Reliability Evaluation for Steam Generator in a Sodium-Cooled Fast Reactor

2018 ◽  
Author(s):  
Huang Yi ◽  
Zhang Tian-yi ◽  
Wang Jun ◽  
Yuan Yu-chen ◽  
Dong Xin
Keyword(s):  
Steam Generator ◽  
Fast Reactor ◽  
Failure Modes ◽  
Latin Hypercube Sampling ◽  
Effect Analysis ◽  
Quantitative Calculation ◽  
Sensitive Factor ◽  
Potential Failure ◽  
Failure Mode Effect Analysis

SG (steam generator) is one of the most important equipment in fast reactors, the experience in design and operation of fast reactor worldwide show that failures of SG occurred frequently and often caused serious consequences, therefore it’s necessary to conduct reliability analysis on SG in design phase. FMEA (Failure Mode Effect Analysis) is used to identify all potential failure modes and filter out main failure modes. Then, qualitative analysis and quantitative calculation are carried out to evaluate main failure modes. Next, reliability of SG can be obtained by conducting Latin Hypercube Sampling. Analysis results show that the leakage probability of SG in 20 years is 0.130 219, and the most sensitive factor is the quality of weld in the junction of tubes and tube plate, and the SG meet its reliability requirement.

scholarly journals Identifikasi Potensi Modus Kegagalan Yang Dapat Menghambat Kelancaran Proses Pelayanan Rawat Jalan Menggunakan Failure Mode Effect Analysis (FMEA) Di Rumah Sakit BM Jakarta Barat

2020 ◽  
Vol 8 (2) ◽  
pp. 105-113
Author(s):  
Achmaddudin Sudiro
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Outpatient Service ◽  
Outpatient Services ◽  
Effect Analysis ◽  
Outpatient Unit ◽  
Mode Effect ◽  
Potential Failure ◽  
Fmea Method ◽  
Failure Mode Effect Analysis

Outpatient services hosted by the hospital have never been absent from public visits. In fact, every year an outpatient visitor is always increasing. This research intends to identify potential failure mode that can  inhibit of every flow of service in the outpatient care unit using the Failure Mode Effect Analysis (FMEA) method. Qualitative research plan using an observation survey approach and in-depth interviews with the outpatient service head Coordinator conducted in February 2020 on the hospital outpatient unit service process. The results of this study Indicate the potential failure mode that has the value of the RPN above the value of cut off point 180 as many as six out of ten failure modes. Firstly, the check is not on schedule (360), secondly, the patient lags a turn call order Check (270), third, Specific drug failure is not available (245), fourth, general patient protests with the price of the drug (224), fifth, the patient is void to poly (196), the sixth patient registrant online missed sequence number queue (180). Based on the results of the research, hospitals are expected to follow up with the results of this research by conducting a redesign of the process that occurs today using the FMEA to maintain service quality.

scholarly journals Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study

2012 ◽  
Vol 32 (3) ◽  
pp. 505-514 ◽  
Author(s):  
Sibel Ozilgen
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Chemical Contamination ◽  
Risk Priority Number ◽  
Analysis Model ◽  
Production Potential ◽  
Effect Analysis ◽  
Potential Failure

The Failure Mode and Effect Analysis (FMEA) was applied for risk assessment of confectionary manufacturing, in whichthe traditional methods and equipment were intensively used in the production. Potential failure modes and effects as well as their possible causes were identified in the process flow. Processing stages that involve intensive handling of food by workers had the highest risk priority numbers (RPN = 216 and 189), followed by chemical contamination risks in different stages of the process. The application of corrective actions substantially reduced the RPN (risk priority number) values. Therefore, the implementation of FMEA (The Failure Mode and Effect Analysis) model in confectionary manufacturing improved the safety and quality of the final products.

scholarly journals A Case Study on Recall of used Scopes in the Endoscopy Department by using a Failure Mode & Effect Analysis (FMEA) Proactive Risk Management

2020 ◽  
pp. 13-24
Author(s):  
Zuber Mujeeb Shaikh
Keyword(s):  
Risk Management ◽  
Failure Mode ◽  
Failure Modes ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Mode Effect ◽  
Potential Failure ◽  
Failure Mode Effect Analysis

Failure Mode and Effects Analysis (FMEA) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. The study revealed that the Risk Priority Number (RPN) was initially 450 and it has decreased to 90 after implementing all the actions in FMEA.

Failure Mode and Effect Analysis (FMEA) for Enhancing Reliability of Water Tube Boiler in Thermal Power Plant

2016 ◽  
Vol 8 (02) ◽  
pp. 79-86
Author(s):  
Kapil Dev Sharma ◽  
Shobhit Srivastava
Keyword(s):  
Power Plant ◽  
Failure Mode ◽  
Thermal Power Plant ◽  
Failure Modes ◽  
Thermal Power ◽  
Effect Analysis ◽  
Water Tube ◽  
Potential Failure ◽  
Fmea Method ◽  
Continuous Power

Failure mode and effect analysis is one of the QS-9000 quality system requirement supplements, with a wide applicability in all industrial fields. FMEA is the inductive failure analysis instruments which can be defined as a methodical group of activities intended to recognize and evaluate the potential failure modes of a product/ process and its effects with an aim to identify actions which could eliminate or reduce the chance of the potential failure before the problem occur. The purpose of this paper is to evaluate the FMEA research and application in the Thermal Power Plant Industry. The research will highlight the application of FMEA method to water tubes (WT) in boilers with an aim to find-out all the major and primary causes of boiler failure and reduce the breakdown for continuous power generation in the plant. Failure Mode and Effect Analysis technique is applied on most critical or serious parts (components) of the plant which having highest Risk Priority Number (RPN). Comparison is made between the quantitative results of FMEA and reliability field data from real tube systems. These results are discussed to establish relationships which are useful for future water tube designs.

Using Statistical Model of Failure Mode Effect Analysis for Risk Factors in Industrial Logistics

2015 ◽  
Vol 803 ◽  
pp. 113-120
Author(s):  
Petr Prusa ◽  
Anastasia Kuptcova ◽  
Jan Chocholac ◽  
Srecko Krile ◽  
Miroslav Nadvornik
Keyword(s):  
Risk Factors ◽  
Failure Modes ◽  
Business Plan ◽  
Powerful Method ◽  
Effect Analysis ◽  
Statistical Reliability ◽  
Estimated Parameters ◽  
Mode Effect ◽  
Improved Performance ◽  
Failure Mode Effect Analysis

The paper presents Six-Sigma methodologies, which is powerful method for increasing quality and development of manufacturing, by understanding risk factors, can suggest proper and thoughtful decision-making that may protect the business plan from causes. This study examines a framework of improved performance under the possible influence of different failure modes. Econometric verification presents statistical assumptions for the application of estimated procedures in the area of logistics, especially in the area of industrial logistics. The statistical method for the methodology is to test statistical reliability and the significance of estimated parameters for the analysis of numerical values of risk priority.

A Method for Problem Selection in the 6σ Definition Stage

2010 ◽  
Vol 139-141 ◽  
pp. 1485-1489 ◽  
Author(s):  
Ming Shun Yang ◽  
Yan Li ◽  
Yong Liu ◽  
Xin Qin Gao
Keyword(s):  
Quality Function Deployment ◽  
Customer Requirements ◽  
Effect Analysis ◽  
Customer Expectations ◽  
Mode Effect ◽  
Gray Relation Analysis ◽  
And Control ◽  
Problem Selection ◽  
Failure Mode Effect Analysis

6σ has proved numerous times that it can help any business to deliver products to meet or even exceed customer expectations. DMAIC (Define – Measure – Analyze – Improve - Control) is one of the Six Sigma methodologies used for a 6σ project that aims to improve and control quality of exiting products. Aiming at the drawbacks existed in the problem selection in definition stage, considering the fuzziness and uncertainty of problem analyzing, a method integrating fuzzy QFD (Quality Function Deployment), frequency-cost FMEA (Failure Mode Effect Analysis) and gray relation analysis is presented, in which the customer requirements, occurring frequencies and the relative costs of the problems are taken into account comprehensively. Thus the key quality characteristics or process features to be improved are determined, which can provide decision support for key problem selection. An example is given to illustrate the effectiveness of the proposed method.

Use of failure mode effect analysis (FMEA) to improve medication management process

2017 ◽  
Vol 30 (2) ◽  
pp. 175-186 ◽  
Author(s):  
Khushboo Jain
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Medication Management ◽  
Management Process ◽  
Effect Analysis ◽  
Content Type ◽  
Complex Process ◽  
Mode Effect ◽  
Corrective Actions ◽  
Failure Mode Effect Analysis

Purpose Medication management is a complex process, at high risk of error with life threatening consequences. The focus should be on devising strategies to avoid errors and make the process self-reliable by ensuring prevention of errors and/or error detection at subsequent stages. The purpose of this paper is to use failure mode effect analysis (FMEA), a systematic proactive tool, to identify the likelihood and the causes for the process to fail at various steps and prioritise them to devise risk reduction strategies to improve patient safety. Design/methodology/approach The study was designed as an observational analytical study of medication management process in the inpatient area of a multi-speciality hospital in Gurgaon, Haryana, India. A team was made to study the complex process of medication management in the hospital. FMEA tool was used. Corrective actions were developed based on the prioritised failure modes which were implemented and monitored. Findings The percentage distribution of medication errors as per the observation made by the team was found to be maximum of transcription errors (37 per cent) followed by administration errors (29 per cent) indicating the need to identify the causes and effects of their occurrence. In all, 11 failure modes were identified out of which major five were prioritised based on the risk priority number (RPN). The process was repeated after corrective actions were taken which resulted in about 40 per cent (average) and around 60 per cent reduction in the RPN of prioritised failure modes. Research limitations/implications FMEA is a time consuming process and requires a multidisciplinary team which has good understanding of the process being analysed. FMEA only helps in identifying the possibilities of a process to fail, it does not eliminate them, additional efforts are required to develop action plans and implement them. Frank discussion and agreement among the team members is required not only for successfully conducing FMEA but also for implementing the corrective actions. Practical implications FMEA is an effective proactive risk-assessment tool and is a continuous process which can be continued in phases. The corrective actions taken resulted in reduction in RPN, subjected to further evaluation and usage by others depending on the facility type. Originality/value The application of the tool helped the hospital in identifying failures in medication management process, thereby prioritising and correcting them leading to improvement.

scholarly journals Effectiveness Of Failure Modes Effect Analysis (FMEA)

2017 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
Putri Ingen Setiasih ◽  
Purnawan Junadi
Keyword(s):  
Medical Errors ◽  
Medical Error ◽  
Failure Modes ◽  
Service Process ◽  
Online Database ◽  
Effect Analysis ◽  
Potential Failure ◽  
Publication Period

Objective : One of the prevention efforts of medical errors that occur in health services is by identifying the potential failure of the service before the failure occurs. FMEA is one way to identify the risks of failure. Therefore, the authors wanted to find out whether FMEA was effective for reducing Medical error based on previous studies.Method: This article was a literature review using references in an online database such as EBSCOhost. The author found 280 articles while searching by using the keyword "FMEA". After filtered by publication period from 2012 to 2017, fulltext and language, finally got 7 articles. Finally, the author used the three most relevant literature.Result: FMEA is proven to decrease potential failure rate after follow-up to failure was done in service process, so medical error can be prevented. In the application of FMEA, bias can occur during the determination of potential failure and determination of scoring on RPN. Therefore, it is expected that the team involved in making FMEA experts in the process of service to be designed.Conclusion: FMEA could prevent medical errors by determining potential failure and following up on potential failure before failure occurs.Keywords: FMEA, healthcare, medical error.

Risk and DoE-Based Analytical Failure Mode Effect Analysis (AFMEA) to Simultaneous Estimation of Montelukast Sodium and Bilastine by HPTLC Method Using Enhanced AQbD Approach

2021 ◽  
Author(s):  
Pintu Prajapati ◽  
Jayesh Tamboli ◽  
Ashish Mishra
Keyword(s):  
Risk Management ◽  
Failure Mode ◽  
Failure Modes ◽  
Simultaneous Estimation ◽  
Effect Analysis ◽  
Quality Risk Management ◽  
Montelukast Sodium ◽  
Mode Effect ◽  
Quality Risk ◽  
Failure Mode Effect Analysis

Abstract The fixed-dose combination (FDC) of montelukast sodium (MLS) and bilastine (BIL) is used for monotherapy in the patient with seasonal allergic rhinoconjuctivitis and asthma. According to the upcoming ICH (International Council for Harmonization) Q14 guideline, the development of the analytical method by the implementation of the Analytical Quality by Design (AQbD) approach based on principles of Quality Risk Management (QRM) and design of experiments (DoE) would be a regulatory requirement for the registration of new drug substance and product in ICH countries. Hence, a robust high-performance thin layer chromatography method has been developed, which was not previously reported for simultaneous estimation of MLS and BIL using risk and DoE-based enhanced AQbD approach. The analytical failure mode effect analysis (AFMEA) was started with the identification of potential analytical failure modes followed by their effect analysis by RPN ranking and filtering method. The DoE-based AFMEA was applied for optimization of high-risk analytical failure modes by central composite design using Design-Expert software. The method operable design ranges and control strategy was set for quality risk management throughout the lifecycle of the developed method. The developed method was validated as per ICH Q2 (R1) guideline. The method was applied for the assay of FDC, and results were found in compliance with the labeled claim.

scholarly journals Proactive risk assessment of vincristine use process in a teaching and referral hospital in Kenya and the implications

2019 ◽  
Vol 26 (3) ◽  
pp. 666-679 ◽  
Author(s):  
Emmanuel K Kurgat ◽  
Irene Weru ◽  
David Wata ◽  
Brian Godman ◽  
Amanj Kurdi ◽  
...  
Keyword(s):  
Failure Modes ◽  
Single Point ◽  
Referral Hospital ◽  
Control Measures ◽  
Flow Diagram ◽  
Effect Analysis ◽  
Middle Income ◽  
Middle Income Countries ◽  
Potential Failure ◽  
And Storage

Introduction The chemotherapy use process is potentially risky for cancer patients. Vincristine, a “High Alert” medicine, has been associated with fatal but preventable medication errors. Consequently, there is a need to improve the use of vincristine especially in lower- and middle-income countries where there are constraints with resources and often a lack of trained personnel to administer cancer medicines. However, where there is a rising prevalence of cancer cases. These concerns can be addressed by performing proactive risk assessments using Healthcare Failure Mode Effect Analysis (HFMEA) and implementing the findings. Methods A multidisciplinary health team driven by pharmacists identified and evaluated potential failure modes based on a vincristine use process flow diagram using a hazard scoring matrix in a leading referral hospital in Kenya. Results The processes evaluated were: prescribing, preparation and dispensing, transportation and storage, administration and monitoring of the use of vincristine. Seventy-seven failure modes were identified over the three-month study period, of which 25 were classified as high risk. Thirteen were adequately covered by existing control measures while 12 including one combined mode required new strategies. Two of the failure modes were single-point weaknesses. Recommendations were subsequently made for improving the administration of vincristine. Conclusions HFMEA is a useful tool to identify improvements to medication safety and reduction of patient harm. The HFMEA process brings together the multidisciplinary team involved in patient care in actively identifying potential failure modes and owning the recommendations made, which are now being actively followed up in this hospital. Pharmacists are a key part of this process.

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