At the heart of airline flight safety management is a systematic approach to identifying hazards and controlling risk factors, which ICAO requires to collect, analyze all deviations in the activities of units, services and personnel airlines and use of its results to develop and implement management activities. That kind of the system enables the organization to predict and fix problems before they lead to an aviation accident. Thus, the organizational management structure should ensure high efficiency, reliability and completeness of the control over all components that ensure the process of the air transportation: the course of transportation, the clear operation of all units in the uninterrupted transport process and their correct matching. In modern conditions, this result is achieved based on a process approach, when the company’s activities are presented as a set of production processes (activities). For each of these areas, the airline has appropriate management systems that are developed, certified, implemented and operated in accordance with international standards. As a result of the interaction of these processes, the goals of the aviation enterprise, which determine its competitiveness, are achieved. Keyword : flight safety, aircraft, risk, algorithm, accident failure, faulty condition, flight delay, management

One of the key concepts in matters of flight safety is that of special (abnormal) situations, with airworthiness regulation and certification of aviation equipment being based on this concept. At the same time, one is forced to admit that today there is no explicit interpretation of the standardized traits of special situations, nor are they not fully elucidated in the scientific literature. In this article we propose a pyramid-based approach to interpreting special (abnormal) in-flight situations, which allows for risk assessment not using risk matrices, but instead relying only on the probabilistic characteristics of the occurrence of events. Using the presence of a causal relationship between the layers of the pyramid, we propose an algorithm for the transition of varying degrees of danger of special situations. This algorithm can be used to develop an on-board device that informs the pilot about the dynamics of transitions from one situation to another, representing each emergency situation in a certain color.

This article reviews the methods of safety management using Heinrich’s and Bird’s pyramids. The presence of a causal relationship between pyramid levels, as a result of inconsistencies in the activities of an organization and personnel, lead to incidents, and incidents in turn lead to accidents. The existence of such a relationship makes it possible to predict the risk of “top-level” events by reducing risks at the middle and lower levels. A mathematical description of the development process of an undesired aviation event is presented, which makes it possible to evaluate the probability of the successful (or unsuccessful) completion of a transportation task. Also given is an analysis of the development of an aviation accident, based on the example of the crash of a Lufthansa A-320 aircraft on 14 September 1993 at the airport of Warsaw (Poland) while landing in adverse weather conditions.

In the 21st century, the systems approach to flight safety began to dominate. ICAO declares 2020 and 2021 the years of safety culture and calls for continued work that would improve safety culture. It is becoming obvious that both the human factor and poor safety culture are risk factors in aviation that directly affect flight safety. Furthermore, a positive safety culture is characterized by mutual trust, which is based on communication, common understanding of the importance of safety and employees’ faith in the effectiveness of preventive measures. Therefore, it is important that every aviation company manager is aware of this and is able to identify and improve the level of safety culture.

21. gadsimtā sāka dominēt sistēmas pieeja lidojumu drošības jomā. ICAO 2020. un 2021. gadu pasludinājusi par drošības kultūras gadu, aicinot turpināt darbu, lai izstrādātu rīkus, kas uzlabo drošības kultūru, nosakot to par prioritāti. Kļūst acīmredzams, ka gan cilvēka faktors, gan zema līmeņa drošuma kultūra ir riska faktors aviācijā, un tas tieši ietekmē lidojumu drošumu. Savukārt pozitīvu drošuma kultūru raksturo savstarpēja uzticība, kas balstīta komunikācijā, kopējā izpratnē par drošības nozīmi un darbinieku ticībā preventīvu pasākumu efektivitātei. Tāpēc ir svarīgi, lai katrs aviācijas uzņēmuma vadītājs apzinātos to un būtu spējīgs noteikt un uzlabot kultūras līmeni.

This proof-of-concept work demonstrates a Bayesian Network (BN) augmentation of the Joint Authorities for Rulemaking on Unmanned Systems (JARUS) Specific Operations Risk Assessment (SORA) 2.5. The proposed architecture maintains the deterministic decision structure of SORA while introducing BN only where operational uncertainty exists. Mission characteristics and observable operational conditions are used as evidence, whereas uncertain factors, such as the risk of ground and air disturbances, are represented probabilistically. Consequently, the Bayesian Network enhances the assessment by quantifying uncertainty while maintaining the official SORA outputs, including the Ground Risk Class (GRC), residual Air Risk Class (ARC), and Specific Assurance and Integrity Level (SAIL). An airframe inspection mission at Riga Airport is used to demonstrate the applicability of the proposed framework and to compare its outputs with those of the SORA 2.5. The results indicate that BN provides an enhanced representation of operational uncertainty and causal relationships while preserving the deterministic structure of SORA. The framework is intended as a probabilistic decision-support tool rather than a replacement for regulatory assessment; therefore, this article does not estimate the probability of regulatory approval or claim predictive superiority over SORA. The contribution is a transparent model specification and a proof-of-concept foundation for future validation using empirical operational data and multiple mission scenarios.