ARTIFICIAL TECHNOLOGY IN 2024 ADVANCEMENTS
In Search Of Artificial Intelligence And Better Outcomes
The term “artificial intelligence” was coined more than 60 years ago, but only recently have we begun to realize all the benefits of AI, machine learning and deep learning in our everyday lives.
Artificial intelligence, Deep Learning / Machine Learning Systems are having a major impact on the aerospace industry, too. With the technologies mentioned above, flying is becoming safer, more comfortable, more predictive and outcome based. Airlines improve schedule performance, use less fuel and create a better passenger experience. Airports are more efficient and easier for travelers to navigate. Ground crews turn flights around faster and dispatch operations are getting more efficient and autonomy based. Airlines are able to use the learning systems to derive better segment strategies and charge according to the relevance and value. And aircraft maintenance is easier, faster, prescriptive and more precise.
All this – and much more – is possible because aerospace is such a data-rich ecosystem. With recent advancements in connectivity, data analytics and the Industrial Internet of Things (IIoT), we can use the vast amounts of data available from disparate systems on and off the aircraft to drive outcomes that impact the operational efficiency, mission effectiveness and profitability of all kinds of operators. AI, Machine Learning and Deep Learning are the engines that connects brains throughout the ecosystem. Not to leave out manufacturing, the digital—physical—digital loop bound by digital threads is taking Industry 4.0 to an altogether different level by creating self-learning networks capable of bringing in an astounding level of autonomy and decision making without humans in the loop.
Let’s look at a few areas in the airline world which are impacted very positively and deeply. For example, artificial intelligence is getting at the heart of maintenance solutions, which provides maintenance techs with an unprecedented level of information and insights about the performance and health of onboard aircraft systems. Airline operators have experienced a 35 percent reduction in operational disruptions thanks to artificial intelligence and deep learning infusion.
With AI and Deep Learning, the intelligent and self-learning maintenance system has the capability to monitors onboard systems, model nominal behavior, detect aberrations and analyzes data and patterns from past events to predict that a fault will occur days in advance. Then, the system provides prescriptive insights to recommend corrective actions and alert the supply chain to order the right parts and materials.
Airlines spend a lot on fuel and what a treat would it be to use modern technologies to bring down this significant cost. AI and Deep Learning Models can crunch data from hundreds of available sources and make recommendations that can reduce fuel consumption and hence operation cost. Even a 1-3 percent saving amounts to tens-of-millions of dollars in annual savings for some carriers. And all this is being made possible by the ingress of intelligent and self-learning models. It is helping airlines uncover novel fuel savings opportunities that are tailored for their specific fleet and operating profile, covering critical factors such as weight, engine utilization and fuel planning.
Another great case where we see lot of benefit is streamlining and make ground operations more efficient and automated. Connectivity, data analytics expertise and modelling the success criteria help airlines reduce block time by improving the ground-handling process, which can have a significant impact on the carrier’s on-time performance. It enables airlines and ground service providers reduce turn-around time by as much as 13 – 15 percent, increasing the number of flights that takeoff on time, a key airline metric and passenger-satisfaction factor.
The setup gives the operations team real-time insight into the status, location and activity of all aircraft and ground equipment, creating the first truly “connected ramp.” Ground vehicles transmit data to the enabling solution, allowing users to monitor vehicle use, improve services and enhance safety.
There are many other examples of how connected aerospace, AI and advanced data analytics are helping to reinvent the entire air transportation system by smashing down the data silos of the past and bringing the power of connected to deliver better outcomes for everyone in the aerospace ecosystem
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