Risk and Reliability Analysis of Critical Boiler Components

A Method for Evaluating Quality Assurance Needs in Radiation Therapy

Targeting specimen misprocessing safety events with failure modes and effects analysis.

The Improvement of a Novel Radiation Therapy Workflow by Failure Mode and Effects Analysis

Risk Management: It's Not Just FMEA

Overview of Failure Mode and Effects Analysis (FMEA): A Patient Safety Tool.

Though failure mode and effects analysis (FMEA) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge, its output has never been validated against data on errors that actually occur. The objective of this study was to perform FMEA of a stereotactic body radiation therapy (SBRT) treatment planning process and validate the results against data recorded within an incident learning system. FMEA on the SBRT treatment planning process was carried out by a multidisciplinary group including radiation oncologists, medical physicists, dosimetrists, and IT technologists. Potential failure modes were identified through a systematic review of the process map. Failure modes were rated for severity, occurrence, and detectability on a scale of one to ten and risk priority number (RPN) was computed. Failure modes were then compared with historical reports identified as relevant to SBRT planning within a departmental incident learning system that has been active for two and a half years. Differences between FMEA anticipated failure modes and existing incidents were identified. FMEA identified 63 failure modes. RPN values for the top 25% of failure modes ranged from 60 to 336. Analysis of the incident learning database identified 33 reported near-miss events related to SBRT planning. Combining both methods yielded a total of 76 possible process failures, of which 13 (17%) were missed by FMEA while 43 (57%) identified by FMEA only. When scored for RPN, the 13 events missed by FMEA ranked within the lower half of all failure modes and exhibited significantly lower severity relative to those identified by FMEA (p = 0.02). FMEA, though valuable, is subject to certain limitations. In this study, FMEA failed to identify 17% of actual failure modes, though these were of lower risk. Similarly, an incident learning system alone fails to identify a large number of potentially high-severity process errors. Using FMEA in combination with incident learning may render an improved overview of risks within a process.

Fuzzy Inference Based FMEA for MR Image Based HDR Brachytherapy

Clustering and visualization of failure modes using an evolving tree

Goal: In this work, the application of FMEA (failure mode and effects analysis) in the execution of maintenance of water network in a medium size city in the state of Maranhão was approached. FMEA (failure mode and effects analysis) with occupational safety approach is applied in the execution of water supply network maintenance in a medium size city in the state of Maranhão. This work shows that FMEA is an effective tool for risk prioritization in work process. The FMEA application with use of index reference table can become faster than application without reference table - and thus spread the tool for risk analysis.
 Design / Methodology / Approach: A photographic records was carried out in loco and the main risks to the workers were enumerated and based on the obtained data, a risk analysis was elaborated with the application of FMEA (Failure modes and effects analysis).
 Results: The maintenance services teams of the supply system are subject to a high risk of accidents caused mainly by the working conditions precariousness. It was observed that the services of manual excavations and the lack of use of PPE (helmet, gloves, pants suitable for flooded environments and etc.) have high risk index (RPN) and that the mismanagement added to the unsafe behavior were the main factors to accident occurrence in this type of work.
 Limitations of the investigation: The study studied the reality found in a medium-sized city with precarious working conditions. Further studies can compare the work reality of other teams in cities of different sizes, with better working conditions. Other limitation of this work is the impossibility of work situation improvement and posterior tool application – a study with this magnitude is non-trivial and needs future research.
 Practical implications: The great achievement of this work is to demonstrate that FMEA - a tool that is widely used in maintenance management and product engineering - is able to identify and prioritize risks based on its preliminary risk index obtained - contributing to reduce the difficulty of index choices previously cited in literature and disseminate the FMEA utilization for employee safety and occupational health. Such a tool has a great capacity for quantitative description of the risks, showing that the FMEA is very useful in the work safety sector for the organization of correction plans.
 Originality / Value: The difficulties of using the tool mentioned in the available literature were minimized with the use of the reference table, showing that the use of FMEA can become faster and thus spread the tool for risk analysis.

BackgroundFailure Mode and Effect Analysis (FMEA) is a structured approach to identify and assess potential failure modes and their impact on the system being analyzed to prevent or mitigate failures...

Can traceability of gametes and embryos be ensured during IVF? The use of a simple and comprehensive traceability system that includes the most susceptible phases during the IVF process minimizes the risk of mismatches. Mismatches in IVF are very rare but unfortunately possible with dramatic consequences for both patients and health care professionals. Traceability is thus a fundamental aspect of the treatment. A clear process of patient and cell identification involving witnessing protocols has to be in place in every unit. To identify potential failures in the traceability process and to develop strategies to mitigate the risk of mismatches, previously failure mode and effects analysis (FMEA) has been used effectively. The FMEA approach is however a subjective analysis, strictly related to specific protocols and thus the results are not always widely applicable. To reduce subjectivity and to obtain a widespread comprehensive protocol of traceability, a multicentre centrally coordinated FMEA was performed. Seven representative Italian centres (three public and four private) were selected. The study had a duration of 21 months (from April 2015 to December 2016) and was centrally coordinated by a team of experts: a risk analysis specialist, an expert embryologist and a specialist in human factor. Principal investigators of each centre were first instructed about proactive risk assessment and FMEA methodology. A multidisciplinary team to perform the FMEA analysis was then formed in each centre. After mapping the traceability process, each team identified the possible causes of mistakes in their protocol. A risk priority number (RPN) for each identified potential failure mode was calculated. The results of the FMEA analyses were centrally investigated and consistent corrective measures suggested. The teams performed new FMEA analyses after the recommended implementations. In each centre, this study involved: the laboratory director, the Quality Control & Quality Assurance responsible, Embryologist(s), Gynaecologist(s), Nurse(s) and Administration. The FMEA analyses were performed according to the Joint Commission International. The FMEA teams identified seven main process phases: oocyte collection, sperm collection, gamete processing, insemination, embryo culture, embryo transfer and gamete/embryo cryopreservation. A mean of 19.3 (SD ± 5.8) associated process steps and 41.9 (SD ± 12.4) possible failure modes were recognized per centre. A RPN ≥15 was calculated in a mean of 6.4 steps (range 2-12, SD ± 3.60). A total of 293 failure modes were centrally analysed 45 of which were considered at medium/high risk. After consistent corrective measures implementation and re-evaluation, a significant reduction in the RPNs in all centres (RPN <15 for all steps) was observed. A simple and comprehensive traceability system was designed as the result of the seven FMEA analyses. The validity of FMEA is in general questionable due to the subjectivity of the judgments. The design of this study has however minimized this risk by introducing external experts for the analysis of the FMEA results. Specific situations such as sperm/oocyte donation, import/export and pre-implantation genetic testing were not taken into consideration. Finally, this study is only limited to the analysis of failure modes that may lead to mismatches, other possible procedural mistakes are not accounted for. Every single IVF centre should have a clear and reliable protocol for identification of patients and traceability of cells during manipulation. The results of this study can support IVF groups in better recognizing critical steps in their protocols, understanding identification and witnessing process, and in turn enhancing safety by introducing validated corrective measures. This study was designed by the Italian Society of Embryology Reproduction and Research (SIERR) and funded by the Italian National Transplant Centre (CNT) of the Italian National Institute of Health (ISS). The authors have no conflicts of interest. N/A.

Aim. The aim of this paper is to improve the efficiency of the failure mode and effects analysis (FMEA) method through the verification of expert judgment correctness by means of statistical methods. Therefore, the paper deals with the matters of improving the quality of products and services in various enterprises through risk-oriented approaches. Methods. For the purpose of improving the efficiency of the failure mode and effects analysis (FMEA) method, it is suggested to increase the number of experts, while making the expert evaluation an independent process, i.e. by separating the experts from each other. The resulting expert judgment is proposed to be considered as a random value. The correctness of the expert judgment is suggested to be evaluated by means of statistical criteria methods, e.g. Grubbs’ criterion methods. The proposed evaluation methods are not limited to the Grubbs’ criterion methods. This criterion can be replaced by the Cochran’s criterion or Shewhart charts. Each of the suggested methods enables more efficient estimates with lower risks in the process of service provision or product manufacture. The paper proposes statistical methods with the example of the Grubbs’ criterion. All indicators of the integral estimation of the failure mode and effects analysis are submitted to statistical verification. Results. Such data verification as part of an independent expert evaluation enables a higher reliability of expert judgment and significantly reduces the number of risks at the enterprise. Such risks may include bribing or collusion of experts involved in the performance of the failure mode and effects analysis. Independent expert judgments after expert evaluation are verified by means of statistical methods. Sharp spikes in independent expert opinions will justify repeated expert evaluation, while complete agreement of evaluations will eliminate doubts regarding the quality of the performed assessment. The use of statistical methods for the evaluation of every indicator of the integral FMEA estimation will allow increasing its reliability. A combination of those approaches enables an independent estimation as part of various projects evaluation, including the evaluation of industrial products or provided service using failure mode and effects analysis, elimination of the human factor in the estimation procedure, significant reduction of risks. Conclusions. Failure mode and effects analysis (FMEA) was performed. Additionally, the method was improved by means of independent expert assessment. The consistency of the results of such evaluation is verified by means of statistical methods. The performance of such verification of independent expert opinion is demonstrated through the Grubbs’ criterion. Expert opinion can also be verified by means of Cochran’s criterion, Shewhart charts. The proposed approach is a combination of the failure mode and effects analysis (FMEA) method and statistical methods with the example of Grubbs’ criterion.

Failure modes and effect analysis (FMEA) is a risk prioritization technique mainly used by manufacturing and process industries. In FMEA, the impact of a particular failure mode is calculated using three risk factors. These are severity (S), occurrence (O), and detection (D). This method is suitable for failure determination in processes, designs, products, software, supply chains, etc. This paper includes a systematic review of the advancements in conventional FMEA. Initially, the drawbacks of traditional FMEA are listed to show the scope for improvement. Then the concept of assigning weight to each factor using the analytic hierarchy process (AHP) is studied. The AHP-FMEA with other risk factors is provided in the next part. The second session of this paper contains an overview of seven types of FMEA integration. They are failure mode and effect anticipatory analysis (FMEAA), fuzzy FMEA, FMEA using fuzzy logic and grey relation theory (GRT), hybrid multilevel fault tree analysis (FTA)-FMEA method, FMEA based on Dempster-Shafer Theory (DST), geometric mean FMEA based on information quality, and ambiguity measure weighted risk priority number (AMWRPN) model.

In this Paper, we introduce a novel FMEA (Failure Mode and effect Analysis) system, It can achieve FMEA more practicable and valuable compared with current FMEA application status as record archives. The novel FMEA basic unit is module and related modules are combined to form a whole FMEA, Six new link/experience function modules are introduced into the standard FMEA format to integrate the database, and the module unit exists independently so that different FMEA file cross share the similar failure modules. Three new link function modules can connect FMEA system with other related production systems to embed FMEA useful resource into production as guidance, this link function can prevent potential and old failure modes timely occurring timely, further reduce defect and improve production efficiency and quality. This novel FMEA tool can make FMEA more value and important functions in semiconductor process.

Purpose:Though FMEA (Failure Mode and Effects Analysis) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge it has never been validated against actual incident learning data. The objective of this study was to perform an FMEA analysis of an SBRT (Stereotactic Body Radiation Therapy) treatment planning process and validate this against data recorded within an incident learning system.Methods:FMEA on the SBRT treatment planning process was carried out by a multidisciplinary group including radiation oncologists, medical physicists, and dosimetrists. Potential failure modes were identified through a systematic review of the workflow process. Failure modes were rated for severity, occurrence, and detectability on a scale of 1 to 10 and RPN (Risk Priority Number) was computed. Failure modes were then compared with historical reports identified as relevant to SBRT planning within a departmental incident learning system that had been active for two years. Differences were identified.Results:FMEA identified 63 failure modes. RPN values for the top 25% of failure modes ranged from 60 to 336. Analysis of the incident learning database identified 33 reported near‐miss events related to SBRT planning. FMEA failed to anticipate 13 of these events, among which 3 were registered with severity ratings of severe or critical in the incident learning system. Combining both methods yielded a total of 76 failure modes, and when scored for RPN the 13 events missed by FMEA ranked within the middle half of all failure modes.Conclusion:FMEA, though valuable, is subject to certain limitations, among them the limited ability to anticipate all potential errors for a given process. This FMEA exercise failed to identify a significant number of possible errors (17%). Integration of FMEA with retrospective incident data may be able to render an improved overview of risks within a process.