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Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automobile Technology & Material is the property of Automobile Technology & Material Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents a framework merging failure mode and effect analysis (FMEA) and fault tree analysis (FTA) techniques to evaluate loss of coolant accident (LOCA) in the Brazilian Reactor TRIGA IPR-RI. At first, FMEA identified failure modes and prioritized risk management based on the risk priority number (RPN). Subsequently, FTA established logical relationships between these failure modes, revealing minimal cut sets. Results indicated that the path involving “loss of coolant from reactor tank” correlate to an externally caused leak, exhibiting a low probability and, consequently, a low RPN. On the other hand, the path involving “loss of coolant through primary circuit rupture without a pump shutdown” highlighted high RPN due to the lack of shutdown signals from the monitoring indicators. Finally, FTA unveiled that LOCA associates with a primary circuit rupture and the simultaneous failure of safety mechanisms, including ultimately human error.

Pouring is an important process in the production of solid propellant rocket engines, and usually, the cost of a solid propellant rocket engine is extremely high. Therefore, pouring production with high reliability is very important. The pouring of three engines of solid propellant rocket engines simultaneously can greatly improve its production efficiency. However, it makes the system more complex and redundant. For a multi-state system, it is difficult to make an accurate evaluation of system reliability. Aiming at the redundancy of multiple engines and acousto-optic combined control in the three-engine simultaneously slurry pouring alarm control system with dissimilar redundant alarm units, a reliability analysis method is proposed based on the combination of Failure Mode Effect Analysis (FMEA) and Fault Tree Analysis (FTA). The control system is divided into several redundant states according to the alarm function, and then the Bayesian Networks method is used for reliability evaluation and calculation. Finally, the reliabilities of systems with dissimilar redundancy degrees are obtained. The tangible results of this research work are as follows: (1) The research results obtained by applying the FMEA method laid a foundation for the establishment of a fault trees model for analyzing the reliability of the control system using the FTA method, in addition, which can guide the maintenance and fault identification of the control system during engineering application. (2) The calculated value of the reliability of the control system is 0.999989, and the mean time between failures is MTBF is 5 × 104 by using the fault tree analysis method, which proves that the designed three-engine simultaneous pouring system is very reliable. (3) Based on the calculation and comparison of the Bayesian Networks of redundant three-engine pouring control systems, the circuit diagram of the improved control system is identified. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to analyze the maintenance of the main propulsion fuel oil system for tugboats using both qualitative and quantitative methods. The focus is on evaluating the reliability of the system and identifying potential areas for improvement. The research employs a combination of expert interviews, industry standards, and statistical analysis to provide a comprehensive overview of the maintenance practices in place. The goal is to enhance the overall performance and longevity of the main propulsion fuel oil system in tugboats. The study uses data on the operational time, failure time and frequency, the number of vessels served, and fuel system diagrams to analyze the system's reliability. Qualitative methods such as Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) were used, as well as quantitative methods such as Overall Equipment Effectiveness (OEE), Markovian Decision Process (MDP), and reliability methods. The study found that the FO Purifier component was the critical component with a Risk Priority Number (RPN) of 294. The average value of OEE was 47%, lower than the standard of 85%. The MDP analysis showed a probability of 0.08 for mild damage and 0.46 for moderate to severe damage under steady-state conditions. The FO Purifier component had the lowest Mean Time to Failure (MTTF) value of 1658.50 hours. The study provides a graph of the reliability function against time, and recommends maintenance actions based on the MTTF and MDP.

Periodic testing of goods transport vehicle is very important in preventing traffic accidents, particularly in Indonesia. One of the leading factors contributing to these accidents is the malfunction of braking system. Despite the implementation of periodic testing, the incidence of accidents remains alarmingly high. Addressing this issue requires a proactive method to enhance and refine the Standard Operating Procedure (SOP) governing periodic vehicle testing. Therefore, this study aimed to introduce a methodology to revise and augment SOP regarding periodic testing of brake system. The method employed included a comprehensive risk assessment using the Fault Tree Analysis (FTA) and Failure Mode and Effect Analysis (FMEA) tools. These methods were grounded in accident investigation data compiled by the National Transportation Safety Committee (NTSC) spanning the years 2017 to 2022. FTA was employed to identify potential risk, while FMEA facilitated analysis of failure causes within brake system to pinpoint the most critical risk scenarios. Based on analysis, thirteen failure cases were identified and classified as Intolerable risk instances. For each of these cases, tailored SOP additions were recommended in order to offer valuable insights to stakeholders, enabling them to revise and refine the regulations governing periodic vehicle testing. [ABSTRACT FROM AUTHOR]

Air transport is considered to be the safest means of transport. However, if an accident occurs, it often ends in catastrophe. Thus, significant efforts have been paid to sustain successful operations in aviation. Several studies have been carried out to understand the underlying reasons for accidents. This study used Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA) and Causal Analysis based on Systems Theory (CAST) methods to analyse Tenerife aircraft accident and to compare the findings of different methods. The findings showed that while all three methods provided some overlapping findings, the CAST method led to the identification of all causes that were identified by other methods. Considering the nature of the causal factors, FMEA provided more causal factors that are related to organisation and technology than FTA. This study indicates that CAST has a significant value to identify all causes that can be identified by the use of traditional methods. [ABSTRACT FROM AUTHOR]

Failure of the braking system is one of the factors causing traffic accidents, therefore periodic testing of goods transport vehicles is very important. In fact, the incidence rate is still very high despite routine testing. Standard Operating Procedures (SOP) for periodic testing must be updated to reduce the risk of possible accidents. Therefore, procedures for updating the SOP for periodic brake system testing are presented in this article. The Fault Tree Analysis (FTA) and Failure Mode and Effect Analysis (FMEA) methods were applied based on accident investigation data from the National Transportation Safety Committee (NTSC) from 2017 to 2022. FTA is used for risk identification, while FMEA is used for risk analysis to find the highest-risk failure cases. The results of our analysis showed that 13 failure cases were classified as intolerable so additional SOPs were required for each case. Finally, the results of this study provide new insights for stakeholders to revise the rules regarding periodic vehicle testing.

Pouring is an important process in the production of solid propellant rocket engines, and usually, the cost of a solid propellant rocket engine is extremely high. Therefore, pouring production with high reliability is very important. The pouring of three engines of solid propellant rocket engines simultaneously can greatly improve its production efficiency. However, it makes the system more complex and redundant. For a multi-state system, it is difficult to make an accurate evaluation of system reliability. Aiming at the redundancy of multiple engines and acousto-optic combined control in the three-engine simultaneously slurry pouring alarm control system with dissimilar redundant alarm units, a reliability analysis method is proposed based on the combination of Failure Mode Effect Analysis (FMEA) and Fault Tree Analysis (FTA). The control system is divided into several redundant states according to the alarm function, and then the Bayesian Networks method is used for reliability evaluation and calculation. Finally, the reliabilities of systems with dissimilar redundancy degrees are obtained. The tangible results of this research work are as follows: (1) The research results obtained by applying the FMEA method laid a foundation for the establishment of a fault trees model for analyzing the reliability of the control system using the FTA method, in addition, which can guide the maintenance and fault identification of the control system during engineering application. (2) The calculated value of the reliability of the control system is 0.999989, and the mean time between failures is MTBF is 5 × 104 by using the fault tree analysis method, which proves that the designed three-engine simultaneous pouring system is very reliable. (3) Based on the calculation and comparison of the Bayesian Networks of redundant three-engine pouring control systems, the circuit diagram of the improved control system is identified.

Background and Objective: Adventitious presence (AP) or unintentional commingling of genetically modified (GM) grain in non‐GM grain lots is a concern for stakeholders who wish to produce non‐GM grain and grain‐based products. AP that exceeds tolerance levels results in the loss of product marketability as "non‐GM" and subsequent loss of a premium market price. The objective of this study was to evaluate the US commodity corn supply chain using Fault Tree Analysis (FTA) and Failure Mode and Effect Analysis (FMEA) to assess factors contributing to AP in supply chains that handle both GM and non‐GM products. Findings: Systematic analysis of the farm‐to‐feed supply chain identified key processes and actors involved. FTA identified 27 factors potentially contributing to AP along with their root causes. Ranking of factors using FMEA prioritized 14 factors as "critical" with a comparatively higher likelihood of occurrence and impact on AP levels. Conclusions: AP contributing factors were found across the supply chain, indicating that successful segregation relies on all supply chain participants. Identification and prioritization of critical factors make it possible to target resources to a small number of significant factors to attain low AP levels rather than distributing resources across the entire set of factors. Significance and Novelty: This study is an initial attempt to provide insights into the assessment and management of AP in the grain and feed supply chain with a novel application of FTA and FMEA techniques. [ABSTRACT FROM AUTHOR]

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Implementing an active system to identify, monitor and manage risk from laboratory errors can enhance patient safety and quality of care. Aims and Objectives: Failure Mode and Effect Analysis (FMEA) technique allows evaluating and measuring the hazards of a process malfunction, to decide where to execute improvement actions, and to measure the outcome of those actions. The aim of this study was to assess pre analytical phase of laboratory testing, mitigate risk and thereby increase patient safety. Materials and Methods: Steps followed in the study were: planning the study, selecting team members, analysis of the processes, risk analysis, and developing a risk reduction protocol by incorporating corrective actions. A Fault Tree Analysis diagram was used to plot the cascade of faults leading to the pre analytical errors. Risk Priority Number (RPN) was assigned. A minimum cut- off 40 RPN was considered for interventions and highest RPN errors were prioritized with corrective actions. Post intervention RPN score was calculated. Results: Eight failure modes had the highest RPN. Corrective actions were prioritized against these errors. RPN scores of test ordering error, sample collection error, transport errors, error in patient identification, site selection, urine samples not received, sample accessioning and sample processing errors decreased, post intervention. Conclusion: With thorough planning, we can use FMEA as a common standard to analyze risk in pre analytical phase of laboratory testing.

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for "intensity modulated radiation therapy (IMRT)" as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

Carbon fiber-reinforced plastics (CFRP)-packaged fiber Bragg grating (FBG) sensors are widely used in full-scale structural testing of wind turbine blades (WTBs). However, the specific process to make CFRP-packaged FBG sensors, such as packaging, bonding, welding, etc., are mainly manually operated, and no unified standard or rule has been formed yet. Non-standard specific processes, coupled with complex stress distribution, unstable working environments, etc., result in the CFRP-packaged FBG sensors having various failures with time, resulting in inaccurate measurements. Thus, the need to carry out related failure analysis is urgent. This paper therefore performed a reliability analysis for CFRP-packaged FBG sensors using failure mode and effects analysis (FMEA) and fault tree analysis (FTA) techniques. The results provide an important basis towards analyzing performance degradation and functional failures for CFRP-packaged FBG sensors. [ABSTRACT FROM AUTHOR]

In line with the increasingly fierce industry competition, all companies strive to make continuous improvements to increase added value and reduce waste which will impact the company's ability to maintain its existence in the future. One of the problems found in the tire manufacturing industry is the quality problem of the occurrence of defects in the mixing process which is dominated by the viscosity out standard on the compound steel breaker. In this study, analysis and improvement of the defect problem were carried out using Fault Tree Analysis (FTA), Failure Mode and Effect Analysis (FMEA), and Multiple Linear Regression (MLR) to test the correlation between the root causes found to the main problem. Based on the results of the analysis found thirteen root causes where the factor of variation in material viscosity and the suitability of determining the design process has the largest Risk Priority Number (RPN) value and has a strong correlation to defects that occur based on hypothesis testing. Furthermore, improvements are made using the DMAIC method on all factors that affect the occurrence of defects. As the result, the improvement can be effective in reducing the defect to 34.5% and achieve the expected target. [ABSTRACT FROM AUTHOR]

Background: Implementing an active system to identify, monitor and manage risk from laboratory errors can enhance patient safety and quality of care. Aims and Objectives: Failure Mode and Effect Analysis (FMEA) technique allows evaluating and measuring the hazards of a process malfunction, to decide where to execute improvement actions, and to measure the outcome of those actions. The aim of this study was to assess pre analytical phase of laboratory testing, mitigate risk and thereby increase patient safety. Materials and Methods: Steps followed in the study were: planning the study, selecting team members, analysis of the processes, risk analysis, and developing a risk reduction protocol by incorporating corrective actions. A Fault Tree Analysis diagram was used to plot the cascade of faults leading to the pre analytical errors. Risk Priority Number (RPN) was assigned. A minimum cut- off 40 RPN was considered for interventions and highest RPN errors were prioritized with corrective actions. Post intervention RPN score was calculated. Results: Eight failure modes had the highest RPN. Corrective actions were prioritized against these errors. RPN scores of test ordering error, sample collection error, transport errors, error in patient identification, site selection, urine samples not received, sample accessioning and sample processing errors decreased, post intervention. Conclusion: With thorough planning, we can use FMEA as a common standard to analyze risk in pre analytical phase of laboratory testing. [ABSTRACT FROM AUTHOR]

Mastering the complexity of safety assurance for modern, software-intensive systems is challenging in several domains, such as automotive, robotics, and avionics. Model-based safety analysis techniques show promising results to handle this challenge by automating the generation of required artifacts for an assurance case. In this work, we adapt prominent approaches and propose to augment of SysML models with component fault trees (CFTs) to support the fault tree analysis and the failure mode and effects analysis. While most existing approaches based on CFTs are only targeting the system topology, e. g., UML class diagrams, we propose an integration of CFTs with SysML internal block diagrams as well as SysML activity diagrams. We realized our approach in a prototypical tool. We conclude with best practices and lessons learned that emerged from our case studies with an electronic power steering system and a boost recuperation system. [ABSTRACT FROM AUTHOR]

Airborne wind energy systems use tethered flying devices to harvest wind energy beyond the height range accessible to tower‐based wind turbines. Current commercial prototypes have reached power ratings of up to several hundred kilowatts, and companies are aiming at long‐term operation in relevant environments. As consequence, system reliability, operational robustness, and safety have become crucially important aspects of system development. In this study, we analyze the reliability and safety of a 100‐kW technology development platform with the objective of achieving continuous automatic operation. We first outline the different components of the kite power system and its operational modes. In the next step, we identify failure modes, their causes, and effects by means of failure mode and effects analysis (FMEA) and fault tree analysis (FTA). Potentially hazardous situations and mechanisms which can render the system nonoperational are identified, and mitigation measures are proposed. We find that the majority of these measures can be performed by a failure detection, isolation, and recovery (FDIR) system for which we present a hierarchical architecture adapted from space industry. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced plastics (CFRP)-packaged fiber Bragg grating (FBG) sensors are widely used in full-scale structural testing of wind turbine blades (WTBs). However, the specific process to make CFRP-packaged FBG sensors, such as packaging, bonding, welding, etc., are mainly manually operated, and no unified standard or rule has been formed yet. Non-standard specific processes, coupled with complex stress distribution, unstable working environments, etc., result in the CFRP-packaged FBG sensors having various failures with time, resulting in inaccurate measurements. Thus, the need to carry out related failure analysis is urgent. This paper therefore performed a reliability analysis for CFRP-packaged FBG sensors using failure mode and effects analysis (FMEA) and fault tree analysis (FTA) techniques. The results provide an important basis towards analyzing performance degradation and functional failures for CFRP-packaged FBG sensors.

As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization and safety. Big data and knowledge-based platforms are receiving much attention to provide a comprehensive decision support system. In this study, the Advanced Advisory system for Anomalies (AAA) is developed to predict and detect the abnormal operation in fired heaters for real-time process safety and optimization in a petrochemical plant. This system predicts and raises an alarm for future problems and detects and diagnoses abnormal conditions using root cause analysis (RCA), using the combination of FMEA (failure mode and effects analysis) and FTA (fault tree analysis) techniques. The developed AAA system has been integrated with databases in a petrochemical plant, and the results have been validated well by testing the application over an extensive period. This AAA online system provides a flexible architecture, and it can also be integrated into other systems or databases available at different levels in a plant. This automated AAA platform continuously monitors the operation, checks the dynamic conditions configured in it, and raises an alarm if the statistics exceed their control thresholds. Moreover, the effect of heaters’ abnormal conditions on efficiency and other KPIs (key performance indicators) is studied to explore the scope of improvement in heaters’ operation.

This article presents the main hazards that occur in the context of inland navigation and their impact on the vessel. First, characteristics are extracted from the following methods with regard to identifying threats: involving steering gear damage to an inland vessel moving on a straight waterway. Next, a hazard identification model is presented, which is appropriate to a situation involving steering gear damage to an inland vessel moving on a straight fairway.

O presente trabalho teve como objetivo o desenvolvimento de um sistema especialista para uso como tutor inteligente, auxiliando no treinamento de técnicos em refrigeração. Foram utilizadas técnicas, como Diagrama de Ishikawa, Análise da Árvore de Falhas (FTA) e Análise dos Modos de Falha e seus Efeitos (FMEA), para o levantamento dos principais modos de falhas e procedimentos de manutenção corretiva. O conhecimento heurístico foi programado em um sistema especialista, utilizando a plataforma CLIPS. O programa interage com o usuário, fornecendo o caminho para correção da falha no refrigerador. Observou-se que o sistema especialista é uma excelente ferramenta para armazenamento de informações heurísticas, podendo ser utilizado como ferramenta de apoio às tarefas de manutenção corretiva básica, como tutor inteligente ou evoluir em incrementos, possibilitando um aperfeiçoamento contínuo do programa.

The present work had as objective the development of a specialist system for use as intelligent tutor, assisting in the training of technicians in refrigeration. We used techniques such as Ishikawa Diagram, Fault Tree Analysis (FTA) and Failure Modes Analysis and their Effects (FMEA) to investigate the main failure modes and corrective maintenance procedures. The heuristic knowledge was programmed into a specialist system using the CLIPS platform. The program interacts with the user providing the path for fault correction in the refrigerator. It was observed that the expert system is an excellent tool for storing heuristic information, and it can be used as a tool to support basic corrective maintenance tasks such as intelligent tutor, or evolve in increments, allowing a continuous improvement of the program. [ABSTRACT FROM AUTHOR]

The hazard analysis and management is vital in textile industry to avoid losing customers and wasting resources caused by the failures in production systems. Risk analysis is also very significant to decrease possible hazards and to avoid possible damage in production systems. In this study, an approach based on Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) is proposed to analyze the ring spinning yarn production process in a textile industry. First, the possible hazards in the production line, yarn production system, in an integrated company operating in the textile sector are analyzed by FTA method. Then, FMEA is applied to ring spinning yarn production process in a textile industry to rank all possible risks corresponding to hazards in descending order with respect to both occupational health and safety. It is very important to remove all possible hazards in textile industry to decrease the number of risks related to occupational health and safety. Therefore, in total of 57 hazard root causes are determined in the yarn production department. Subsequently, the faults related to the hazard root causes are examined by FTA and then risk corresponding to these hazards are prioritized by FMEA. The results obtained from the proposed FTA-FMEA approach show that decision makers and engineers can easily decrease the number of hazards and risks with respect to both occupational health and safety in practice. [ABSTRACT FROM AUTHOR]

Defective product is a product that has poor quality and do not meet the standart. This defective products can give a bad impact to company, such as high production costs and decreased image company. Several methods that can be used to improve the quality is Six Sigma DMAIC methodology, FTA, and FMEA method. This study is conducted for several purpose, they are to determine the value of sigma level on the process of sugar production in PT.PG. Krebet Baru, to determine the factors that cause defective products in the process of sugar production by the FTA method, and to make a suitable solution based on the FMEA defective causes. The process sigma level in PT.PG.Krebet Baru is 3.58. That value sigma level indicates PT. PG. Krebet Baru is a company that are still growing and need improvement. The primary cause of the defects in the production process is a factor of operator and machine. Mode of failure with the highest RPN at 210 is time for steam process is too long, so they need to install the equipment that can detect the water level on sugar. When this equipment is installed, the exact time for drying will be known and the amount of defective product will be decreased.

When designing a maintenance programme for a capital good, especially a new one, it is of key importance to accurately understand its failure behaviour. Failure mode and effects analysis (FMEA) and fault tree analysis (FTA) are two commonly used methods for failure analysis. FMEA is a bottom-up method that is less structured and requires more expert knowledge than FTA, which is a top-down method. Both methods are time-consuming when applied thoroughly, which is why in many cases, they are not applied at all. We propose a method in which both are used in a recursive manner: First, a system level FTA is performed, which results in a set of failure modes. Using FMEA, the criticality of the failure modes is assessed in order to select only the critical system level failure modes. For each of those, a function level FTA is performed, followed by an FMEA. Finally, a component level FTA and FMEA are performed on the critical function level failure modes. We apply our method to a recently developed additive manufacturing system for metal printing, the MetalFAB1 of Additive Industries (AI), and find that the engineers at AI consider the method to be efficient and effective. [ABSTRACT FROM AUTHOR]

Application of active suspensions in high-speed passenger trains is gradually getting more and more common. Active suspensions are primarily aimed at improving ride comfort, wear or stability. Failure of these systems may not only just deteriorate the performance but it may also put vehicle safety at risk. There are not many studies that explain how a thorough study proving safety of active suspension should be performed. Therefore, initiating this type of study is necessary for not only preventing incidences but also for assuring acceptance of active suspension by rail vehicle operators and authorities. This study proposes a flowchart for systematic studies of active suspension failures in rail vehicles. The flowchart steps are solidified by using failure mode and effects analysis and fault tree analysis techniques and also acceptance criteria from the EN14363 standard. Furthermore, six failure modes are introduced which are very general and their use can be extended to other studies of active suspension failure. In the last section of the paper, the proposed flowchart is put into practice through four failure examples of active vertical suspension. [ABSTRACT FROM AUTHOR]