Example of predictive maintenance
- Our client has a portfolio of 1,500 tunnels
- The park is aging and maintenance costs are high
- Tunnels are inspected and assessed every 5 years on average
By using data from inspection surveys carried out over the past 30 years, the objective is to understand how this fleet of tunnels is changing in order to calculate an aging rate associated with each type of tunnel. This makes it possible to better predict the next moments of intervention, just in time and at a lower cost, to avoid accidents and plan the maintenance budget, thanks to predictive maintenance.
How are inspections carried out?
A tunnel is cut along its length into successive sections of 5 meters each. In each section, the damage is listed (nature, size, location, etc.) and digitized. An overall score describing the state of degradation, called the rating below, is assigned to each section. This dimension varies over time during the various inspections and makes it possible to assess and quantify the deterioration of a tunnel.
The hypothesis put forward by our client is that this coast evolves at a speed depending on various listed criteria: geological nature of the terrain, dimensions and materials of the tunnel, etc.
What is predictive maintenance?
It is a method which consists in anticipating failures, damages, breakdowns by carrying out models of degradation of the systems with the aim of predicting the evolution of a quantity, in this case a coast. Predictive maintenance therefore makes it possible to reduce costs and anticipate breakdowns or damage.
Use of machine learning models to predict the aging rate of a tunnel based on its construction and environmental characteristics.