Inspection and maintenance are essential for nuclear but also for any industrial sector encompassing industrial processes. Downtimes of a plant can have impact on the safety of the installation and lower production, having a financially negative impact. Through preventive maintenance, equipment can be fixed, changed and upgraded before a breakdown, making it essential.

However, preventive activities have a cost in terms of resource mobilisation and finance. To defining the right frequency of preventive maintenance, inspection and maintenance must be done on a regular basis, even while the equipment is still functioning. The right balance is to minimise as much as possible the frequency of preventive walkdowns to optimise your maintenance budget and remain in the safe zone.

There is a lot of details to consider. Each equipment has characteristics that can impact its availability: type and origin of material, usage, external conditions, type of impact on the safety of the plant, etc.

This is where risk-based maintenance can optimise resources. Mobilising probabilities and root cause analysis, this methodology takes quantitative information and turns them into a probability of failure.

So far, this approach was only accounting for physical and chemical parameters that can lead to a failure, but it does not consider the business aspects, the regulatory information, the manufacturer profile or the OPEX shared by other plant operators. Now, with the rise of AI and data science, there is a great opportunity to account for all those unaccounted parameters to turn a risk-based approach into something broader, more holistic to further help towards operational excellence.