With the EU’s Green Deal Climate Act, airlines encounter the challenge of reducing their impact by operating in a climate-neutral manner. Fuel cell technologies, including Low Temperature Proton Exchange Membrane Fuel Cells and Solid Oxide Fuel Cells, are suitable candidates for this endeavour. However, there is uncertainty surrounding the maintenance scope and corresponding costs of novel systems such as fuel cells, that is leading to reluctance within the industry to implement these technologies. This study addresses this research gap by assessing the fuel cell systems using the Reliability Centered Maintenance approach and the MSG-3 framework. For this purpose, task intervals are determined based on statistical reliability values from literature and data from legacy aircraft. As a final step, the scheduled maintenance scope is derived, accounting for the required maintenance tasks, corresponding intervals, and parts of the labor and material scope. The aim of this comparative study is to identify the fuel cell system best suited for regional aircraft operations based on its maintenance characteristics. This enables us to provide designers and researchers with valuable insights to support the development of technically feasible fuel cell systems for the aviation industry.

With increasing adoption of carbon fiber reinforced polymers in modern aircraft, new challenges in the maintenance of these structures arise. These materials are prone to internal damages such as delaminations, necessitating advanced non-destructive testing methods like ultrasonic testing. Guided ultrasound waves are a promising solution for testing large thin-walled structures like aircraft fuselages due to their long propagation range and high sensitivity to internal damage. However, traditional methods like laser-doppler vibrometry, while effective, are limited by their reliance on surface reflective properties, restricting their applicability in real-world maintenance scenarios. In this paper, a laser-based optical microphone is used to detect and visualize guided waves in carbon fiber reinforced polymer materials, featuring a very high bandwidth and independence from surface reflectivity. A robot test setup is developed to sample areas on the plate through repeated experiments. Signal processing enables the analysis of the wavefield and the visualization as two-dimensional wavefield images. By introducing defects into the plate, it is shown that these can be detected by changes in wave propagation patterns. With the flexible test setup using a robotic arm, the scalability of this approach to more complex structures with curvatures is demonstrated, highlighting its relevance for future use in aircraft maintenance.

This paper introduces a novel robotic endoscope equipped with an optical microphone for non-destructive testing (NDT) of structural components using ultrasound guided waves. Conventional NDT often requires disassembling components, a labor-intensive and time-consuming process, especially for defects in carbon fiber reinforced polymers that are not visible externally. To address these challenges, a concept from minimally invasive medicine is transferred and a robotic prototype is developed that integrates endoscopic mobility, robotic precision and ultrasonic inspection capabilities. A test stand demonstrates the robot’s ability to navigate confined areas and perform internal ultrasonic measurements. By scanning the surface of components, the system generates full wavefield images and post-processing reveals alterations in the structure, offering insights into structural damage that traditional visual inspections may not detect. This technology is particularly promising for applications like the inspection of hydrogen storage tanks, where conventional methods are limited.

Markerless tracking methods have undergone continuous improvements in terms of the required computing power, tracking stability and reliability. However, accuracy and precision of markerless tracking depends not only on the algorithm used and the environmental conditions, but essentially on the shape of the tracked object. For example, the tracking result is influenced by the component's dimensions, symmetries, edges, occlusions, and colors. To support design decisions in order to obtain a component with an optimal shape for good tracking results, a simulation with parameters of the component, the tracking camera, and the environment can be performed during the design phase. However, the projection of simulation results into real environments can only be verified on an experimental basis. In an experimental setup, the position and orientation of a previously designed component are recorded with the help of markerless tracking at predefined positions to assess its tracking performance. An examination of the measurement results confirms the different tracking ability of the regarded objects in this paper. This work presents a method to evaluate the expected tracking performance with regard to the design of a component before it is actually used in a real environment.

The adoption of automated visual inspection systems is growing across various industries, such as manufacturing and energy, and is expected to expand significantly into other sectors, including aerospace. However, these systems often encounter challenges when visually inspecting highly reflective metallic surfaces, as varying light conditions can obscure critical surface details, thus risking errors in defect detection. This paper addresses these challenges by developing methods to detect specular light reflections in order to automatically assess the quality of inspection images. This enables automated systems to take inspection images from different angles, to avoid undesired reflections. We show that U-Net based architectures trained on a novel dataset of inspection images and reflection masks lead to good detection under challenging conditions. The results demonstrate that Convolutional Neural Network (CNN)-based models, particularly U-Net++ with a ResNet-50 encoder, outperform Transformer-based approaches, achieving the highest accuracy in identifying reflective areas. While the proposed UNETR-Attention Fusion (UNETR-AF) model shows promise for smaller reflections, it struggles with larger ones. This research offers a practical solution for industries aiming to improve visual inspection reliability, particularly for safety-critical applications. By enabling automated systems to handle reflective surfaces effectively, it addresses a significant gap in current inspection technologies.

Globally interconnecting machines, processes, and resources driven by exploring and advancing new technologies defined Industry 4.0 (I4.0), resulting in, e.g., Cyber-Physical Production Systems (CPPS). The aircraft industry particularly struggled with transforming production and Maintenance, Repair, and Overhaul (MRO) processes, replacing humans with machines and automating as well as digitalizing significant parts of their value- and non-value-adding activities. However, in the face of current social and environmental challenges, future industries will need to shift from purely technology-driven to value-driven, working sustainably with resources, including human capital. Together, these approaches constitute the idea of Industry 5.0 (I5.0). On the one hand, the aviation industry faces the challenge that even I4.0 concepts and technologies are not yet fully exploited or implemented. On the other hand, due to the specific characteristics of aircraft production and MRO as well as the environmental impact of the product, a tremendous potential arises regarding placing human well-being back into the center of adding value and decreasing environmental footprint while building an industry that is resilient and fortified against disruptions of this era. In line with the I5.0 terminology, in this work, we outline the challenges and opportunities of integrating I5.0 principles into the aircraft production and MRO industries, focusing specifically on the scope of selected use cases.

The aviation industry relies on continuous inspections to ensure infrastructure safety, particularly in confined spaces like aircraft fuel tanks, where human inspections are labor-intensive, risky, and expose workers to hazardous exposures. Robotic systems present a promising alternative to these manual processes but face significant technical and operational challenges, including technological limitations, retraining requirements, and economic constraints. Additionally, existing prototypes often lack open-source documentation, which restricts researchers and developers from replicating setups and building on existing work. This study addresses some of these challenges by proposing a modular, open-source framework for robotic inspection systems that prioritizes simplicity and scalability. The design incorporates a robotic arm and an end-effector equipped with three RGB-D cameras to enhance the inspection process. The primary contribution lies in the development of decentralized software modules that facilitate integration and future advancements, including interfaces for teleoperation and motion planning. Preliminary results indicate that the system offers an intuitive user experience, while also enabling effective 3D reconstruction for visualization. However, improvements in incremental obstacle avoidance and path planning inside the tank interior are still necessary. Nonetheless, the proposed robotic system promises to streamline development efforts, potentially reducing both time and resources for future robotic inspection systems.

To ensure that air travel stays safe, airplanes are regularly maintained and repaired. Maintaining an aircraft is a very costly procedure; the longer the ground time of an aircraft is, the more profit is lost for the airline. At the same time, finding qualified employees is becoming increasingly difficult. To cope with this extra work and time constraints, a solution can be the digitalization and integration of new technologies that save time and ease the work of the employees. However, these solutions only reach their full potential if they are actually used. This is only achievable through the employees' acceptance of the new solutions. This paper examines the relationship between requirements for new aircraft maintenance technologies and the technology acceptance model (TAM). The requirements for an augmented reality (AR) Dent & Buckle Chart solution from a qualitative user study are used for this analysis. The analysis shows that the collected requirements highlight factors that lead to technology acceptance. Furthermore, it is found helpful to include qualitative questions about technology acceptance in the quantitative TAM questionnaire items to measure the acceptance level and contextualize the qualitative results. This also helps to identify features that users would appreciate, ultimately leading to higher acceptance.

Medical professionals require in-situ visualization of X-ray imaging in 3D to assist with surgical navigation and planning. Research on surgical Augmented Reality (AR) focuses on improving the tracking quality of devices and tools but disregards human requirements. Our user study evaluates application areas and potentials for AR in neurosurgery, as well as feedback for HoloLens 2 based inside-out tracking systems. The main findings include a reported simplification in perception and lowered mental workload. Additionally, we propose a simplified implementation for an infrared-based inside-out rigid body pose estimation system on HoloLens 2 to redirect feedback away from the tracking problem and gain access to human requirements for such systems. Decent patient and exemplary instrument tracking are reached.

The visual realism classification scale (VRCS) is a tool to help researchers judge, compare, and describe the visual realism of objects in virtual environments. In Human-Computer Interaction, visual realism is a much-investigated topic, as different tasks benefit from a particular level of detail. The subjective feeling of realism becomes more tangible by judging 3D objects based on the objective criteria: lighting, reflection, texture, structure, form , and internal consistency . This paper revises the original VRCS using statistical analysis and an expert focus group. The adopted changes are evaluated through a complementary user study of 34 participants, which resulted in high validity due to a significant correlation between the subjective measure and VRCS. Furthermore, the scale significantly predicts subjective realism and improves the inter-rater reliability on multiple questions. Using the focus group and user study results, this paper offers guidance on applying the VRCS in research.

The use of hydrogen as a fuel for aircraft is a topic that has been extensively researched. One of the major challenges that this research has identified is the safety concerns that are brought about by hydrogen leakages. This research focuses on the design of a smart sensor network comprising multiple sensors that are capable of detecting hydrogen leakages and performing condition monitoring in aircraft. MEMS (micro-electromechanical systems) sensors that are capable of responding to changes in temperature, pressure, humidity, gas resistance, and the changes in hydrogen concentration are used. Two distinct approaches to the design of a distributed sensor network are presented. The sensor network is intended to perform periodic condition monitoring, thereby enabling the detection and localization of a hydrogen leak. This paper discusses initial tests conducted to measure and locate hydrogen leakages in a laboratory setting.

Medical professionals require in-situ visualization of X-ray imaging in 3D to assist with surgical navigation and planning. Research on surgical Augmented Reality (AR) focuses on improving the tracking quality of devices and tools but disregards human requirements. Our user study evaluates application areas and potentials for AR in neurosurgery, as well as feedback for HoloLens 2 based inside-out tracking systems. The main findings include a reported simplification in perception and lowered mental workload. Additionally, we propose a simplified implementation for an infrared-based inside-out rigid body pose estimation system on HoloLens 2 to redirect feedback away from the tracking problem and gain access to human requirements for such systems. Decent patient and exemplary instrument tracking are reached.

Besides the fact that civil and military aerospace are governed by the same physics and design fundamentals, differences exist between the initial and continued airworthiness criteria for these two aviation fields. Whereas civil aerospace is highly regulated by national and international organizations, the military is mainly governed by national regulations or, in multinational projects, by agreed-upon regulations. A trend exists towards the homogenization of rules in both fields; however, due to national security interests, these are generally agreed upon on a case-by-case basis. This review aims to provide an overview of the processes employed for initial and continued airworthiness of civil and military aviation, focusing on the similitudes and differences.

This work presents a new concept for permanent markers consisting of RFID tags built into aircraft components made from fibre reinforced plastics. The novelty of this concept lies in the antenna design, which represents a geometric point that can be accessed using commonly employed non-destructive testing (NDT) methods, specifically suited for thermovision. These geometric points provide a reliable frame of reference for accurate data localization throughout the entire life cycle of the components. Initial results obtained with an antenna design incorporated into a glass-reinforced epoxy laminate quantify the anticipated localization accuracy achieved through our concept. We utilize a geometrically calibrated, off-the-shelf bolometer and standard lock-in thermography in our approach.

Knowledge about the location of a defect is essential for damage assessment. In terms of a digitalised maintenance, inspection data is combined with position information. The presented approach regards the manual ultrasonic inspection, where the ultrasonic probe and the inspected component are both hand-held. By using markerless tracking technologies, it is possible to track the component without any markers. The ultrasonic probe is tracked by a more stable marker-based tracking technology. This results in a hybrid tracking system, which allows a referencing of the non-destructive testing (NDT) data directly to the local coordinate system of the 3D model that corresponds to the inspected component. Transferring this approach to other manual inspection technologies allows for a superimposition of recorded NDT data without any postprocessing or transformation. A better damage assessment is thus enabled. The inspection system, the inspection tool calibration and the camera registration process are described and analysed in detail. This work is focused on the analysis of the system accuracy, which is realised by using a reference body.

3D models are at the core of every virtual and augmented reality application. They appear in varying degrees of visual realism complexity, depending on the intention of use and contextual as well as technical limitations. The research concerning the effects induced by different degrees of visual realism complexity of 3D models can be used to define in which fields and applications a high visual realism is needed. This paper proposes a classification of 3D models in extended reality applications, according to their visual realism complexity. To identify the aspects of realism classification this work considers how past studies defined the virtual realism complexity of 3D models and looks into approaches of diverse disciplines. After defining the visual realism complexity scale, the paper validates the method in a user study. The study was conducted with 24 participants that viewed 16 different 3D models in virtual reality and rated them with the proposed scale. The collected data shows a significant correlation between subjective realism and the proposed scale. Next to depicting visual realism, the scale also improves the explicitness of realism ratings. The classification enables scientists to specify the level of visual realism complexity of their used 3D models. At the same time, this opens up opportunities to conduct comparable research about visual realism complexity.

The processing of multiple data sets from different NDT vendors and systems can be challenging. Accessing the data requires dealing with different and often proprietary data formats. In addition to that the correct spatial alignment requires knowledge and information about the acquisition system and must consider different approaches for markers and reference coordinate systems. The key features of NDE 4.0 and digital twin concepts are storage and interoperability with standard data formats. In this example data from thermography, manual ultrasonic testing and immersion ultrasonic testing are considered. For established devices multiple tools exist for the conversion of data into image-based formats. However, besides the lack of spatial alignment there is a need to access the raw data for further processing. In medical and CT-like applications the DICOM format has become a widely used exchange format. Its derivative DICONDE transfers this into the field of NDT. This study demonstrates the use of this format for data processing from multiple NDT methods and addresses issues related to interoperability and the integration of less structured data from inspections.