Today, vehicles are smarter and safer than ever thanks to sophisticated technologies. Cars are data-driven and connectable to everything: other cars, infrastructure, pedestrians, the grid, and even smart homes. A key component of this advancement is predictive maintenance. By 2027, the global demand for these systems is expected to exceed $2.7 billion!

Preventive maintenance does not suffice to meet the needs of car owners. In addition to the spare part catalogs from epcatalogs.com, diagnostic programs, and service manuals, technicians need predictive tools. Here is how they work and where they are used.

Engine mechanic with hood of car open

The Definition

So, what is predictive maintenance all about? It is a set of techniques and systems for the detection of defects and irregularities. Its output determines the appropriate time for maintenance. Essentially, it lets experts fix problems before they manifest themselves.

Predictive maintenance is a cost-saving approach based on statistical process control, and it starts from monitoring the entire operation. Then, the system collects, stores, and processes the data to produce forecasts. The key applications include:

  • Scheduled oil change
  • Checking of transmission
  • Changing of belts
  • Inspecting brakes and tires
  • Replacing coolant
  • Changing cabin filter and air filter, etc

The Advantages of Predictive Maintenance

In recent years, predictive maintenance has evolved from an option into an essential for the automotive industry. The value it brings is undeniable. Using predictive tools, experts can:

  • anticipate impending failures, monitor asset condition
  • monitor the equipment around the clock
  • ensure reliability
  • assess any rotating equipment quickly on site
  • eliminate downtime thanks to enhanced security

Underlying Technologies

Predictive maintenance requires the collection of reliable data. IoT sensors send diagnostic trouble codes for failure tracking in real-time. You can monitor changes in temperature, fuel consumption, run time, etc. These data collection devices include:

  • sensors for oil and lubricants
  • sensors for thermal imaging
  • sensors for sonic, ultrasonic, and vibration analysis

Big Data and Analytics

Sensors and the history of previous repairs provide a massive amount of data. It allows the predetermination of characteristics or behavior in different circumstances. ML and AI algorithms turn the readings into insights. Predictive maintenance boosts productivity and safety while reducing warranty costs. For example:

  • drivers can avoid traffic accidents due to unforeseen car malfunctions,
  • manufacturers can provide long-term wear and tear,
  • fleet managers reduce maintenance costs, as they do not service cars until it is appropriate.

Interactive Reporting

Comprehensive dashboards give immediate access to relevant data and parameters. The users can monitor all critical data and react to potential issues.

Cloud Computing

Clouds are more cost-efficient and flexible than physical storage. They can accumulate data from different sources, support scalability and provide access from anywhere.

Steering wheel with hand on it

To Sum Up

IoT sensors, Big Data, interactive reports and cloud computing are only some systems powering predictive maintenance. It provides a plethora of benefits to drivers, fleet managers and OEMs. These new technologies offer security, cheaper maintenance, longer lifespan of vehicles, absence of downtime, and other advantages.

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