Applying the Technology Acceptance Model to Understand Aviation Students’ Perceptions toward Augmented Reality Maintenance Training Instruction

Augmented Reality (AR) Technology, since its inception, has been enhanced significantly by software and hardware developers, and has been widely utilized in various fields such as manufacturing, entertainment, architecture, commerce and education. In recent years, maintenance instructions developed on the basis of AR technology have demonstrated their potential to positively impact maintenance training and technical tasks in aviation. Features of AR maintenance instructions include interactive content, user-friendly operation interface, enhanced visualization and real-time data feeds. The researchers conducted a case study of forty-one aviation maintenance students at a Midwestern university. The purpose of this study was twofold: to evaluate the Technology Acceptance Model as a valid framework for assessing AR implementation in aviation maintenance training; and to evaluate students’ acceptance of AR instructions in aviation maintenance training. On one hand, The Technology Acceptance Model (TAM) can help identify and prove the relationships among variables affecting aviation students’ perceptions and future use of AR instructions, including perceived usefulness, perceived ease of use, attitude toward using, and intention to use. On the other hand, the results may help establish an initial benchmark for aviation students’ acceptance of AR instructions in a maintenance training setting

Examining the Use of Model-Based Work Instructions in the Aviation Maintenance Environment

Part 2: PLM for Sustainability, Traceability and PerformanceInternational audienceA fundamental tenet of product lifecycle management (PLM) environments is the use of high-fidelity, 3D product models. The capability to create models with high degrees of fidelity to the physical world has driven companies to extract as much benefit and use from these digital assets as possible throughout the design, production, and support stages of the lifecycle. This is particularly apparent in the aviation industry where aircraft lifecycles routinely reach 80 years or longer. As the aviation industry migrates to the use of 3D model-based communications mechanisms in lieu of 2D drawings, multiple factors will impact the use of digital model-based work instructions, including the device, the form of the product model data, and levels of detail in geometry and interactivity. This paper will present a series of short studies conducted over the last three years using novice university students and expert university staff aircraft mechanics to evaluate the use of model-based work instructions in a general aviation maintenance environment. The results indicate that varying levels of detail and levels of interactivity have an effect on number of errors, time on task, and mental workload

Examining the Use of Model-Based Work Instructions in the Aviation Maintenance Environment

Part 2: PLM for Sustainability, Traceability and PerformanceInternational audienceA fundamental tenet of product lifecycle management (PLM) environments is the use of high-fidelity, 3D product models. The capability to create models with high degrees of fidelity to the physical world has driven companies to extract as much benefit and use from these digital assets as possible throughout the design, production, and support stages of the lifecycle. This is particularly apparent in the aviation industry where aircraft lifecycles routinely reach 80 years or longer. As the aviation industry migrates to the use of 3D model-based communications mechanisms in lieu of 2D drawings, multiple factors will impact the use of digital model-based work instructions, including the device, the form of the product model data, and levels of detail in geometry and interactivity. This paper will present a series of short studies conducted over the last three years using novice university students and expert university staff aircraft mechanics to evaluate the use of model-based work instructions in a general aviation maintenance environment. The results indicate that varying levels of detail and levels of interactivity have an effect on number of errors, time on task, and mental workload