https://en.sputniknews.africa/20250822/we-cant-wait-for-failure-nigerian-aviation-expert-builds-ai-for-early-aircraft-fault-detection-1077303929.html
‘We Can’t Wait for Failure’: Nigerian Aviation Expert Builds AI for Early Aircraft Fault Detection
‘We Can’t Wait for Failure’: Nigerian Aviation Expert Builds AI for Early Aircraft Fault Detection
Sputnik Africa
Across Africa, aviation remains both a symbol of connectivity and a test of resilience. With safety central to air travel and maintenance often proving... 22.08.2025, Sputnik Africa
2025-08-22T14:19+0200
2025-08-22T14:19+0200
2025-08-22T14:19+0200
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'We Can't Wait for Failure': Nigerian Aviation Expert Builds AI for Early Aircraft Fault Detection
Sputnik Africa
Across Africa, aviation remains both a symbol of connectivity and a test of resilience. With safety central to air travel and maintenance often proving complex, new approaches are emerging. Innovators are turning to artificial intelligence as a tool to strengthen reliability and keep the continent's skies secure.
One of those innovators is Ndubuisi Chibuogwu, an Airworthiness Inspector and licensed aircraft maintenance engineer (avionics) with Nigeria's Civil Aviation Authority. Building on a decade of fieldwork, he has created a lightweight AI-based predictive maintenance system designed to spot hidden risks early and support safer, more cost-effective flight operations.
One of those innovators is Ndubuisi Chibuogwu, an Airworthiness Inspector and licensed aircraft maintenance engineer (avionics) with Nigeria’s Civil Aviation Authority. Building on a decade of fieldwork, he has created a lightweight AI-based predictive maintenance system designed to spot hidden risks early and support safer, more cost-effective flight operations.In his conversation with Global South Pole, Chibuogwu explained that traditional “reactive” approaches to aircraft maintenance leave room for risk, because faults are only addressed after they appear. He stressed that predictive tools powered by data and machine learning can shift aviation toward anticipating and preventing problems before they occur.To listen to the whole discussion, tune in to the Global South Pole podcast, brought to you by Sputnik Africa.In addition to the website, you can also catch our episodes on Telegram.► You can also listen to our podcast on Apple Podcasts, Spotify, Deezer, Castbox, Pocket Casts, Afripods, Podcast Addict, Overcast, and Mave Stream.► Check out all the episodes of Global South Pole.
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‘We Can’t Wait for Failure’: Nigerian Aviation Expert Builds AI for Early Aircraft Fault Detection
Aliyu Bello
Correspondent, Podcast Host
Across Africa, aviation remains both a symbol of connectivity and a test of resilience. With safety central to air travel and maintenance often proving complex, new approaches are emerging. Innovators are turning to artificial intelligence as a tool to strengthen reliability and keep the continent’s skies secure.
One of those innovators is Ndubuisi Chibuogwu, an Airworthiness Inspector and licensed aircraft maintenance engineer (avionics) with Nigeria’s Civil Aviation Authority. Building on a decade of fieldwork, he has created a lightweight AI-based predictive maintenance system designed to spot hidden risks early and support safer, more cost-effective flight operations.
In his conversation with Global South Pole, Chibuogwu explained that traditional “reactive” approaches to aircraft maintenance leave room for risk, because faults are only addressed after they appear. He stressed that predictive tools powered by data and machine learning can shift aviation toward anticipating and preventing problems before they occur.
“Aviation is a global industry […] My interest in predictive maintenance was sparked by a near decade of hands-on experience as an airworthiness inspector. Over the years, I’ve seen how relying on reactive maintenance […] waiting for something to go wrong and this usually puts safety at risk, interrupts operations, and drives up maintenance costs. This issue is even more pressing coming from a Nigerian experience, where older aircraft, limited diagnostic tools, and fragmented data systems often delay the early detection of wear and aircraft degradation. That’s what actually drew me to predictive maintenance. I saw it as a practical and scalable solution, one that you can use machine learning, AI and data to predict failures before they happen, even in a resource-constrained setting,” he said.
To listen to the whole discussion, tune in to the Global South Pole podcast, brought to you by Sputnik Africa.
In addition to the website, you can also catch our episodes on
Telegram.► Check out all the episodes of Global South Pole. 
