Jan 26, 2026
Industrial maintenance in your pocket
Industrial maintenance still relies heavily on physical sensors, visual inspections, and the experience of field teams. Today, everyday tools like smartphones, thanks to their numerous sensors (microphone, camera, accelerometer...) and artificial intelligence, allow maintenance to be done differently: faster, more simply, and at a lower cost. This is not a promise. It is already an industrial reality. Here are two field returns, from projects carried out with major industrial players.
✈️ Airbus: listening to an airplane to avoid a global recall
On A380 airplanes, some defective door seals generated, at certain altitudes and speeds, unpleasant noises for passengers. The real issue was not the noise itself.
It was to precisely identify which seals were involved. A global recall of the fleet would have been long, complex, and extremely costly.
The implemented solution:
A mobile application has been made available to the onboard teams. With a simple smartphone, the noise emitted by the door is captured and then analyzed.
The application automatically identifies the defective seal or seals. An industrial Shazam, in a way. The approach relies solely on fine analysis of the acoustic signal (thanks to AI), without adding specific sensors or modifying the airplane.
The benefits:
No massive recall of the fleet
Targeted replacement only of the affected seals
Problem resolved in less than 9 months, instead of the 2 years initially planned
Non-invasive, discreet, and low-cost method.
🚆 SNCF: listening to trains to repair them better
When a problem arises with a train engine, the diagnosis still heavily relies on the listening and experience of the mechanics. Quickly identifying the source of an abnormal noise is not easy.
And without the right diagnosis, interventions take longer, sometimes involving several unnecessary trips.
The implemented solution:
The mechanic uses a simple smartphone to record the engine noise.
The application analyzes the signal and compares it to known signatures. It offers diagnostic leads and repair recommendations.
It also allows verifying that the repair is correct when the engine noise returns to being perfectly normal.
The benefits:
Faster and more reliable diagnostics
Fewer unnecessary returns to the workshop
Sharing and sustainability of professional expertise
🏭 Why these approaches concern all industries
These cases are not limited to aviation, railways, or even just sound analysis. In the industry, the observations are often the same:
ever more complex equipment,
a great diversity of models,
the necessity to make machines last,
a shortage of experienced profiles,
production stoppages that are costly.
Sound, image, and video are already there, directly on the field.
The real breakthrough is being able to exploit them on a large scale thanks to AI, relying on consumer-grade hardware, with a level of reliability now compatible with industrial uses… and at a lower cost.
🧑🔧 A situation that many will recognize
Let me describe a very concrete situation.
A situation that you have probably already experienced. A technician is urgently called to a client.
His colleague is absent.
He does not have all the details of the problem.
He is not familiar with the context.
He does not really know what actions have already been taken on the equipment. In short, this is clearly not the ideal situation for a calm intervention.
And the chances that the intervention will become complicated, or that the relationship with the client will become tense, are very real. This scenario has become almost commonplace in the field.
A pragmatic solution:
To respond to these situations, mobile applications for AI-assisted diagnostics now allow technicians to be concretely supported, where it matters: on the field. With a simple photo of a machine taken from their smartphone, the application can:
identify the machine, its location, and its characteristics,
retrieve the history of interventions,
propose the correct manuals and the maintenance contract,
suggest corrective actions.
And that's not all. It can also:
share information with a colleague and exchange interactively,
contact the right supplier or advanced assistance if necessary,
automatically generate a clear and understandable intervention report for the client.
All without burdening the technician's daily routine or multiplying tools.
🚧 What these field feedbacks really say
Behind these examples, the message is ultimately quite simple. With everyday tools like smartphones, and an artificial intelligence designed for specific uses, it becomes possible to bring value quickly, where teams really need it. We capture a sound, an image, a video.
We analyze.
And we help the technician make the right decision. This approach is also more accessible.
It is not only aimed at large groups capable of investing massively.
SMEs and mid-sized companies can also fully benefit from it, without heavy projects or exorbitant investments. We move away from cumbersome systems.
We move towards simple, useful, and genuinely adopted tools by the field. Solutions that do not replace humans, but help them, secure them, and save them time. And in the end, it is this simplicity that makes all the difference.
📱To go further
Do these topics resonate with you?
Are you wondering how to apply them concretely in your industrial context?
Contact us and we will be pleased to meet you.
I am Audrey, and I will tell you what is happening at akawan.
