Application of OCR-based assistance solutions in engine maintenance
Sophie Sandner, Phillip Bausch, Nikolai Strek, Joachim Metternich · Procedia CIRP · 2024
The aviation industry is one of the leading transportation sectors with a rising number of passengers worldwide. However, this rise in demand leads to increased maintenance requirements for the engines. Jet engines are comprised of many components each denoted with a part and serial number. The data entry task for mechanics can be cumbersome and human errors can lead to incorrectly documented numbers and even result in severe safety issues. To assist mechanics in the task of recognizing and transcribing serial numbers, optical character recognition methods are being considered, with no satisfactory solution being found yet. This paper addresses this issue by comparing possible optical character recognition methods and identifying ways to improve the error rate based on a real use case.