The purpose of this study was to determine the effects of a simulation with workedexamples on the creation of episodic memories and the troubleshooting ability of maintenance technician students. Previous research shows that domain knowledge, conceptual knowledge, strategic knowledge, and episodic memories are all required to successfully troubleshoot. While domain, conceptual, and strategic knowledge can all be taught using traditional instruction, episodic memories require students to experience the actual troubleshooting of a fault. Simulations and worked examples are two instructional methods that have proven effective at teaching troubleshooting. This research specifically examined how a simulation combined with worked examples would affect 1) immediate troubleshooting abilities, 2) the creation of episodic memories, and 3) delayed troubleshooting abilities. This study was conducted in two stages and administered via a learning management system due to COVID-19 restrictions. The first stage included a pre-test, a training session using the simulation with worked examples, and an immediate post-test for near and far transfer of troubleshooting abilities. The second stage occurred one week later and included the final posttest for near and far transfer of troubleshooting abilities and creation of episodic memories. Answers to four troubleshooting questions on each of the pre-test and immediate and delayed post-tests were collected to determine any differences in the immediate and retained troubleshooting abilities. Answers to the solution mapping questions were collected to determine the creation of episodic memories. A repeated measure analysis of variance was conducted in SPSS to analyze the results of the troubleshooting pre- and post-tests. A correlational coefficient was used to determine any interaction between episodic memories and delayed troubleshooting abilities. Previous experience levels and participants’ major of study were also examined to determine their effect on the results. The findings show the simulation with worked examples had a statistically significant effect on delayed troubleshooting abilities and the created episodic memories had a positive correlation with the delayed troubleshooting, both with a medium effect size. However, the simulation with worked examples had no statistically significant effect on immediate troubleshooting abilities. Levels of previous experience and participants’ major of study had little effect on the results.

<p>With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that help in optimizing and streamlining the different underlying tasks. One such task is the technical documentation of the performed maintenance operations. Instead of paper-based documentation, voice tools that transcribe spoken logbook entries allow technicians to document their work right away in a hands-free and time efficient manner. However, an accurate automatic speech recognition (ASR) model requires large training corpora, which are lacking in the domain of aviation maintenance. In addition, ASR models which are trained on huge corpora in standard English perform poorly in such a technical domain with non-standard terminology. Hence, this thesis investigates the extent to which fine-tuning an ASR model, pre-trained on standard English corpora, on limited in-domain data improves its recognition performance in the technical domain of aviation maintenance. The thesis presents a case study on one such pre-trained ASR model, wav2vec 2.0. Results show that fine-tuning the model on a limited anonymized dataset of maintenance logbook entries brings about a significant reduction in its error rates when tested on not only an anonymized in-domain dataset, but also a non-anonymized one. This suggests that any available aviation maintenance logbooks, even if anonymized for privacy, can be used to fine-tune general-purpose ASR models and enhance their in-domain performance. Lastly, an analysis on the influence of voice characteristics on model performance stresses the need for balanced datasets representative of the population of aviation maintenance technicians.</p>

U.S. Army helicopter maintenance condition is affected by operation environment and high flight hours. Due to the environmental conditions and high operation tempo of Afghanistan and Iraq, U.S. Army Aviation created the RESET aviation maintenance program to provide restorative maintenance following deployments in theater. The RESET maintenance program was created in addition to the existing two-level maintenance programs. Following deployment, RESET is a thorough cleaning to remove contaminants, inspection of airframe and components, and repair cycle to restore the condition of the helicopter to acceptable condition. Based on the original intent of RESET, it was projected that at the conclusion of military operations in Afghanistan and Iraq, the RESET maintenance program could be discontinued. Because of the presumed safety, reliability, and mission readiness created by RESET, this thesis appraised the RESET maintenance program as a permanent addition to U.S. Army Aviation maintenance programs. The hypothesis was that RESET does improve safety, reliability, and mission readiness of the Army UH-60 Black Hawk fleet. The design was a quantitative survey of three variables: safety, reliability, and mission readiness. The survey featured Likert scale and open-ended questions of three groups: UH-60 maintenance test pilots, UH-60 AVUM/AVIM maintenance supervisory personnel, and ACE (Airframe Condition Evaluation) technical evaluators. Data from each of the three survey groups verified the hypothesis that RESET improved safety, reliability, and mission readiness. Data from open-ended questions indicated that the additional disassembly and special inspections of RESET are more extensive than the aviation unit and intermediate Phased Maintenance Inspection (PMI). Therefore, given the disassembly and special inspections of RESET, and the verification that RESET improves safety, reliability, and mission readiness, it was concluded that RESET is a successful program that should be continued. Based on the effectiveness of RESET in discovering these deficiencies, RESET should be a permanent addition to the Army aviation maintenance programs.

Made available in DSpace on 2016-06-02T19:16:27Z (GMT). No. of bitstreams: 1 3469.pdf: 2787116 bytes, checksum: 3e93f7fd10c28a8af437b5d788656f52 (MD5) Previous issue date: 2011-02-17 / The airline industry worldwide has brought great benefits to society, affecting the economic, social and environmental sustainability, including the most diverse and cultural people around the world. This has been reflected by the increased new aircraft sales each year, and the flight safety is one of the most important and challenging factors to achieve and keep the trust of the users and the perpetuity of this transport. The flight safety is associated with both aircraft manufacturing and maintenance, where the maintenance technician plays a key role. Training and upgrading of the professional regulation and education involve theoretical and practical knowledge, which should be given special attention to human factors and ways to prevent human errors for incidents and accidents in aviation. Despite its importance, this issue has not been investigated like it would be, especially in Brazil. The objective of this research is to analyze the current situation of aircraft maintenance mechanics training with emphasis on flight safety, using an exploratory method. The results point to an increased trend of incidents and accidents in this transport sector, including the factors associated with human failings; and to the relevance of place greater emphasis on flight safety into Brazilian regulations that standardize the graduation of airplane maintenance mechanics. It has been also recommended that the curriculum and other requirements for such training be compatible with the technological innovation speed for new and old airplanes. Increased collaboration between companies and schools can also bring benefits and the regional maintenance center of Sao Carlos, Araraquara and Ribeirao Preto has potential for that. It is also suggested that such revision on the Brazilian national regulations has as reference some consultations with people involved on this market, taking into account relevant international regulations. / O setor de transporte aéreo mundial tem trazido grandes benefícios à sociedade, afetando a sustentabilidade econômica, social e ambiental, inclusive influenciando culturalmente os mais diversos povos ao redor do mundo. Isso reflete no grande aumento de novas aeronaves vendidas a cada ano, e a segurança de voo é um dos fatores mais importantes e desafiadores para se obter e manter a confiança dos usuários e a perpetuidade desse transporte. A segurança de voo está associada tanto à fabricação como à manutenção de aeronaves, onde o profissional de manutenção aeronáutica desempenha papel chave. A formação e atualização desse profissional envolvem regulamentação e ensino de conhecimentos teóricos e práticos que devem dar atenção especial aos fatores humanos e a forma de se evitar erros humanos na ocorrência de incidentes e acidentes aéreos. Apesar da importância, essa temática tem sido pouco pesquisada, sobretudo no Brasil. O objetivo da presente pesquisa é analisar a situação atual da formação de mecânicos de manutenção aeronáutica com ênfase na segurança de voo através do método exploratório. Os resultados obtidos apontam para a tendência de aumento de incidentes e acidentes aéreos, inclusive os associados a fatores e erros humanos; e a pertinência de se incluir maior ênfase na segurança de voo na regulamentação aeronáutica nacional da formação destes mecânicos. Também é recomendável que a grade curricular e os demais requisitos para essa formação acompanhem a dinâmica das inovações tecnológicas das aeronaves novas e antigas. A intensificação da colaboração entre empresas e escolas podem também ser benéfica e o pólo regional de São Carlos, Araraquara e Ribeirão Preto tem potencial para isso. Recomenda-se, ainda, que haja revisão dos regulamentos brasileiros com base em consultas aos envolvidos, levando em conta também os regulamentos internacionais relevantes.

Approved for public release, distribution is unlimited / This thesis addresses the need of Naval Aviation Maintenance to streamline and more effectively manage the process of technical consultation aboard deployed aircraft carriers. The current process involves the physical transportation of an appropriate technician to the carrier to perform required maintenance and/or repairs. In light of the technology currently available this process becomes obviously obsolete, overly costly and needlessly time consuming. By implementing wireless technology in combination with advanced software allowing the virtual collaboration of parties widely separated by geographical distance the Navy can establish a "virtual technical presence" onboard aircraft carriers wherever they may be in the world. This thesis will describe how the fusion of wearable computing, augmented reality, intelligent agents coupled with CoABS, and a modern collaborative software application can revolutionize Naval aviation maintenance as we know it. The technology is there - it only remains for the Navy to leverage it and take advantage of the significant returns that it will provide. The implementation of this technology will allow maintainers onboard deployed aircraft carriers to consult in an augmented virtual environment with technical assets on the shore. These shore-based assets will then be able to "walk" deployed personnel through complicated repair procedures in a matter of minutes or hours as opposed to the previous need to wait for days for the technician to arrive. This is a bold and innovative new concept that will allow commands at sea to increase their levels of combat readiness and allow them the ability to respond to ever changing mission needs. Turn around times for the repair of critical parts and assemblies will be reduced and readiness levels elevated. The ultimate goal of any command is mission accomplishment. This system will aid commands in achieving that all important goal. / Lieutenant, United States Navy

This dissertation develops systems engineering and machine learning models for aviation maintenance support. With the constant increase in demand for air travel, aviation organizations compete to maintain airworthy aircraft to ensure the safety of passengers. Given the importance of aircraft safety, the aviation sector constantly needs technologies to enhance the maintenance experience, ensure system safety, and limit aircraft downtime. Based on the current literature, the aviation maintenance sector still relies on outdated technologies to maintain aircraft maintenance documentation, including paper-based technical orders. Aviation maintenance documentation contains a mixture of structured and unstructured technical text, mainly inputted by operators, making them prone to error, misunderstanding communication, and inconsistency. This dissertation intends to develop decision support models based on systems engineering and artificial intelligence models that can automate the maintenance documentation system, extract useful information from maintenance work orders, and predict the aircraft's top degrader signals based on textual data. The first chapter of this dissertation introduces the significant setbacks of the aviation industry and provides a working ground for the following chapters. The dissertation's second chapter develops a system engineering framework using model-based systems engineering (MBSE) methodology to model the aviation maintenance process using the systems engineering language (SysML). The outcome of this framework is the design of an automated maintenance system model that can be used to automate maintenance documentation, making it less prone to error. The third chapter of the dissertation uses textual data in maintenance work orders to develop a hybrid approach that uses natural language processing (NLP) and transformer models to predict the readiness of a legacy aircraft. The model was tested using a real-life case study of the EA-6B military aircraft. The fourth chapter of this dissertation develops an ensemble transformer model based on three different transformer models. The ensemble model leverages the benefits of three different transformer architectures and is used to classify events based on an aviation log-based dataset. This dissertation's final and fifth chapter summarizes key findings, proposes future work directions, and provides the dissertation's limitations.