Today’s vehicles are much smarter than just several years before. Thanks to advanced technologies like IoT, Big Data, Data Analytics, AI, cloud computing, cars have become safer, autonomous, and data-driven. They can be connected to everything: vehicles can easily communicate with surroundings including other vehicles, pedestrians, devices, infrastructure, grid, and smart homes. 

Given all this, routine car maintenance is not enough for modern vehicles that include millions lines of code and are equipped with various sensors and devices. Thus, automotive businesses are now increasingly moving from preventive maintenance to predictive maintenance. But how to implement predictive maintenance in the automotive industry? What benefits does it have? And what technologies are used? Here, you will discover the ins and outs of predictive maintenance in automotive manufacturing.

From preventive to predictive maintenance in the automotive industry

Until recently, preventive maintenance has been one of the most popular methods of vehicle maintenance. According to Plant Engineering’s Maintenance study report, 80% of businesses undertook a preventive maintenance strategy in 2018. And automotive was one of those industries that widely adopted preventive car maintenance. In comparison to the reactive type of maintenance that allows assets to run to failure, preventive approach is more cost-effective and efficient. 

Preventive maintenance in the automotive industry has many applications:

  • Regular oil change
  • Transmission checkup
  • Belt change
  • Brake and tire inspection 
  • Coolant replacement
  • Engine air filter and cabin filter change, etc.

All these things should be checked on a regular basis. In this case, traditional checklists and regular quality control procedures work well. Based on instructions from original equipment manufacturers (OEMs) and the history of past failures, car owners can prevent the breakdown or degradation of a piece of equipment, component, or spare part. They can identify the frequency in which the equipment can have a breakdown and require repair/service and schedule a maintenance plan accordingly.

But there are specific issues that depend on the driver’s behavior and the conditions under which the car is kept. Thus, very often preventive maintenance is combined with predictive maintenance to cover use cases when it is not possible to establish a standard for the breakdowns of an asset and it can fail randomly. 

Also, with predictive maintenance, machines are serviced only when it is actually required. This way, it helps reduce over-maintenance and no-fault-found events that cause service standstill and cost companies a lot of trouble.

But predictive maintenance is hard to implement when there is no record of planned maintenance activities. In this case, preventive maintenance serves as a good basis for kicking off predictive maintenance. So, in the majority of industries like automotive predictive and preventive maintenance go hand in hand. 

With the rise of intelligent technologies, predictive maintenance investments in transportation started to increase. Due to the Covid-19 crisis, many consumers prefer individual mobility at the expense of public transport and shared mobility services. The key reason behind this shift is concern over health and safety. Many consumers plan to buy a car. The demand for cars is going to be high while new vehicle production has slowed down due to lockdowns and disrupted supply chains. Thus, it is expected that we will all see the rebirth of the used car market. Used car sales and used car leasing will fill gaps between customer demands and low new vehicle production. Predictive maintenance will greatly help prolong the lifespan of the used cars and prevent unexpected downtimes.
Predictive maintenance in the automotive industry (investments)

Uses cases of predictive maintenance in automotive:

  • Trouble code analysis: finding bugs in code that can lead to vehicle failures.
  • Roadside assistance: vehicle data helps roadside service providers determine where exactly the car broke down and what’s wrong with it. It also helps determine if roadside assistance is even needed: maybe over the phone assistance about how to fix the car would be enough.
  • Tracking vehicle health indicators: an early warning that a part is likely to fail and the estimated time to failure. 
  • New insights for OEMs: giving feedback to OEMs to enhance security, performance, and lifespan of vehicles.

Predictive maintenance brings a myriad of advantages to OEMs, fleet operators, and private users:

  • Security
  • Reduced maintenance costs
  • Improved vehicle lifespan
  • No downtime
  • Less warranty claims 
  • Optimized spare parts inventory

how predictive maintenance works in the automotive industry

Technologies that power predictive maintenance in the automotive industry

Cars are going to become an integral part of connected living solutions. Modern technologies can connect the vehicle-to-home, vehicle-to-vehicle and vehicle-to-everything. With the help of cloud, IoT, predictive analytics, chances are your next car will be a lot like your smartphone. 


For effective predictive maintenance in automotive, it is important to have enough reliable data for accurate analysis and predictions. Connected IoT sensors can provide up-to-date data on vehicle parts and send Diagnostic Trouble Codes (DTCs) to track mechanical failures in real time. There are various types of sensors that can help you monitor everything from fuel consumption and engine temperature to fluid levels and run time:

  • Oil & lubricant sensors
  • Thermal imaging sensors
  • Sensors enabling vibration, sonic, and ultrasonic analysis, etc.

Big Data & Data Analytics

Data in automotive comes from IoT sensors and history of previous repairs. These are huge volumes of data, which help predetermine the characteristics or behavior of a machine ( as well as a human being in some situations) in certain environments and situations. Thanks to big data:

  • drivers can make more-informed decisions on the road avoiding crashes due to sudden car malfunctions; 
  • car makers can ensure long-term wear and tear; 
  • and fleet managers can save a lot of money on maintenance by doing service on a car only when it is needed.

AI and ML algorithms turn your vehicle data into insights. Implementing advanced analytics can not only increase productivity and safety of your vehicle but also reduce warranty costs by 15 to 20 per cent. For a large OEM group, this could mean savings of up to £200 million per year. Automotive data analytics companies can help you gain the maximum of your investment in predictive maintenance.


Interactive reporting is one of the key requirements of today’s customers. User-friendly and comprehensive dashboards help:

  •  monitor the most critical data,
  •  analyze technical parameters, 
  •  and react to potential issues.

Cloud computing

Judging from the amount of data that comes from many sensors, cloud is the best solution to storing and operating this data. In contrast to physical data centers, cloud offers cost-efficiency and high flexibility. Cloud computing: 

  • ensures on-demand scalability;
  • allows for processing big data sets;
  • and provides access to critical data from everywhere. 


Wireless connectivity has a significant positive impact on predictive maintenance. Especially 5G provides the ability to transfer high volume data with low latency, enabling real time data analysis of equipment. This is particularly important for the automotive industry. It is expected that between 2020 and 2025, 5G and 4G will coexist, and starting in 2025, we will see the increased use of 5G in automotive and other industries.

Case study: Implementing preventive and predictive maintenance for effective asset performance

About the client

Our client is a US-based company that manufactures, distributes, and services electronic test tools and software for measuring and condition monitoring. The company provides automobile combines like Toyota, Volkswagen with solutions to improve asset performance and reduce maintenance costs.

N-iX approach

The N-iX team has helped the client improve equipment uptime, reduce maintenance costs and ensure better performance of the client's products by arming maintenance teams with critical asset information and tools that can effectively process it.

N-iX experts have been working on a solution that enables users to perform work order management and inventory management tasks from mobile devices. Our software developers are responsible for reactive and preventative maintenance of the equipment based on a predefined calendar. Also, we have ensured that the alarm module works on a set of rules based on real-time data. 

In collaboration with the client, our specialists are working on developing a predictive maintenance solution based on vibration data for essential machinery: motors, pumps, fans, gearboxes, etc. Data is collected with the help of handheld devices during inspection rounds or online sensors installed on an asset permanently. The approach depends on the data available, its amount, quality and type, from statistical and mathematical methods to ML and AI algorithms: rule-based, auto-encoders, neural networks or image recognition. Vibration data is analysed either to extract features like crest factor, 0-P, P-P, kurtosis, etc. or to convert it into appropriate format for an input into the model. Implementing such solution will help the client detect failures on earlier stages with less effort, higher efficiency, helping vibration experts focus on more complex analysis.  

How N-iX can help you with predictive maintenance in the automotive industry

  • We have more than 2,200 IT specialists onboard ready to support your project with relevant automotive expertise;
  • You can benefit from our expertise in such domains as Cloud, Big Data, Business Intelligence, Data Science, Data Analytics, Artificial Intelligence & Machine Learning, and more;
  • N-iX has been providing offshore development services for over 21 years.
  • We have a proven track record in delivering IT outsourcing services to many automotive companies including Cardo, Bycyklen, and iCabbi;
  • We have delivery centers in Ukraine, Poland, Sweden, Malta, and the USA, which allows, which allows us to access a wide pool of professional automotive software developers;
  • N-iX has a reputation of a trusted IT outsourcing services provider, which is supported by numerous awards and industry ratings, including IAOP, GSA, Inc. 5000, Software 500,, and others;
  • N-iX complies with the security standards and regulations, such as ISO 27001:2013, PCI DSS, ISO 9001:2015, GDPR, and HIPAA to ensure secure software development.