Failure Mode Effects And Criticality Analysis Research Articles

Strategy to secure the neuraxial route in anaesthesia: Risk mapping and feedback from the application of the ISO 80369-6 standard NRFit® connectors

In anesthesia, a medication error would occur every 20 to 133anesthesia procedures, and 14% is related to a route administration error. To secure neuraxial route, ISO group published a norm in 2016 to develop specific connectors, the "NRFit® connector". The main objective of this work, is to develop a risk mapping related to neuraxial medication errors therefore prepare the NRFit® implementation in anesthesia units in a French Universitary Hospital. Failure modes, effects and criticality analysis (FMECA) methodology was used for our risk mapping which was divided in 3 anesthesia specialities. For each, the analysis was performed for accidental neuraxial administration of intravenous drugs, and its opposite error. Secondly, NRFit® devices were tested for 1month by 3 experimented anesthetists. The majority of reported errors concerns epidural and intrathecal anesthesia, and more frequently in the field of obstetrics. Opioids and tranexamic acid, administered in neuraxial route, are drugs with the highest criticality. The tests were rather conclusive and made it possible to highlight the additional needs in medical devices. Obstetrics is the riskiest area due to the frequency of epidural anesthesia, the administration of critical drugs in intravenous and neuraxial route. This work increased the awareness of our group, improved the measure of this risk and harmonized practices. This work is the first step of the project to prevent administration route error in anesthesia during patient's drug management. The next step will be the NRFit® implementation for epidural and combined spinal-epidural anesthesia in our hospital.

Evaluation of the risk of occupational exposure to antineoplastic drugs in healthcare sector: part II - the application of the FMECA method to compare manual vs automated preparation.

Healthcare workers handling antineoplastic drugs (ADs) in preparation units run the risk of occupational exposure to contaminated surfaces and associated mutagenic, teratogenic, and oncogenic effects of those drugs. To minimise this risk, automated compounding systems, mainly robots, have been replacing manual preparation of intravenous drugs for the last 20 years now, and their number is on the rise. To evaluate contamination risk and the quality of the working environment for healthcare workers preparing ADs, we applied the Failure Mode Effects and Criticality Analysis (FMECA) method to compare the acceptable risk level (ARL), based on the risk priority number (RPN) calculated from five identified failure modes, with the measured risk level (MRL). The model has shown higher risk of exposure with powdered ADs and containers not protected by external plastic shrink film, but we found no clear difference in contamination risk between manual and automated preparation. This approach could be useful to assess and prevent the risk of occupational exposure for healthcare workers coming from residual cytotoxic contamination both for current handling procedures and the newly designed ones. At the same time, contamination monitoring data can be used to keep track of the quality of working conditions by comparing the observed risk profiles with the proposed ARL. Our study has shown that automated preparation may have an upper hand in terms of safety but still leaves room for improvement, at least in our four hospitals.

Réforme de l’accès dérogatoire : impact sur la gestion dans une PUI et identification des risques

The reform of derogatory access authorisations (DAs) on 1st July 2021 has distorted the routine of the hospital pharmacists dealing with innovative medicines that are waiting for marketing authorization or approval. There are two distinct categories of DAs: Compassionate Access Authorisations (CAAs) are granted by the French National Agency for the Safety of Medicines (ANSM) while Early Access Authorisations (EAPs) are granted at the request of pharmaceutical companies by the French National Authority for Health (HAS). All AAPs and a majority of the AACs are supported by a Protocol for Therapeutic Use and Data Collection (PTU-DC).The aim of this study is to assess the impact of the reform on pharmacy process one year following its implementation, and to identify the risks related to the new circuits.The working group, composed of three pharmacists carried out an initial assessment of the effects first measured the impact of the reform on medicine processes in DAs. They performed a comparison of the changes in their management methods: 3 months prior to the reform (M0), and 3 months (M3) and 12 months (M12) post-reform.Risks analysis was conducted using the FMEA (Failure Modes, Effects and Criticality Analysis) method. The analysis was limited to the process steps specific related to DAs drugs were analyzed. The critical severity of the risk situations identified was rated. A critical hierarchy matrix was used to establish priority actions. The priority actions to be taken were determined using the critical hierarchy matrix.Over the span of one year, the number of DAs in our establishment showed a 31.7% increase, from 41 at M0 to 54 at M12. At M0, the proportion of drugs needed inclusion via a drug- specific digital platform, specific to each drug, stood at 27% (11/41) of drugs at M0 while at M12, it rose to 52% (28/54).The percentage of PTU-DCs therefore increased by a factor of 1.7, rising from 29% (12/41) at M0 to 47% (21/45) at M3 and 60% (32/54) at M12. For orders, which are always nominative, approval depends on both the presence of the PTU-DC tracking sheet being present in 12% of PAAs, and the inclusion number in 26% of PAAs.The risk analysis shows 44 failure modes and 28 risk situations. Among the failure modes, 33 have a consequence of acceptable or tolerable criticality under control, whilst 11 are deemed of unacceptable criticality. A suitable control method exists has been identifies for 3 of them. Finally, the ranking evaluation of criticalities has highlighted 4 situations which require immediate action as a priority: delivery times, obtaining completed tracking sheets and ordering procedures.The aim of the DAs reform is to simplify access to innovative medicines. However, the reform has significant and damaging repercussions on pharmaceutical activities. Corrective measures need to be taken in conjunction with all parties involved in the circuits including laboratories and service providers (CROs), authorities and healthcare professionals.

Fuzzy Inference System Development for Turbogenerator Failure Diagnosis on Floating Production Offloading and Storage Platform

This paper introduces a novel approach for diagnosing failures within a turbogenerator mineral lube oil system, employing a fuzzy inference system (FIS) model. The study leverages real operational data collected from supervisory monitoring sensors across four turbogenerators over a three-year operational span, resulting in a dataset comprising 40,456,663 input parameters. The failure modes were established through expert knowledge, using the Failure Mode, Effect, and Criticality Analysis (FMECA) documentation as the basis. Initially, the model’s universe variables were constructed using the sensor calibration range, and then the fuzzy membership functions were formulated based on the operational thresholds inherent to each measured parameter. The fault identification mechanism is underpinned by an inference system employing predefined rules, extrapolated from expert judgments encapsulating failure typologies specific to the turbogenerators’ mineral lube oil system, as delineated in the FMECA. The FIS model demonstrates notable efficacy in failure diagnosis with an overall performance evaluation of the system yielding satisfactory outcomes, having a 98.35% true positive rate for failure classification, coupled with a 99.99% true negative rate for accurate classification during normal system operation. These results highlight the visibility of the FIS model in diagnosing failures within the turbogenerator mineral lube oil system, thereby showcasing its potential for enhancing operational reliability and maintenance efficiency.

基于模糊综合评判的 FMECA 脱粒清选系统可靠性分析

Aiming at the traditional FMECA (Failure Modes, Effect and Criticality Analysis) results of the threshing and cleaning system, which are strongly influenced by subjective factors, imprecise and easy to repeat, the fuzzy comprehensive evaluation method is introduced to quantify the results of the expert evaluation and reduce the subjective influence. Analytic Hierarchy Process (AHP) is used to assign weights to each influencing factor, and by calculating the comprehensive hazard level index, the hazard ranking of each failure mode is carried out, from which the critical failure modes are identified as the focus of improvement, so as to improve the reliability of the system. Comparison shows that the improved method effectively makes up for the shortcomings of the traditional FMECA analysis method, and it is easier to find out the critical failure modes, which provides a theoretical basis for practical application.

A quantitative safety assessment for offshore equipment evaluation using fuzzy FMECA: A case study of the hydraulic submersible pump system

The Hydraulic submersible pump system (HSPS) is integral to the offloading of oil on offshore platforms and oil tankers. Due to the inflammable and explosive properties of the oil, the working process of HSPS is of high risk. Therefore, this study focused on the safety assessment of HSPS, key potential failure modes of HSPS were identified. A Fuzzy Failure Mode Effects and Criticality Analysis (FFMECA) model was proposed based on fuzzy logic theory and failure mode effects and criticality analysis (FMECA) method. Fuzzy linguistic terms were used to assess the Occurrence (O), Severity (S), and Detection (D) of the identified failure modes. The weights for O, S, and D were calculated based on experts’ ratings and entropy theory. A case study was carried out and the Fuzzy Risk Priority Numbers (FRPNs) for the failure modes were obtained. The results highlighted that 5 failure modes, namely wear of bearings, failure of mechanical seal, failure of rotary seal, zero pressure on the outlet and influence of excessive temperatures, were of critical level and required immediate preventive action. Risk control measures were proposed to ensure the safety of HSPS in practical application and to improve the reliability of system operation.

FMECA and FTA analysis applied to the manufacturing process of pulsating heat pipes

Pulsating heat pipes (PHPs) offer significant advantages for the thermal control of electronic components due to their simple manufacturing and high heat transfer rates. The reliability of PHPs has traditionally been assessed through long-life testing, but detailed reliability analyses from an equipment perspective are limited. The study of PHP reliability is essential due to its application and operational conditions. For instance, in aerospace applications these devices operate under severe conditions, and maintenance or replacement is impossible during operation, making them critical components in system functionality. The reliability analysis of PHPs focuses on the manufacturing process, considering future operating conditions. Although preliminary PHP testing will be conducted on Earth, laboratory conditions are less stringent due to the difficulty of replicating launch acceleration and space conditions for long-term testing under microgravity. This study presents an FMECA (Failure Modes, Effects, and Criticality Analysis) of the pulsating heat pipe manufacturing process, breaking down the production of each component. The results indicate that the most critical point is concentrated in the assembly of these components, leading to a higher incidence of welding failures. It recommends further work to improve welding and analyze mechanical stresses within the heat pipe.

Optimizing chemotherapy medication leftover management circuit in a centralized chemotherapy preparation unit: A comprehensive FMECA risk analysis and continuous improvement approach.

Chemotherapy medications are usually having high costs, and new targeted drugs can be especially expensive, representing a challenge on healthcare, particularly in low- and middle-income countries. As cytotoxic leftover management is crucial for reducing medication wastage, the aim of this study is to evaluate and optimize leftover management circuit in NIO'S Pharmacy Centralized Chemotherapy Preparation Unit (CCPU) through a Failure Mode, Effects and Criticality Analysis (FMECA), and propose continuous improvement element to enhance the security of the process. The FMECA were conducted in NIO's CCPU from March to May 2023, then continuous improvement plan was established to enhance the security of the process. The failure modes, their causes, impact, and criticality were assessed through criticality index calculation (CI = severity × frequency × detectability), and the risk concerned safety and effectiveness disruptions in chemotherapy preparation circuit using cytotoxic leftover. Leftover management circuits were described in flowchart form, where 18 failure modes were detected in four different steps of the process from chemotherapy preparation to disposal. Failure with highest critical index were detected in the case of equipment malfunction, improper storage temperature, and humidity. Continuous improvement recommendations were proposed in a table form. FMECA analysis applied to NIO's chemotherapy leftover management process allowed us to evaluate, secure, and optimize the circuit, and to propose several actions to implement in a perspective of continuous improvement.

A rule-based Bayesian network modelling under evidential reasoning theory for risk analysis of anchoring operation in maritime transportation

Anchoring is one of the most repeated routine operations concerning many maritime transportation vessel types. The operation poses significant risks due to the nature of the work and could cause damage to the vessel, commodity, or environment. This paper introduces a conceptual framework to analyse the risk of anchoring operations by adopting a rule-based Bayesian Network (BN) under evidential reasoning (ER) modelling. Failure Mode Effects and Criticality Analysis (FMECA) is used to gain detailed insight into the operational hazards of anchoring, while rule-based BN extended ER is capable of dealing with the weaknesses of FMECA by evaluating the importance of risks. In this context, Failure Mode 5.2 (Ship rudder/thruster/steering system failure) with an RPN of 46.42 was determined as the most critical danger for anchoring operations on ships. The research outcomes will provide valuable insight to the maritime industry, in particular ship owners, ship crew, safety managers, and superintendents, to retain a high level of safety at the operational level and minimize anchoring-related accidents onboard ships.

Cost effective maintenance strategy for centrifugal pumps using reliability centred maintenance

The aim of this work is to obtain a maintenance strategy that is cost effective for centrifugal pumps using reliability centred maintenance (RCM). The components of the centrifugal pump used for the study are the shaft, impeller, bearing, mechanical seal, coupling, shaft sleeve, wear-ring casing, suction flange and discharge flange. The motor that drives the pump was also considered. Two basic tools of the RCM strategy were applied. These are the failure modes, effects and criticality analysis (FMECA) and logic tree analysis (LTA). Failure data for a period of 10 years about a centrifugal pump was collected and the FMECA was applied to determine the failure modes, the effects of the failure, the criticality of the components, the mean time between failure (MTBF), the failure rate and the mean time to repair (MTTR). The risk priority numbers of all the components were estimated. The LTA was applied to come up with a new maintenance strategy for each of the components of the pump. The maintenance cost consisting of spare part cost and labour cost for the pump components were estimated for the current maintenance practice as well as the new or proposed maintenance practice. The most critical components observed were the motor, shaft, impeller and the mechanical seal. The motor has the highest MTTR value (58 hrs) while the mechanical seal has the highest failure rate (8.06E-04 per hr). The proposed maintenance strategy leads to reduction in spare part cost in a number of components, with the largest reduction of 19.88% occurring in mechanical seal. The proposed strategy also leads to reduction in labour cost in motor, shaft, impeller and the mechanical seal with the values 33%, 25%, 50% and 25% respectively. The methodology could be applied to other devices.

Quantifying potential cyber-attack risks in maritime transportation under Dempster–Shafer theory FMECA and rule-based Bayesian network modelling

Maritime cyber security is a growing concern in the shipping industry as reliance on technology increases. With the potential for cyber attacks to disrupt vessel operations, compromise sensitive information, and endanger crew and cargo, assessing the risks and developing effective risk management strategies is crucial. On the other hand, cyber risk assessments in maritime transportation have been limited, and there is a lack of probabilistic databases of cyber threats. To remedy this gap, this paper presents a probabilistic approach to estimate cyber threats, especially for the bridge navigational systems in the maritime sector, focusing on the Bayesian network model to evaluate cyber risks for integrated bridge navigational systems onboard, and marine security experts evaluate 32 threats with respect to FMECA (Failure modes, Effect and Criticality Analysis) parameters. Dempster-Shafer theory is utilised to consolidate expert opinions for cyber risk analysis. The findings of the research showed that AIS spoofing poses the highest risk. GPS jamming is the other significant threat to ship bridge navigational systems during cyber attacks. The research provides a basis for identifying cyber threats and risks, calculating the highest risk values and developing control actions to maintain effective risk management strategies for safe and secure maritime transportation.

Biochemical test as an efficient system to improve safety in parenteral nutrition for premature infants

ObjectiveThe biochemical test validation process of parenteral nutrition bags is described to verify the correct composition of critical compounds before its administration, as well as its impact on safety after two years since its implantation in a population of premature infants. MethodFor the validation of the technique, 35 samples of parenteral nutrition without lipids were processed by the emergency laboratory, following the routine procedures used to measure the concentrations of glucose and electrolytes in plasma and urine. To analyze its impact on safety, pre-implantation and post-implantation risk analysis was carried out using failure mode, effects and criticality analysis (FMECA). Likewise, all out-of-range results and their potential repercussions on patient safety were evaluated. ResultsRegression analysis showed no systematic measurement error for glucose, calcium and potassium; however, there is a constant systematic error for sodium and magnesium, thus both were discarded for routine analysis. Failure mode, effects and criticality analysis results showed a decrease in the risk of the process of 11% for the biochemical test. We tested 1,734 parenteral nutritions from 218 premature neonates; 58 (3.3%) results were out of the acceptance range, and 7 were considered to be potentially dangerous compounding errors. ConclusionsThe biochemical test of glucose and electrolytes is an efficient and reproducible method that prevents possible compounding errors from reaching the patient.

SAPERO: a new tool for safety analyses in advanced radiotherapy

Improving safety standards in advanced radiotherapy technologies, where historical experience is not sufficient due to innovation aspects, raises the need to perform studies using new tools that follow a holistic view of the process chain. Such studies are useful to identify additional critical elements compared to safety analyses carried out by classic tools. In this field, SAPERO (La SicurezzA del PazientE: tecniche avanzate ed innovative per la valutazione del rischio di eventi indesiderati all'interno del percorso assistenziale nel settore RadioterapicO) is a new assessment tool that allows to use integrated of Hierarchical Task Analysis (HTA); Failure Mode Effects and Criticality Analysis (FMECA); Cognitive Task Analysis (CTA); Human Error Assessment Reduction Technique (HEART). The methodological approaches have been suitably modified to address their operating in the medical sector under study. Some improvements have concerned the application of the fuzzy theory in FMECA and the use of a linguistic approach in HEART. In this paper, SAPERO application on a case study related to treatment procedures in helical tomotherapy performed at the radiotherapy department of ARNAS Civico hospital, Italy, is described. The results have allowed to provide suggestions aimed to improve the examined process.

A quality by design framework for developing nanocrystal bioenabling formulations

The present study aims to outline a rational framework for the design and development of a 1.0% (w/v) hydrocortisone nanocrystal-based formulation, resorting to a simple, efficient, and scalable nanonization methodology, based on the high-pressure homogenization (HPH) technique. Accordingly, the innovative product was comprehensively optimized following a Quality by Design (QbD) approach. The thorough selection of formulation composition was driven by a dual purpose: improving skin permeation and stability. In the early stage of development, a Failure Mode, Effects and Criticality Analysis (FMECA) diagram was employed to identify the most impactful variables for the critical quality attributes (CQAs). In this sense, a rotatable, three-factor and five-level circumscribed central composite design (CCCD) was applied to investigate how squalene concentration (x1), soluplus concentration (x2) and HPH-time (x3) influence physicochemical properties, performance and physical stability of the formulation. A robust Design Space (DS) was defined, establishing the optimal settings for the critical variables, whose combination meets the requirements set in the quality target product profile (QTPP). Morphological analysis revealed the cuboidal shape of hydrocortisone nanocrystals. In what concerns colloidal properties, the most promising formulation disclosed a small particle size (Dx(50) = 311.8 ± 1.5 nm), along with narrow size distribution (span value = 1.91 ± 0.17). Zeta potential results (−2.19 ± 0.15 mV–−12.1 ± 0.4 mV) suggested a steric hindrance stabilization. FTIR spectra showed no chemical interactions between drug and formulation components. XRD diffractograms confirmed loss of crystallinity during the downsizing process. In vitro studies revealed an improvement on drug release rate (316 ± 21–516 ± 35 μg/cm2/√t), compared to the coarse suspension and commercial products, and a straight dependence on the stabilizer concentration and HPH time. The permeation flux across the skin (0.16 ± 0.02–1.2 ± 0.5 μg/cm2/h) appeared to be dependent on the drug physicochemical properties, in particular saturation solubility. Further characterization of the experimental formulations pointed out the role of the stabilizing component to prevent against physical instability phenomena. This organic solvent-free, and therefore “green” nanocrystal production technology offers great potential for pharmaceutical R&D and drug delivery by enabling the development of new forms of conventional drugs with optimal physicochemical properties and performance.

Comparative Study of K-Means Clustering and a Novel Ranking Algorithm for Risk Priority Number Analysis in FMECA

Failure mode, effects, and criticality analysis (FMECA) has become a fundamental tool for identifying critical failure modes and prioritizing maintenance activities. As part of the analysis, the risk priority number (RPN), a numeric assessment of the risk, has received much attention as it is computed using severity (S), occurrence (O), and detectability (D), which serve as the main criteria for criticality analysis in many practical FMECA cases. In this paper, we assemble and present a data set containing RPN evaluations from 20 real-world cases. We then apply K-Means clustering to identify the most critical failure modes and propose a novel ranking algorithm that prioritizes mitigation actions based on specific criteria for each failure mode. Our experimental results suggest that both clustering and ranking methods can provide effective prioritization for critical failure modes under given assumptions, while our novel ranking algorithm can adapt to general scenarios and provide more accurate prioritization that can help develop effective maintenance strategies to minimize equipment failure risk and optimize maintenance costs.

Device Health Status Assessment Under the Influence of Multiple Exception Modes

Equipment reliability is the key feature to ensure the equipment operation for a long time. It is difficult to determine the overall reliability of industrial equipment due to the different reliability states of different subsystems. A device abnormality identification method based on JS (Jenson's Shannon) divergence and a health status assessment technology based on FMECA (failure mode, effect and criticality analysis) are proposed. This method enables an accurate assessment of the current health status of the device. First, the historical operation data is preprocessed according to the characteristics of the equipment to improve the data quality. The JS divergence method is reused to extract the similarity between the key feature data distribution and the benchmark data distribution. Then, the FMECA report is established using the real running data of the device combined with expert experience. Gray theory was used to determine the degree of association between one-way health state membership vector and different health state rank vector. Finally, the health status level was comprehensively evaluated by the fuzzy membership method. Taking the mechanical arm component of a 100-ton crane as an example, the results show that this method can effectively evaluate the current health state of the equipment, and provide power for the abnormal advance disposal and auxiliary management decisions.

Risk Assessment Analysis of Multiple Failure Modes Using the Fuzzy Rough FMECA Method: A Case of FACDG

With the increasing operating mileage and ownership of high-speed electric multiple units (EMU), a reasonable operation and maintenance strategy is the key to ensure their safe and reliable operation. As a key component of recombined EMU, creating a reasonable and effective risk assessment method for the fully automatic coupler draft gear (FACDG) is the first task. Therefore, based on fuzzy rough number theory, combined with the analytic hierarchy process (AHP), entropy weight method (EWM), technique for order performance by similarity to ideal solution (TOPSIS) and grey relational analysis (GRA), a risk priority indicator of comprehensive nearness degree is developed. Furthermore, a novel multi-criteria decision making (MCDM) failure modes, effects and criticality analysis (FMECA) assessment method is proposed. The effectiveness and rationality of the risk assessment method proposed are verified by the analysis of data and failure modes of a certain FACDG at fourth-level engineering maintenance.

Application of Overall Equipment Effectiveness and Failure Mode Efffect and Criticality Analysis Methods to Improve Machine Performance Effectiveness

PT XYZ is a company that produces hot rolled coils (HRC) steel products. One of the machines used in the process is a rough mill machine in the milling process. The problem is downtime on the rough mill machine that disrupts the production process time. The purpose of this study is to determine the value of the effectiveness of the machine, find the largest losses that affect the value of the effectiveness of the machine, identify the cause of the biggest losses and provide recommendations for improvement steps. The methods used are overall equipment effectiveness (OEE), six big losses, and the failure mode effect and criticality analysis (FMECA). The results show that the average OEE value of PT XYZ is 80%, but this value was still not following the ideal standard. By identifying the six big losses, the most significant losses are reduced speed losses, with a total percentage value of 86% and an average time loss of 5,020 minutes. FMECA results obtain three components that cause the biggest losses: the engine motor, gearbox, and spindle. Recommendations for improvement include making and setting schedules, implementing predictive maintenance and preventive maintenance on rough mill machines, and regularly checking and replacing component spare parts.

Reliability Study of an Intelligent Profiling Progressive Automatic Glue Cutter Based on the Improved FMECA Method

This study introduces the fuzzy theory approach as an enhancement to the traditional failure mode, effect, and criticality analysis (FMECA) method in order to address its limitations, which primarily stem from subjectivity and a lack of quantitative analysis. The proposed method, referred to as FMECA improvement based on fuzzy comprehensive evaluation, aims to quantify the qualitative aspect of the analysis and provides a detailed outline of the analysis procedure. By applying the enhanced FMECA method to assess the reliability of an intelligent profiling progressive automatic rubber cutter, the hazard ranking for each failure mode of the cutter can be determined, thereby identifying areas that require reliability improvement. The analysis outcomes demonstrate that this method establishes a theoretical foundation for subsequent cutter improvement designs, enables early identification of potential failures, and consequently leads to a reduced failure rate and an enhanced reliability level for the intelligent profiling progressive automatic cutter. Furthermore, this innovative agricultural equipment reliability analysis and testing approach holds significant value in elevating the reliability standards of agricultural equipment as a whole and can be explored and implemented in other agricultural machinery contexts.

Security-Informed Safety Analysis of Autonomous Transport Systems Considering AI-Powered Cyberattacks and Protection.

The entropy-oriented approach called security- or cybersecurity-informed safety (SIS or CSIS, respectively) is discussed and developed in order to analyse and evaluate the safety and dependability of autonomous transport systems (ATSs) such as unmanned aerial vehicles (UAVs), unmanned maritime vehicles (UMVs), and satellites. This approach allows for extending and integrating the known techniques FMECA (Failure Modes, Effects, and Criticality Analysis) and IMECA (Intrusion MECA), as well as developing the new SISMECA (SIS-based Intrusion Modes, Effects, and Criticality Analysis) technique. The ontology model and templates for SISMECA implementation are suggested. The methodology of safety assessment is based on (i) the application and enhancement of SISMECA considering the particularities of various ATSs and roles of actors (regulators, developers, operators, customers); (ii) the development of a set of scenarios describing the operation of ATS in conditions of cyberattacks and physical influences; (iii) AI contribution to system protection for the analysed domains; (iv) scenario-based development and analysis of user stories related to different cyber-attacks, as well as ways to protect ATSs from them via AI means/platforms; (v) profiling of AI platform requirements by use of characteristics based on AI quality model, risk-based assessment of cyberattack criticality, and efficiency of countermeasures which actors can implement. Examples of the application of SISMECA assessment are presented and discussed.