Machine-based Learning Solves a Long-standing Problem Impacting the Accuracy of Aircraft Data and Overall Safety.
Summary
ATP CaseBank®, a leading provider of information services and software solutions for the aviation industry, officially launched a new machine-based learning application, designed to help improve the accuracy of documenting Air Transport Association (ATA) codes. Revealed today at the 2019 Aviation Week MRO Europe show in London, the new feature is the latest in the continuing evolvement of the company’s ChronicX® software suite, a solution used by over 25% of the world’s commercial airline fleet to detect recurring or chronic issues on aircraft. “The airline industry has struggled for years with the accuracy of the ATA codes being applied to maintenance issues and its impact on the data they rely on to ensure the safety of their aircraft”, claimed James Geneau, Chief Marketing Officer at ATP CaseBank. “This new feature allows them to stay focused on the job at hand while maintenance control can rely on technology to ensure a higher degree of accuracy in the overall data needed to do their job”. The CaseBank software division provides troubleshooting, reliability, and defect trend analysis tools that help engineering and service teams accelerate equipment repair, increase uptime, reduce warranty costs, and improve product support and performance.
Classifications
AskAI Classifications
LabelsLinked Companies
