Automation is a driving force in manufacturing, enabling quality and scalability during production and assembly. In contrast with the automotive industry, civil aerospace automation has traditionally lagged. However, the adoption rate of methodologies embracing automation for manufacturing, assembly, and testing is now accelerating, with new technologies being tested to enable reliable and safe assembly and inspection steps. This paper introduces a semi-automated system for quality control during the final production steps of single-aisle aircraft, namely after the automated assembly of hatrack and sidewall elements in the passengers' area, but before any seating elements are assembled in the environment. Quality control is performed using color and 3d cameras mounted on a custom holonomic mobile robot. The acquired data is processed for identifying geometrical or surface defects by using machine learning based models and 3D processing-based algorithms. The results are provided to an inspector officer using different on-site and off-site validation modalities. The obtained results enable us to affirm that the proposed solution looks very promising for semi-automatic quality control, and it can serve as a foundational framework for efficient manufacturing in the aerospace industry.

VISTA — Vision-based inspection system for automated testing of aircraft interiors: A panoramic view

Mosca, Nicola
Co-primo
Writing – Original Draft Preparation
;
Renò, Vito
Co-primo
Writing – Review & Editing
;
Nitti, Massimiliano
Co-primo
Conceptualization
;
Patruno, Cosimo
Secondo
Writing – Review & Editing
;
Negri, Simone Pio
Penultimo
Methodology
;
Stella, Ettore
Ultimo
Project Administration
2024

Abstract

Automation is a driving force in manufacturing, enabling quality and scalability during production and assembly. In contrast with the automotive industry, civil aerospace automation has traditionally lagged. However, the adoption rate of methodologies embracing automation for manufacturing, assembly, and testing is now accelerating, with new technologies being tested to enable reliable and safe assembly and inspection steps. This paper introduces a semi-automated system for quality control during the final production steps of single-aisle aircraft, namely after the automated assembly of hatrack and sidewall elements in the passengers' area, but before any seating elements are assembled in the environment. Quality control is performed using color and 3d cameras mounted on a custom holonomic mobile robot. The acquired data is processed for identifying geometrical or surface defects by using machine learning based models and 3D processing-based algorithms. The results are provided to an inspector officer using different on-site and off-site validation modalities. The obtained results enable us to affirm that the proposed solution looks very promising for semi-automatic quality control, and it can serve as a foundational framework for efficient manufacturing in the aerospace industry.
2024
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA) Sede Secondaria Bari
Aircraft interiors
Assembly lining
Computer vision
Quality control
XR validation modalities
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/515375
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