Failure Mode Effects And Criticality Analysis Research Articles

D-S evidence based FMECA approach to assess potential risks in ballast water system (BWS) on-board tanker ship

Ballast water is essential for cargo ships since it stabilizes vessels at sea. Most ships are equipped with a ballast water system (BWS) to maintain safe operating conditions. This paper attempts to perform a risk assessment for the BWS on-board tanker ship as it poses a major threat to the operational safety of the ship, marine environment, and cargo. To achieve this purpose, the paper utilizes a robust methodology integrating D-S evidence (Dempster-Shafer) theory and FMECA (Failure mode effects and criticality analysis). In the methodology, while the D-S evidence theory introduces a proper mathematical framework to handle epistemic uncertainty in the assessment of risk parameters and to prioritize failure modes as intended, the FMECA is capable of evaluating system potential failures and their causes. Hence, the risk priority number (RPN) can be calculated to assess potential hazards and their consequences in BWS on-board ships. Besides its theoretical insight, the paper contributes to marine safety inspectors, safety researchers, and HSEQ (Health, Safety, Environment, and Quality) managers to identify potential hazards, effects, and consequences in case of BWS failures on-board tanker ships.

Development of Fault Diagnostics and Prognosis System Based on Digital Twin and Blockchain

In this paper, a development of fault diagnostics and prognosis system based on digital twin and blockchain is demonstrated. The main focus is to provide cheaper solution for maintenance operations, data safety, and machines’ life control. Initially, various details of prerequisites required by an engineer to conduct machinery condition monitoring is discussed. This include concepts of instrumentation, signal processing techniques such as vibration monitoring, motor volume signature analysis, and thermography where debris analysis and detection techniques are discussed. Furthermore, principles on how to operate maintenance operations in particular conditions illustrating the best techniques available for making a good maintenance decisions known as FEMCA (Failure Mode Effects and Criticality Analysis) are described. The experimental evaluation is performed to monitor the alignment of shaft and missing gear tooth using a simple locking mechanism using a sensor.

FMECA Application in Tomotherapy: Comparison between Classic and Fuzzy Methodologies

Accident analysis in radiotherapy highlighted the need to increase quality assurance (QA) programs by the identification of failures/errors with very low probability (rare event) but very severe consequences. In this field, a Failure Mode, Effects and Criticality Analysis (FMECA) technique, used in various industrial processes to rank critical events, has been met with much interest. The literature describes different FMECA methods; however, it is necessary to understand if these tools are incisive and effective in the healthcare sector. In this work, comparisons of FMECA methodologies in the risk assessment of patients undergoing treatments performed with helical tomotherapy are reported. Failure modes identified for the phases “treatment planning” and “treatment execution” are classified using the Risk Priority Number (RPN) index. Differences and similarities in the classification of failures/errors of the examined FMECA approaches are highlighted.

Failure mode effect and criticality analysis of ultrasound device by classification tracking

BackgroundMedical ultrasound device has been more and more widely used in the hospital and Its safety risk is significantly increased when failures occur. However, there is a lack of quantitative risk assessments of different types of failure modes for medical ultrasound device. This study utilizes a failure mode, effect and criticality analysis (FMECA) approach for quantitative risk evaluation of different failure modes for ultrasound devices.MethodsThe 4216 medical ultrasound device failure records at various hospitals were investigated. A failure mode and effect analysis method was developed for the quantitative evaluation of the risks of different failure modes. Visual correlation analysis was conducted for all categories to identify the causes of various failure modes. Based on the severity, occurrence and detectability of the failure causes determined, the risk priority number (RPN) for each failure mode was back-calculated through the obtained tracking diagram.ResultsThe failure modes of unclear images, unable to power on and dark shadows on an image had the highest RPNs. One failure mode could be caused by various factors, and the failure location was not necessarily related to the cause of the failure.ConclusionsThis quantitative approach more accurately evaluated the risks of different failure modes, and the results of the corresponding analysis of failure modes and causes could support the rapid determination of the causes of failures in clinical practice.

An Integrated Approach-Based FMECA for Risk Assessment: Application to Offshore Wind Turbine Pitch System

Failure mode, effects and criticality analysis (FMECA) is a well-known reliability analysis tool for recognizing, evaluating and prioritizing the known or potential failures in system, design, and process. In conventional FMECA, the failure modes are evaluated by using three risk factors, severity (S), occurrence (O) and detectability (D), and their risk priorities are determined by multiplying the crisp values of risk factors to obtain their risk priority numbers (RPNs). However, the conventional RPN has been considerably criticized due to its various shortcomings. Although significant efforts have been made to enhance the performance of traditional FMECA, some drawbacks still exist and need to be addressed in the real application. In this paper, a new FMECA model for risk analysis is proposed by using an integrated approach, which introduces Z-number, Rough number, the Decision-making trial and evaluation laboratory (DEMATEL) method and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method to FMECA to overcome its deficiencies in real application. The novelty of this paper in theory is that the proposed approach integrates the strong expressive ability of Z-numbers to vagueness and uncertainty information, the strong point of DEMATEL method in studying the dependence among failure modes, the advantage of rough numbers for aggregating experts’ diversity evaluations, and the strength of VIKOR method to flexibly model multi-criteria decision-making problems. Based on the integrated approach, the proposed risk assessment model can favorably capture and aggregate FMECA team members’ diversity evaluations and prioritize failure modes under different types of uncertainties with considering the failure propagation. In terms of application, the proposed approach was applied to the risk analysis of failure modes in offshore wind turbine pitch system, and it can also be used in many industrial fields for risk assessment and safety analysis.

IQbD: A Technological Readiness Level-Indexed Quality-by-Design Paradigm for Medical Device Engineering

Abstract Risk assessment is a critical step in the roadmap of medical device development (MDD). Failure modes, effects and criticality analysis is a common approach based on declarative prior information that proved beneficial in the risk assessment of well-established processes. But at early steps of development when innovative materials or technologies are embedded, the lack of experience on those innovations introduces too much subjectivity in failure modes, effects, and criticality analysis (FMECA) for a robust risk assessment. Since mid-2000, the quality-by-design (QbD) guideline has been proposed within the pharmaceutical industry as a pro-active engineering approach to drug development. This paradigm enables a data-driven risk assessment throughout the development workflow, which completes the risk assessment provided by FMECA. Nevertheless, its implementation guide is unclear and not flexible enough to be efficiently applied to the development of medical devices. To address this issue, a new quality by design (QbD) paradigm indexed on the technological readiness level of the innovative product is proposed. It covers the development of medical devices throughout the whole preclinical phase and is composed of at least nine learning cycles. The first part of this medical device QbD layout, composed of three consecutive risk assessment cycles, is evaluated through a real study case with the objective to demonstrate the proof of concept of a photobleaching controller in photodynamic therapy. Beyond this experimental result, this application has confirmed practical ability of the indexed quality by design (iQbD) approach to complete FMECA and to provide an alternative solution to risk assessment when prior knowledge on the technological innovation is not available.

Risk Assessment of Failures in Generic Drug Development and Approval Procedure under Competitive Generic Drug Therapy and Patent Challenge Exclusivities Provided by the United States Food and Drug Administration

Abstract Objective: The United States Food and Drug Administration implemented two exclusivity programs Competitive generic therapy and Patent Challenge exclusivity to develop generic drugs, which provide a 180-day monopoly market for first generic applicants in the United States of America. The aim of the present study is to find the root cause of failures in developing and filing the first generic drugs under these exclusivities and to compare both the exclusivities to find the merits and demerits. Methods: We used descriptive statistics for data analysis of both the exclusivities and Risk assessment was conducted on 14 industries to find the root cause of failures in every stage of the approval procedure by FMECA (Failure mode, Effects and Criticality Analysis). Results: We found 44% of rejections in competitive generic therapy drugs and 30% of rejections in patent challenge exclusivity drugs. The risk analysis conducted on failures found that, in drug selection, 6% of failures are occurred due to rare diseases. In drug development, 9% of failures are occurred due to formulation failures. In pre-approval, 10% of failures are occurred due to secondary patents. In post-approval, 6% of failures are occurred due to product changes after approval. Conclusion: We hope this study can give an idea for small and medium companies in developing countries for the early development of generic drugs for life-threatening diseases.

Risk Assessment of Railway Switch and Crossing Failures: Case Study of an Urban Rail Transit in Thailand

Railways are becoming the main transportation mode in Thailand. Thus, maintaining the optimal service level to passengers is one of the significant issues that need to be addressed. This makes the way to manage railway assets extremely important, especially with the essential assets on a railway network such as switches and crossings (S&C). This study presents how the risk of switch and crossing failures could be assessed and managed. The process of the risk management is based on ISO 31000, and the method used to analyse the risk is the Failure Modes, Effects and Criticality Analysis (FMECA). In detail, the switches and crossings on the Airport Rail Link city line (ARL), Thailand, are considered as a case study. The interview data from six experts, engineers and technicians who are responsible for the maintenance of S&C were used to determine the risk of each S&C component. The results show that the point machines, check and wing rails are the most critical components of S&C in the case study, and the least critical components are heel blocks, slide chairs and closure rails. Based on these findings, it is suggested that the current S&C maintenance program of the ARL may need to be improved. The priority of the inspection and maintenance activities of each S&C component could be adjusted according to the risk evaluation results presented in this study.

Improved FMECA for effective risk management decision making by failure modes classification under uncertainty

Failure Mode, Effects, and Criticality Analysis (FMECA) is a proactive reliability and risk management technique extensively used in practice to ensure high system performance by prioritising failure modes. Owing to the limitations of traditional FMECA, multi-criteria decision-making methods have been employed over the past two decades to enhance its effectiveness. To consider the vagueness and uncertainty of the FMECA evaluation process, an interval-based extension of the Elimination et Choice Translating Reality (ELECTRE) TRI method is proposed in the present paper for the classification of failure modes into risk categories. Therefore, ratings of failure modes against risk parameters are provided in an interval form by a panel of FMECA experts and then properly synthesised to provide a group consensus and improve the accuracy of the results. The relative importance of the risk parameters is also considered. The method is validated using a numerical example relating to the propulsion system of a fishing vessel.

Association rules and social network analysis for supporting failure mode effects and criticality analysis: Framework development and insights from an onshore platform

The ongoing digital transformation enables the collection of a vast amount of data from the maintenance and production processes. Hence, the techniques traditionally applied for monitoring the operations and defining the maintenance approaches for improving the asset reliability can be accompanied by new methodologies more oriented to data analytics. In this context, this work proposes a data-driven framework for supporting the analysis of the production processes in terms of failures and related effects through the well-known and widely applied Failure Mode, Effect, and Criticality Analysis (FMECA). Indeed, after developing the Failure Mode Effects and Criticality Analysis, the results obtained for the plant under investigation are elaborated through Machine Learning techniques such as the Association Rule Mining to define the cause-effect relationships that led to a failure. The association rules extracted are then processed through the Social Network Analysis to represent such relationships, facilitate their comprehension, and identify the existence of communities of nodes to detect critical patterns and locate the most influential nodes. The knowledge of such details can provide helpful support in terms of awareness of the plant and the development of intelligent maintenance procedures.The proposed approach is applied to an off-shore and on-shore platform to assess the impact of the theoretical analysis on the practical implementation by highlighting unknown relations among the analyzed variables and showing new cause-effect relationships.

Safety analysis of a high-pressure fuel gas supply system for LNG fuelled vessels

The liquified natural gas (LNG) is currently considered an attractive marine fuel in the short- to medium-terms that can lead to the reduction of the shipping industry carbon emissions. LNG fuelled ocean-going ships have been designed by employing either low-pressure or high-pressure fuel systems. This study aims at enhancing the safety of a high-pressure fuel gas supply system (FGSS) designed for ocean-going LNG fuelled vessels. A model-based safety analysis is performed by employing the MADe™ software. The functional model of the baseline design of the investigated system is developed and subsequently employed to carry out the Failure Modes, Effects and Criticality Analysis (FMECA), as well as the quantitative Fault Tree Analysis (FTA). FMECA provided the risk priority number (RPN) for the identified system failure scenarios, the analysis of which leads to the identification of the FGSS critical components. The FTA results, which include the probabilities of the selected top events and appropriate importance metrics, are used for the FMECA results verification. This study results demonstrate that the FGSS critical components include the process valves responsible for supplying either LNG or natural gas to the gas treatment system and consumers respectively, as well as the pressure feedback controllers. Recommendations for design alterations pertain to the addition of pressure sensors and redundancy of the identified critical system components. The derived results demonstrate that impact of these design alterations on the calculated safety metrics are quite considerable, thus enhancing the safety of the baseline design. This study contributes to the safety analysis of FGGS and supports decisions for the designer and operator of LNG fuelled ships.

Abstract TP74: Risk Assessment Of The Acute Stroke Diagnostic Process

Introduction: Acute stroke (AS) is a high-harm, high-cost condition that affects nearly 800,000 people/year in the US. Proven, time-sensitive treatments can reduce disability. However, to deliver an AS treatment, a timely and accurate diagnosis is first needed. Yet, diagnostic error is the most common type of error in AS, occurring in ~10% of AS patients, and higher in patients with mild or atypical presentations. Hypothesis: The identification, characterization, and ranking of failures of the AS diagnostic process, by clinicians who provide AS care in the ED, is an essential step prior to designing feasible, robust, and effective solutions to reduce AS diagnostic error. Methods: A Learning Collaborative (LC) of clinicians involved in the AS diagnostic process at 3 health systems in Chicago, IL participated in a Failure Modes, Effects, and Criticality Analysis (FMECA) to identify the steps in the AS diagnostic process, failures of each step and their underlying causes, and to characterize each failure’s frequency (F), impact (I) on making a timely and accurate AS diagnosis, and any existing safeguards (S), using standardized scores. A risk priority index (RPN=FxIxS) and a criticality number (CN=FxI) was calculated for each failure and rank ordered. Results: In a series (N=7) of 60-90 minute virtual sessions, the LC, comprised of Emergency Medicine (N=9), Neurology (N=10), and Radiology (N=1) clinicians of all professions (MD, RN, Technician) and levels (resident, attending, coordinator), created an AS diagnostic process map and risk table. The process map included 27 specific steps. The highest risk steps were failure to use a severe stroke/large vessel occlusion scale (RPN=432; CN=72); inability to establish patients’ last known well (RPN=384; CN=48); failure to use an AS screening scale (RPN=384; CN=54); lack of a “witness” of the event to confirm information (RPN=378; CN=42); and failure to recognize potential stroke and activate a stroke code at triage (RPN=288; CN=48). Conclusion: This study, for the 1 st time, reveals specific targets, particularly in the early phase of the AS diagnostic process, for which solutions should be designed (e.g., standardized process to use a severe stroke/LVO tool) to reduce AS diagnostic error.

Improving Homecare Risk Management and Patient Safety


 Background: Risk management in the domiciliary healthcare setting is a harder challenge than in a hospital environment. Many, not always predictable, variables related to the patient, the caregiver, the health professionals and the home environment make it impossible to guarantee complete safety in homecare. The first aim of the study was to verify that the Electrical Medical Devices (EMD) and medical Consumables Supplies (CS) provided to mechanically ventilated and artificially fed patients at home comply with requirements for safe homecare. 
 Methods: We conducted a Failure Modes, Effects and Criticality Analysis (FMECA) on two processes, mechanical ventilation and artificial feeding at home, and defined a local institutional list of the requirements for safe home healthcare; a checklist containing all the items in the list was administered to ventilated and artificially fed patients at home. 
 Results: The checklist was used for 92 home patients, sex M/F=52/40, mean age 59,8±22 years (range 2÷102 years). Many failures were highlighted when the checklist was applied and problems affecting AMBU resuscitator bags, tracheostomy tubes, ventilators in patients being mechanically ventilated around-the-clock and ventilator circuits were identified as the most critical potential vulnerabilities for homecare patients. 
 Conclusion: The checklist is a simple and valid tool for implementing proactive clinical risk management initiatives in homecare. Although it is impossible to guarantee complete safety in any healthcare environment, scheduling periodic checks with checklists to assess the quantitative and qualitative adequacy of EMD and CS provided to the patient could contribute to the homecare risk reduction. 

Cartographie des risques liés à l’organisation de la campagne de vaccination contre la COVID-19

ObjectifsEn 2020, la COVID-19 a causé plus de 260 000 hospitalisations et près de 64 000 morts en France. La vaccination est le principal espoir pour contrôler la pandémie. Notre objectif est de réaliser la cartographie des risques relatifs à l’organisation du début de la campagne vaccinale contre la COVID-19 dans la région Provence-Alpes-Côte d’Azur, de décembre 2020 à avril 2021 (inclus).MéthodeAprès avoir décrit le processus relatif à l’organisation de la campagne de vaccination contre la COVID-19, les risques, les causes, les conséquences et les éléments de maîtrise ont été identifiés par 15 entretiens semi-directifs. L’analyse a été menée selon l’approche par processus, complétée par une analyse des modes de défaillances, de leurs effets et de leurs criticités (AMDEC).RésultatsLe processus se décline en une approche collective et une individuelle. Quarante-sept risques ont été identifiés et 15 actions proposées. La logistique d’approvisionnement régional, les lieux de vaccination, la gestion des rendez-vous et le système d’information Vaccin-COVID sont les points critiques. La surcharge de travail est le risque le plus souvent vécu (n = 18), favorisant la désaffection des professionnels de santé, menace majeure de cette organisation. L’éligibilité, la consultation médicale et la période post-vaccination sont maîtrisées.ConclusionsCette analyse a permis d’identifier les risques liés à l’organisation de la campagne de vaccination contre la COVID-19 et de proposer des actions d’amélioration prioritaires susceptibles d’optimiser les pratiques actuelles et futures. Elle apporte une vision régionale, à confronter à d’autres données régionales, nationales et internationales.

Failure mode effect analysis for a better functional composite rocket motor casing

Composite Rocket Motor Casing (CRMC) is one of the highly critical elements of Solid Rocket Motor (SRM) and Launch Vehicle (LV). Being a single shot device and designed with a marginal Factor of Safety (FOS), it calls for a robust design with a high order of reliability. Composites are strongly influenced by the manufacturing process and are susceptible to flaws. To, take care of the manufacturing process variability, it demands stringent process and quality control. Any design or process non-conformity and defects in composites may have a functional influence resulting in a calamitous effect and total mission failure. In this present study, as part of a systematic risk assessment framework, Failure Mode Effect Analysis (FMEA) and Failure Mode Effect and Criticality Analysis (FMECA) are performed on a typical CRMC to study all potential failure modes and their severity. For a typical configuration of CRMC, qualitative analysis in line with MIL-STD-1629A and quantitative FMECA using Risk Priority Number (RPN) is performed. The results are studied in-depth and the most critical and high-risk failure modes are identified using the RPN method. The results of the FMEA and FMECA are also supported by our experiences in the development of CRMCs of various configurations and experimental test data obtained during qualification testing. Based on our experiences on more than 100 CRMCs, an action plan is developed to mitigate risk and improve design and process robustness. The preventive and corrective actions successfully developed CRMCs and were successfully used in multiple LV without a single failure with expected performance. The results of the FMEA, FMECA analysis, as well as the robustness of the recommendations mentioned in this paper, can form effective and well-established guidelines for CRMC designers and engineering practitioners boosting the overall reliability and lowering overall life cycle program costs.

A new method for risk assessment in industrial processes

Safety is one of the most important issues in modern industrial plants and industrial activities. The Safety Engineering role is to ensure acceptable safety levels of production systems, not only to respect local laws and regulations, but also to improve production efficiency and to reduce manufacturing costs. For these reasons the choice of a proper model for risk assessment is crucial. In this context, the present research aims to propose a new method, called Total Efficient Risk Priority Number (TERPN), able to classify risks and identify corrective actions in order to obtain the highest risk reduction with the lowest cost. The main scope is to suggest a simple, but suitable model for ranking risks in a company, to reach the maximum effectiveness of prevention and protection strategies. The TERPN method is an integration of the popular Failure Mode Effect and Criticality Analysis (FMECA) with other important factors in risk assessment.

Urban floods management using AHP and FMEA methods-case study of Bejaia, Algeria

This study aims to help the management of the Stormwater Drainage System (SDS) of Bejaia City to manage urban flood problems, i.e., to provide them with tools for a better organization of information on SDS combined with a better optimization of its interventions on the network. Our study is based on a multicriteria analysis of the ?SDS-inundation-Impact? system. We used a multicriteria approach and classified the overflow points called Black Points (BPs) using two methods: Analytic Hierarchy Process (AHP) and Failure Mode, Effect and criticality Analysis (FMEA). The criteria and the evaluation scale were defined on the basis of past observations, expert opinions, and feedback experience. The map of the past flooded areas was made and used to calibrate the two models. We mapped the BPs according to intervention priorities (one to four). The outcomes from both models are greatly comparable to the results of the impact assessment of past floods. The proposed approach can also reduce flood risks by integrating some of influencing factors (causing floodings) and the application can be adapted and implemented in other cities too. Both methods are reliable, particularly the AHP for the most overflowing BPs. They could be advantageously combined to improve decision-making.

Assessment of reliability and maintainability of earth pressure balance tunnel boring machine (EPBTBM) – An approach

Earth pressure balance tunnel boring machines (EPBTBM) are used in soft or mixed ground conditions often encountered in tunneling operations. The performance of EPBTBM could be enhanced to a great extent by appropriate time management, proper maintenance and reduced unproductive times such as idle hours and breakdown hours using reliability analysis. The reliability of a system primarily depends on time between failure (TBF) and maintainability is based on time to repair (TTR). Investigations on EPBTBM system performance were carried out for an irrigation tunnel through mixed strata conditions and the failure/repair data were collected. TBF and TTR data are found independent and identically distributed (IID). This implies that data are not following any particular trend or correlation. Therefore, these data are fitted in different types of probability distributions such as Gamma, Lognormal, Weibull with Easyfit and MATLAB tools. All the distributions are subjected to a Kolmogorov-Smirnov (k-s) test. Data analysis carried out on EPBTBM deployed in tunnels showed that TBF data and TTR data are found to best fit in General Gamma (4p) and General Gamma distribution respectively. Analysis indicated that ninety percent level of reliability of the system is at 2.64 h of operation whereas the mean time to repair is 5.78 h. The overall availability of the system was 67% which is comparatively less. Failure mode effects and criticality analysis (FMECA) was also carried out to find the critical part of the EPBTBM system. Disc cutter got the highest risk priority number indicating that it is the most vulnerable part of the EPBTBM. This paper reports that the availability of such systems can be increased to 80 percent by appropriate scheduling, preventive maintenance, and effective use of skilled manpower.

FMECA and MFCC-Based Early Wear Detection in Gear Pumps in Cost-Aware Monitoring Systems

Gear pump failures in industrial settings are common due to their exposure to uneven high-pressure outputs within short time periods of machine operation and uncertainty. Improving the field and line clam are considered as the solutions for these failures, yet they are quite insufficient for optimal reliability. This research, therefore, suggests a method for early wear detection in gear pumps following an extensive failure modes, effects, and criticality analysis (FMECA) of an AP3.5/100 external gear pump manufactured by BESCO. To replicate this condition, fine particles of iron oxide (Fe2O3) were mixed with the experimental fluid, and the resulting vibration data were collected, processed, and exploited for wear detection. The intelligent wear detection process was explored using various machine learning algorithms following a mel-frequency cepstral coefficient (MFCC)-based discriminative feature extraction process. Among these algorithms, extensive performance evaluation reveals that the random forest classifier returned the highest test accuracy of 95.17%, while the k-nearest neighbour was the most cost efficient following cross validations. This study is expected to contribute to improved evaluations of gear pump failure diagnosis and prognostics.

Risk Analysis by Failure Modes, Effects and Criticality Analysis and Biosafety Management During Collective Air Medical Evacuation of Critically Ill Coronavirus Disease 2019 Patients

In March 2020, coronavirus disease 2019 (COVID-19) caused an overwhelming pandemic. To relieve overloaded intensive care units in the most affected regions, the French Ministry of Defence triggered collective air medical evacuations (medevacs) on board an Airbus A330 Multi Role Tanker Transport of the French Air Force. Such a collective air medevac is a big challenge regarding biosafety; until now, only evacuations of a single symptomatic patient with an emergent communicable disease, such as Ebola virus disease, have been conducted. However, the COVID-19 pandemic required collective medevacs for critically ill patients and involved a virus that little is known about still. Thus, we performed a complete risk analysis using a process map and FMECA (Failure Modes, Effects and Criticality Analysis) to assess the risk and implement mitigation measures for health workers, flight crew, and the environment. We report the biosafety management experienced during 6 flights with a total of 36 critically ill COVID-19–positive patients transferred with no casualties while preserving both staffs and aircraft.