Part of the book: Advances in Air Navigation Services
Aeronautic industry is one of the enablers of the economic development and social insertion at European level, and it is one of the drivers of expansion of remote regions as far as it allows habitants, workers, and companies at these regions to expand their activities and areas of influence. The European aeronautics industry, including the commercial air transport, generates more than 220 billion of Euros and more than 4.5 million of jobs. These figures are expected to be double by 2030. Future developments in the sector, together with greater intra-European mobility of workers and population aging, bring a greater need for new skills in the work force together with an urgency for a larger number of professionals. Therefore, to achieve the desirable sustained growth the EU needs to invest in high-quality VET (vocational education and training) in order to be able to supply the AI (aeronautic industry) with qualified workers. VET stands for education and training which aims to equip people with knowledge, know-how, skills and/or competences required in particular occupations or more broadly on the labor market. This work discusses the outcomes of the AIRVET project, an European partnership whose principal objective is the development and promotion of “curricula and VET courses” in the Maintenance and Information and Communications Technologies (ICT) domains, required for a highly skilled aeronautical workforce.
Part of the book: Skills Development for Sustainable Manufacturing
The world is talking about the Industry 4.0 or the fourth industrial revolution, that is, the current trend of higher level of automation, digitalization and data exchange in manufacturing technologies. It includes cyber-physical systems, Internet of Things and cloud computing among other technological assets. With more than 5000 sensors, which generate up to 10 GB of data per second, modern aircraft engines are an exponent of what digitalization and the Internet of Aircraft Things could furnish, as part of the upcoming Industry 4.0 revolution, in the aviation industry. This new era has the potential to improve air transport key performance areas. Particularly, in an industry where safety levels are so high and the margins for improvement are extremely tight, this upcoming era might imply a shift in safety improvement. In an attempt to define Aviation 4.0, this chapter discusses the stages of aviation development from basic VFR flight rules at Aviation 1.0 up to Aviation 4.0 where cyber-physical systems are designed to assist humans’ unkind or hazardous work, to take decisions and to complete tasks autonomously. It illustrates the current and future cases of application of Aviation 4.0 to increase the aviation safety, while outlines how they might increase aviation safety levels.
Part of the book: Aircraft Technology
Most decisions in aviation regarding systems and operation are currently taken under uncertainty, relaying in limited measurable information, and with little assistance of formal methods and tools to help decision makers to cope with all those uncertainties. This chapter illustrates how Bayesian analysis can constitute a systematic approach for dealing with uncertainties in aviation and air transport. The chapter addresses the three main ways in which Bayesian networks are currently employed for scientific or regulatory decision-making purposes in the aviation industry, depending on the extent to which decision makers rely totally or partially on formal methods. These three alternatives are illustrated with three aviation case studies that reflect research work carried out by the authors.
Part of the book: Bayesian Networks
System safety assessment (SSA) has become a standard practice in air traffic management (ATM). System safety assessment aims, through a systematic and formal process, to detect, quantify, and diminish the derived risks and to guarantee that critical safety systems achieve the level of safety approved by the regulatory authorities. Verification of compliance with the established safety levels becomes the last but an essential part of the safety assurance process. This chapter provides a Bayesian inference methodology to assess and evaluate the compliance with the established safety levels under the presence of uncertainty in the assessment of systems performances.
Part of the book: Risk Assessment in Air Traffic Management