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Automotive Predictive Maintenance Market - Extensive Application in Engine Performance to Drive Market Growth

09-03-2021 05:30 AM CET | IT, New Media & Software

Press release from: Transparency Market Research

According to a new market report pertaining to the global automotive predictive maintenance market published by Transparency Market Research, the global automotive predictive maintenance market is projected to reach a value of ~US$ 2.7 Bn by 2027. The automotive predictive maintenance market is projected to expand at a CAGR of ~28% from 2019 to 2027. Growth of the market can be attributed to increased focus on optimizing vehicle operational cost from the point of view of both, the user as well as the manufacturer.

Over the forecast period, Asia Pacific is anticipated to grow rapidly in the automotive predictive maintenance market, at a CAGR of ~30%. In terms of share, the market is dominated by North America, followed by Europe. In the automotive predictive maintenance market, the software segment was valued at ~US$ 167 Mn in 2017 and is expected to reach ~US$ 2.1 Bn by 2027, expanding at a CAGR of ~28% during the forecast period.

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Increase in Demand for Embedded Computer Systems or IoT Devices to Avoid Unplanned Maintenance Downtime – Automotive predictive maintenance systems can help individual consumers and companies avoid downtime. Furthermore, predictive maintenance provides other important insights regarding vehicle or automotive part and usage patterns. Automotive predictive maintenance has the potential to provide cost-saving solutions to reduce expenses on maintenance. IoT systems or embedded computer systems help reduce repairs and improve vehicle safety outcomes, so that vehicles or fleets can reliably operate.

Increase in Demand for Smart Cars and Connected Cars – Car manufacturers are now using data science to improve driving experience and car performance. If a vehicle is equipped with smart sensors, the customer or mechanic can identify potential issues before they become problems. A smart vehicle can provide data regarding its performance, fuel consumption and emission, status of transmission system, speed, and driving behavior. Moreover, insurance companies use vehicle maintenance data to pass insurance claims by customers. All types of sensors store real-time data on the cloud platform to provide easy access to customers.

Automotive Predictive Maintenance Market: Regional Outlook

In terms of region, the global automotive predictive maintenance market has been segmented into North America, Europe, Asia Pacific, Middle East & Africa, and South America. North America is expected to dominate the automotive predictive maintenance market during the forecast period. Asia Pacific is expected to see increasing growth in the automotive predictive maintenance market. The automotive predictive maintenance markets in Europe and Middle East & Africa are also expected to expand rapidly during the forecast period.

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Automotive Predictive Maintenance Market: Competition Dynamics

The research study includes the profiles of leading companies operating in the global automotive predictive maintenance market. Key players profiled in the report include Harman International Industries, Inc., IMS - Part of Trak Global Group, Rockwell Automation, Inc. Delphi Technologies, Siemens AG, IBM Corporation, Microsoft Corporation, Robert Bosch GmbH, SAP SE, and Teletrac Navman.

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About Us

Transparency Market Research is a global market intelligence company providing global business information reports and services. Our exclusive blend of quantitative forecasting and trends analysis provides forward-looking insight for thousands of decision makers. Our experienced team of analysts, researchers, and consultants use proprietary data sources and various tools and techniques to gather and analyze information.

Our data repository is continuously updated and revised by a team of research experts, so that it always reflects the latest trends and information. With a broad research and analysis capability, Transparency Market Research employs rigorous primary and secondary research techniques in developing distinctive data sets and research material for business reports.

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