. By ensuring that their vehicles function at their peak, predictive maintenance solutions give businesses the chance to maximize the productivity of their fleets. This might lead to better fuel efficiency, lower emissions, and more productivity. Early adopters of predictive maintenance systems can have an advantage over their competitors. Businesses may boost market share, increase customer satisfaction, and differentiate themselves from competitors by enhancing vehicle reliability and performance. Many data points produced by predictive maintenance solutions can be mined to reveal important information about the efficiency of vehicles as well their maintenance requirements.
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Report Segmentation of the automotive predictive maintenance market
Based on component, based on components, the automotive predictive maintenance (PDM) market is segmented into services and solutions, the solution industry dominated the automotive predictive maintenance market. The solution uses data gathered by multiple IoT sensors and conducts extensive data analysis to forecast an anomaly in the operation of critical equipment. Hence, it is a major source of revenue for the predictive maintenance (PDM) market. Businesses may choose to adopt managed services directly for their operations in accordance with their needs. In addition, it is projected that the growing need for staff training, effective application of these solutions, also assistance with integration, and good implementation would promote the rise of the services industry.
By Technology System, the IoT segment dominated the automotive predictive maintenance market. IoT-based predictive maintenance solutions for the automotive industry typically involve the use of sensors and other IoT devices to monitor the condition of a vehicle’s critical components, such as the engine, brakes, and transmission. The data collected by these devices is then analyzed in real-time using advanced analytics as well as machine learning algorithms to predict when maintenance will be required. Business intelligence (bi) is essential in the global automotive predictive maintenance market, helping analysts interpret data to gain insight and make informed decisions.
Predictive maintenance utilizes data analytics to monitor vehicle and equipment performance to anticipate failures and prevent them from occurring, thus saving downtime and maintenance expenses. The use of 5g technology is having a profound effect on the global automotive predictive maintenance market. 5g provides high-speed connectivity and low latency, allowing real-time monitoring and analysis of vehicle performance data. This enables automotive manufacturers and service providers to anticipate maintenance needs before they arise, leading to reduced downtime and improved efficiency.
Vehicle Type Insight
Based on Vehicle Type, passenger cars are holding the largest share in the automotive predictive maintenance market. This is due to the vast number of passenger cars on the road today and an ever-increasing need for proactive solutions that improve safety also dependability. Predictive diagnostics and remote monitoring are often employed in passenger cars to identify potential issues before they become major issues.
Commercial vehicles such as trucks and buses are an important segment in the automotive predictive maintenance market. These vehicles are frequently used for long-distance travel and transport, necessitating high levels of upkeep to guarantee their safety and dependability. Predictive maintenance solutions such as scheduling appointments ahead of time and remote monitoring can help fleet managers optimize their maintenance regimens while reducing downtime.
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Based on Component
- Managed Services
- Professional Service
Based on the Technology
Based on Vehicle Type
- Passenger Cars
- Light Commercial Vehicles
- Heavy Duty Trucks
- Buses and Coaches
Based on Application
- Oil Change
- Transmission Checkup
- Belt Change
- Brake and Tire Inspection
- Coolant Replacement
- Engine Air Filter
- Cabin Filter
- Others Application
- The UK
- Rest of Western Europe
- The Czech Republic
- Rest of Eastern Europe
- South Korea
- Australia & New Zealand
- Rest of APAC
- Costa Rica
- Rest of Latin America
- Saudi Arabia
- South Africa
- United Arab Emirates
- Rest of MEA
Companies are actively engaged in product development, strategic collaborations, mergers, and acquisitions, as well as other growth strategies to gain a competitive edge in the market. Furthermore, they invest heavily in research and development to enhance their existing offerings and introduce new innovative solutions tailored to the automotive industry. The global automotive predictive maintenance market is highly competitive with several established and emerging players offering various solutions and services.
Recent Development of the automotive predictive maintenance market
- In January 2023- Salesforce, a provider of customer relationship management (CRM) solutions, and Qualcomm Technologies, Inc. announced their strategic partnership to develop Automotive Cloud, an advanced connected car platform specifically designed for the automotive industry.
- In January 2023- An agreement to stream connected vehicle data directly into Microsoft Maps was signed by Israeli auto data provider Otonomo and Microsoft.
Some of the major players include:
- SAS Institute Inc.
- Software AG
- TIBCO Software Inc
- Hewlett Packard Enterprise Development LP
- Altair Engineering Inc.
- Splunk Inc
- Amazon Web Services, Inc
- General Electric
- Schneider Electric
- Hitachi, Ltd.
- RapidMiner Inc
- Operational Excellence (OPEX) Group Ltd
- CHIRON Swiss SA
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