Researchers are developing a system based on artificial intelligence (AI) to pinpoint internal flaws in aircraft quickly and accurately that are missed otherwise.
Aircraft made mostly from composite materials are already on the drawing boards of major aeronautical manufacturers, which seek lighter planes able to carry more passengers, cargo and fuel.
While these ultralight materials are available, their widespread use is problematic because scanning them for potential flaws is expensive and more time—consuming than similar processes used for checking and certifying metals.
Swinburne University of Technology researchers are tackling this challenge by developing an automated approach, based on AI technology that greatly speeds up analysis and accuracy than a human technician can ever achieve.
“There is a lot of pressure on the technicians who analyse the scans of composite materials for certification,” said Mark Hodge, CEO of the Defence Materials Technology Centre, based at Swinburne’s Hawthorn campus, according to a Swimburne statement.
“Getting it wrong could cost lives and a lot of money. The risk of those consequences means there is a tendency for the technician to be conservative and not certify parts that have any potentially threatening flaw,” he said. Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."
The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings, issues which have been addressed by myth, fiction and philosophy since antiquity.Artificial intelligence has been the subject of optimism,suffered setbacks and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.
AI research is highly technical and specialized, and deeply divided into subfields that often fail to communicate with each other.Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. General intelligence (or "strong AI") is still among the field's long term goals.
Aircraft made mostly from composite materials are already on the drawing boards of major aeronautical manufacturers, which seek lighter planes able to carry more passengers, cargo and fuel.
While these ultralight materials are available, their widespread use is problematic because scanning them for potential flaws is expensive and more time—consuming than similar processes used for checking and certifying metals.
Swinburne University of Technology researchers are tackling this challenge by developing an automated approach, based on AI technology that greatly speeds up analysis and accuracy than a human technician can ever achieve.
“There is a lot of pressure on the technicians who analyse the scans of composite materials for certification,” said Mark Hodge, CEO of the Defence Materials Technology Centre, based at Swinburne’s Hawthorn campus, according to a Swimburne statement.
“Getting it wrong could cost lives and a lot of money. The risk of those consequences means there is a tendency for the technician to be conservative and not certify parts that have any potentially threatening flaw,” he said. Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."
The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings, issues which have been addressed by myth, fiction and philosophy since antiquity.Artificial intelligence has been the subject of optimism,suffered setbacks and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.
AI research is highly technical and specialized, and deeply divided into subfields that often fail to communicate with each other.Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. General intelligence (or "strong AI") is still among the field's long term goals.
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