Generative AI: the key to Maintenance 4.0
Generative AI: a new horizon for predictive maintenance
The rise of generative AI marks a new stage in the transformation of industrial maintenance. After years of predictive maintenance based on structured data and conventional sensors, the latest AI models are now paving the way for the exploitation of previously unusable data: free text, images, weak signals, etc.
“Generative AI now makes it possible to exploit unstructured data that was previously non-existent,”
emphasises Alexandre Ribeiro, CEO of BeTomorrow. Thanks to advances in LLM, these capabilities are becoming accessible not only to large corporations, but also to SMEs and mid-cap companies.
The example of the start-up Wormsensing perfectly illustrates this shift. Born out of CEA-LETI, the young company has developed ultra-thin sensors capable of detecting the slightest vibrations in industrial machinery. Combined with analytical AI, these patches identify abnormal behaviour at an early stage to prevent breakdowns. "This is a prime example of what we can do today with AI in maintenance", says Alexandre Ribeiro, who sees these innovations as a major milestone in Maintenance 4.0.
Beyond sensors, generative AI is also revolutionising the use of textual data produced on a daily basis in factories. Thousands of maintenance tickets written freely by operators can now be analysed automatically to optimise maintenance cycles, component life and team organisation. Where industry once had a mass of dormant information, it can now draw actionable insights from it without any additional effort.
Towards maintenance 4.0 accessible to all businesses
Finally, this revolution is distinguished by its rapid dissemination and increased accessibility. Advanced AI solutions, once reserved for industrial giants, are now within reach of businesses of all sizes. Alexandre Ribeiro highlights another major change: the ability for field teams to "question data more directly" without going through long cycles of dashboard generation. This technological democratisation clearly paves the way for more agile, predictive and efficient maintenance.
Read the full article published in Les Echos HERE.
