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Journal articles on the topic 'Failure mode and effects analysis (FMEA)'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Alruqi, Mansoor, Martin Baumers, David Branson, and Robert Farndon. "A Structured Approach for Synchronising the Applications of Failure Mode and Effects Analysis." Management Systems in Production Engineering 29, no. 3 (2021): 165–77. http://dx.doi.org/10.2478/mspe-2021-0021.

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Abstract Failure Mode and Effects Analysis (FMEA) is a systematic approach for evaluating the potential failure modes in a system, and is mainly employed in three distinct tasks labelled: (1) Functional FMEA – evaluating those failures associated with product functional definition, (2) Design FMEA – analysing those failures associated with design definition and (3) Process FMEA – assessing potential failures in manufacturing and assembly processes. The literature review has shown limited works on the field of synchronising these different tasks into a working model. To address this gap, this r

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BOUTI, ABDELKADER, and DAOUD AIT KADI. "A STATE-OF-THE-ART REVIEW OF FMEA/FMECA." International Journal of Reliability, Quality and Safety Engineering 01, no. 04 (1994): 515–43. http://dx.doi.org/10.1142/s0218539394000362.

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The Failure Mode and Effects Analysis (FMEA) documents single failures of a system, by identifying the failure modes, and the causes and effects of each potential failure mode on system service and defining appropriate detection procedures and corrective actions. When extended by Criticality Analysis procedure (CA) for failure modes classification, it is known as Failure Mode Effects and Criticality Analysis (FMECA). The present paper presents a literature review of FME(C)A, covering the following aspects: description and review of the basic principles of FME(C)A, types, enhancement of the met

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Krouwer, Jan S. "An Improved Failure Mode Effects Analysis for Hospitals." Archives of Pathology & Laboratory Medicine 128, no. 6 (2004): 663–67. http://dx.doi.org/10.5858/2004-128-663-aifmea.

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Abstract Objective.—To review the Failure Mode Effects Analysis (FMEA) process recommended by the Joint Commission on Accreditation of Health Organizations and to review alternatives. This reliability engineering tool may be unfamiliar to hospital personnel. Data Sources.—Joint Commission on Accreditation of Health Organizations recommendations, Mil-Std-1629A, and other articles about FMEA were used. Study Selection.—The articles were selected by a literature search that included Web site–accessible material. Data Extraction.—All articles found were used. Data Synthesis.—The results are based

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Roy, Soumen Kumar, A. K. Sarkar, and Biswajit Mahanty. "Fuzzy risk assessment for electro-optical target tracker." International Journal of Quality & Reliability Management 33, no. 6 (2016): 830–51. http://dx.doi.org/10.1108/ijqrm-03-2015-0034.

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Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from techni

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Price, C. J., J. E. Hunt, M. H. Lee, and A. R. T. Ormsby. "A Model-Based Approach to the Automation of Failure Mode Effects Analysis for Design." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 206, no. 4 (1992): 285–91. http://dx.doi.org/10.1243/pime_proc_1992_206_189_02.

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This paper describes the application of model-based technology in the area of failure mode effects analysis (FMEA). FMEA involves the repetitive application of engineering expertise, and so would seem to be a promising target for automation through knowledge-based systems (KBS) technology. However, in order to decide what would be the effect of a failure in a sub-system, it is necessary to reason about the structure of the sub-system being investigated and to be able to represent and reason about different facets of the way in which the sub-system works. The difficulty of automating this analy

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EFE, Burak. "An integrated fuzzy approach based failure mode and effects analysis for a risk assessment." Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 11, no. 2 (2022): 681–96. http://dx.doi.org/10.17798/bitlisfen.1088988.

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This paper provides to cope with the limitations of traditional FMEA by using an integrated fuzzy multi-criteria decision making method, which considers fuzzy extension of AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and a linear programming. The proposed method is shown for an application to failure mode and effects analysis (FMEA) based risk assessment of a construction firm. Firstly, fuzzy extension of AHP approach is utilized to define the weights of criteria in risk evaluation. Secondly, fuzzy TOPSIS approach is used t

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NICOLIN, Ilie, and Bogdan Adrian NICOLIN. "Failure Mode and Effect Analysis for a military nose landing gear project." INCAS BULLETIN 13, no. 4 (2021): 205–12. http://dx.doi.org/10.13111/2066-8201.2021.13.4.17.

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Failure Mode and Effect Analysis (FMEA) techniques were originally developed by the US Military and have been used as techniques for assessing the reliability and effects of equipment failures. However, the first notable applications of FMEA techniques are related to the impressive development of the aerospace industry in the mid-1960s. FMEA is a methodology for systematically analyzing the failure modes of a project, product or process, prioritizing their importance, identifying system failure mechanisms, analyzing potential failure modes and the effects of these failures, followed by correct

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Gill, Adrian, Ireneusz Pielecha, and Filip Szwajca. "A New Method of Failure Mode and Severity Effects Analysis for Hydrogen-Fueled Combustion Systems." Energies 17, no. 19 (2024): 4802. http://dx.doi.org/10.3390/en17194802.

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This article aims to align its content with current trends in hybrid risk analysis methods while utilizing experimental research. This paper presents a hybrid methodology for analyzing the failure severity of a two-stage hydrogen-powered combustion system and details its implementation. This methodology assumes the use of the original FMESA method (Failure Mode and Effects Severity Analysis) with dedicated tabular scales of the failure severity. Obtaining results under the FMESA using experimental research is intended to reduce epistemic uncertainty, which is an important component of hazard s

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Lee, Dongwoo, Dongmin Lee, and Jongwhoa Na. "Automatic Failure Modes and Effects Analysis of an Electronic Fuel Injection Model." Applied Sciences 12, no. 12 (2022): 6144. http://dx.doi.org/10.3390/app12126144.

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In the development of safety-critical systems, it is important to perform failure modes and effects analysis (FMEA) to identify potential failures. However, traditional FMEA activities tend to be considered difficult and time-consuming tasks. To compensate for the difficulty of the FMEA task, various types of tools are used to increase the quality and the effectiveness of the FMEA reports. This paper explains an automatic FMEA tool that integrates the model-based design (MBD), FMEA, and simulated fault injection techniques in a single environment. The automatic FMEA tool has the following adva

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Haktanır, Elif, and Cengiz Kahraman. "Interval-valued neutrosophic failure mode and effect analysis." Journal of Intelligent & Fuzzy Systems 39, no. 5 (2020): 6591–601. http://dx.doi.org/10.3233/jifs-189121.

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Failure mode and effects analysis (FMEA) is a structured approach for discovering possible failures that may occur in the design of a product or process. Since classical FMEA is not sufficient to represent the vagueness and impreciseness in human decisions and evaluations, many extensions of ordinary fuzzy sets such as hesitant fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, spherical fuzzy sets, and picture fuzzy sets. Classical FMEA has been handled to capture the uncertainty through these extensions. Neutrosophic sets is a different extension from the others handling the unce

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Manestar, Vedran, Anita O'Donovan, and Sarah Barrett. "Failure Mode and Effects Analysis Application in External Beam Radiotherapy." Radiološki vjesnik 48, no. 1 (2024): 13–25. http://dx.doi.org/10.55378/rv.48.1.3.

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Background: Radiotherapy is a medical procedure with potential high risk to harm patients. In order to reduce that risk and create a workflow safe for patients, prospective analysis tools are used. Failure modes and effect analysis (FMEA) is one such tool, used to evaluate potential risks. As FMEA originated from industry, there is a constant effort to adjust FMEA methodology for use in radiotherapy. This has caused a variety of approaches and inhomogeneous practices. Purpose: To investigate the current practice of FMEA in external beam radiotherapy and to propose a more standardised approach.

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Molnár, Vince, and István Majzik. "Model Checking-based Software-FMEA: Assessment of Fault Tolerance and Error Detection Mechanisms." Periodica Polytechnica Electrical Engineering and Computer Science 61, no. 2 (2017): 132. http://dx.doi.org/10.3311/ppee.9755.

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Failure Mode and Effects Analysis (FMEA) is a systematic technique to explore the possible failure modes of individual components or subsystems and determine their potential effects at the system level. Applications of FMEA are common in case of hardware and communication failures, but analyzing software failures (SW-FMEA) poses a number of challenges. Failures may originate in permanent software faults commonly called bugs, and their effects can be very subtle and hard to predict, due to the complex nature of programs. Therefore, a behavior-based automatic method to analyze the potential effe

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Pino, Felicity A., Darcy K. Weidemann, Lisa L. Schroeder, Damon B. Pabst, and Audrey R. Kennedy. "Failure mode and effects analysis to reduce risk of heparin use." American Journal of Health-System Pharmacy 76, no. 23 (2019): 1972–79. http://dx.doi.org/10.1093/ajhp/zxz229.

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Abstract Purpose Failure mode and effects analysis (FMEA) was used to identify safety risks of unfractionated heparin (UFH) use and to develop and implement countermeasures to improve safety. Methods FMEA was used to analyze the transportation, preparation, dispensation, administration, therapeutic monitoring, and disposal of UFH in a tertiary care, freestanding pediatric hospital. The FMEA was conducted in a stepwise fashion. First, frontline staff mapped the different steps within the UFH use process. Next, key stakeholders identified potential failures of each process step. Finally, using c

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Shi, Jun Li, Hong Wei Qu, Ya Jun Wang, Yan Qiu Liu, Ke Xin Wang, and Jia Lin Li. "Application of Improved Failure Modes and Effects Analysis in Product Reliability Analysis." Advanced Materials Research 926-930 (May 2014): 3438–41. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3438.

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On the analysis of the disadvantage of traditional Failure Mode and Effect Analysis (FMEA), an improved FMEA based on fuzzy set theory and Analytical Hierarchy Process (AHP) is proposed. In this method, the fuzzy language set and the fuzzy number of Severity (S), Occurrence (O) and Detection (D) are firstly set up, then failure modes are evaluated, and finally the weights of S, O and D are determined by AHP. So, risk priorities of the failure modes can be determined by calculating the modified Risk Priority Number (RPN). Improved FMEA could provide a method for the company to evaluate the reli

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Zhu, Jianghong, Bin Shuai, Rui Wang, and Kwai-Sang Chin. "Risk Assessment for Failure Mode and Effects Analysis Using the Bonferroni Mean and TODIM Method." Mathematics 7, no. 6 (2019): 536. http://dx.doi.org/10.3390/math7060536.

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As a safety and reliability analysis technique, failure mode and effects analysis (FMEA) has been used extensively in several industries for the identification and elimination of known and potential failures. However, some shortcomings associated with the FMEA method have limited its applicability. This study aims at presenting a comprehensive FMEA model that could efficiently handle the preference interdependence and psychological behavior of experts in the process of failure modes ranking. In this model, a linguistic variable expressed by the interval-valued Pythagorean fuzzy number (IVPFN)

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F.H.P.A, Dattu, Syed Shazali S.T, Tanjong S.J, Abdullah Abdullah, and Abdul Rani Achmed. "Application of Failure Mode and Effects Analysis (FMEA) to Improve Medical Device Reliability." Welcome to the International Journal Multidisciplinary Business Management 12, no. 6 (2024): 24–30. https://doi.org/10.56805/ijmbm.2024.12.6.111.

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Dong, Yu Liang, Ye Su, and Cheng Bing He. "Wind Turbine Risk Assessment Using Modified Failure Mode and Effects Analysis." Applied Mechanics and Materials 385-386 (August 2013): 1141–44. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.1141.

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Aiming at the problem that the failure history data available from wind turbine are scarce and often accompanied with a high degree of uncertainty, the risk assessment using traditional failure mode and effects anaysis (FMEA) may not be well-suited. A wind turbine risk assessment method based on modified FMEA is proposed. The method introduces grey theory into traditional FMEA and use the degree of relation to rank risk level. The method is then used to assess the risk of a 1.5MW wind turbine. It is proved that this method can rank the risks of main failure modes.The assessment results can be

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Wibowo, Tiur Lestari, Arfita Yuana Dewi, Erhaneli Erhaneli, and Andi Syofian. "Analisa Keandalan Jaringan Distribusi Menggunakan Metode Section Technique dan Failure Mode Effect Analysis." Jurnal Multidisiplin Teknologi dan Arsitektur 3, no. 1 (2025): 10–22. https://doi.org/10.57235/motekar.v3i1.5767.

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Berdasarkan data gangguan PT. PLN (Persero) ULP Sabang Januari - Desember 2024 gangguan paling sering terjadi pada penyulang Balohan. Mengacu pada SPLN 68-2 : 1986 indeks keandalan SAIDI yang diizinkan sekitar 21,09 Jam/Pelanggan/Tahun, dan indeks keandalan SAIFI yang diizinkan adalah 3,2 Kali/Perpelanggan/Tahun. Tujuan penelitian ini yaitu untuk meningkatkan keandalan sistem distribusi 20 kV menggunakan metode Section Technique dan Failure Mode Effects Analysis (FMEA). Setelah dilakukan perhitungan metode section technique didapatkan indeks SAIDI sebesar 8,728083 Jam/Pelanggan/Tahun dan SAIFI

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Ivančan, Jelena, Dragutin Lisjak, Duško Pavletić, and Davor Kolar. "Improvement of Failure Mode and Effects Analysis Using Fuzzy and Adaptive Neuro-Fuzzy Inference System." Machines 11, no. 7 (2023): 739. http://dx.doi.org/10.3390/machines11070739.

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The reliable operation of a process plant is critical to the safety, performance, and profitability of a business. Failure Mode and Effects Analysis (FMEA) is a process of reviewing systems, subsystems, and equipment that identify potential failure modes, their root causes, and consequences. FMEA is also a risk assessment tool that has been used successfully in a wide range of process industries as an integral part of reliability-centered maintenance, safety management, and continuous improvement. The method has indeed been criticized, especially in the area of system assessment, but engineers

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Mubarok, Khoirul, Rudi Kurniawan, and Iis Riyana. "Evaluasi Kecacatan Produk Air Minum Dalam Kemasan (AMDK) 200 mL Menggunakan Metode FMEA (Failure Mode Effect Analysis)." Jurnal Teknik Industri Terintegrasi 8, no. 3 (2025): 2269–75. https://doi.org/10.31004/jutin.v8i2.44730.

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PT. DALWA ANUGRAHHASANIAH, a company that produces Packaged Drinking Water (AMDK) using ozone technology, this company also produces various sizes of glasses, bottles, and uses two types of raw materials - mineral water and demineralized water. This study aims to ensure that the AMDK production process does not experience defects. In an effort to reduce product defects, the Failure Mode and Effect Analysis (FMEA) method is used. FMEA is a proactive risk management method used to identify potential failures in a system, design, process, or service before it reaches the consumer. The goal is to

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Zheng, Haixia, and Yongchuan Tang. "Deng Entropy Weighted Risk Priority Number Model for Failure Mode and Effects Analysis." Entropy 22, no. 3 (2020): 280. http://dx.doi.org/10.3390/e22030280.

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Failure mode and effects analysis (FMEA), as a commonly used risk management method, has been extensively applied to the engineering domain. A vital parameter in FMEA is the risk priority number (RPN), which is the product of occurrence (O), severity (S), and detection (D) of a failure mode. To deal with the uncertainty in the assessments given by domain experts, a novel Deng entropy weighted risk priority number (DEWRPN) for FMEA is proposed in the framework of Dempster–Shafer evidence theory (DST). DEWRPN takes into consideration the relative importance in both risk factors and FMEA experts.

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Mohammed, Hamed Ahmed Soliman. "Analyzing Failure to Prevent Problems." Industrial Management 56, no. 5 (2014): 10. https://doi.org/10.6084/m9.figshare.9108707.

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Failure mode and effects analysis (FMEA) was initiated by the aerospace industry in the 1960s to improve the reliability of systems. It is a part of total quality management programs and should be used to prevent potential failures that could affect safety, production, cost or customer satisfaction. FMEA can be used during the design, service or manufacturing processes to minimize the risk of failure, improving the customer’s confidence while also reducing costs. Complete paper is here: http://www.iienet2.org/details.aspx?id=37883

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Bhagat, Mr Suraj D., Mr Hrithik N. Bichakule, Mr Aniket B. Mali, Mr Yash A. Patil, Ms Anuradha S. Waghmare, and Prof Ufaq U. Buch. "Implementing Failure Mode & Effect Analysis(FMEA) on Framework Structure." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 4549–56. http://dx.doi.org/10.22214/ijraset.2024.62712.

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Abstract: The Failure modes and effects analysis (FMEA) is one of the most practical design tools implemented in the product design to analyze the possible failures and to improve the design. The use of FMEA is diversified, and different approaches are proposed by various organizations and researchers from one application to another. The question is how to use the features of FMEA along with the design process. This research focuses on different types of FMEA in the design process, which is considered as the mapping between customer requirements, design components, and product functions. These

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Liu, Hu-Chen, Jian-Xin You, Xue-Feng Ding, and Qiang Su. "Improving risk evaluation in FMEA with a hybrid multiple criteria decision making method." International Journal of Quality & Reliability Management 32, no. 7 (2015): 763–82. http://dx.doi.org/10.1108/ijqrm-10-2013-0169.

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Purpose – The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes. Design/methodology/approach – A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map a

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Shebl, Nada, Bryony Franklin, Nick Barber, Susan Burnett, and Anam Parand. "Failure Mode and Effects Analysis: Views of Hospital Staff in the UK." Journal of Health Services Research & Policy 17, no. 1 (2012): 37–43. http://dx.doi.org/10.1258/jhsrp.2011.011031.

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Objective To explore health care professionals' experiences and perceptions of Failure Mode and Effects Analysis (FMEA), a team-based, prospective risk analysis technique. Methods Semi-structured interviews were conducted with 21 operational leads (20 pharmacists, one nurse) in medicines management teams of hospitals participating in a national quality improvement programme. Interviews were transcribed, coded and emergent themes identified using framework analysis. Results Themes identified included perceptions and experiences of participants with FMEA, validity and reliability issues, and FME

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Belu, Nadia, Daniel Constantin Anghel, and Nicoleta Rachieru. "Failure Mode and Effects Analysis on Control Equipment Using Fuzzy Theory." Advanced Materials Research 837 (November 2013): 16–21. http://dx.doi.org/10.4028/www.scientific.net/amr.837.16.

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Failure Mode and Effects Analysis is a methodology to evaluate a system, design, process, machine or service for possible ways in which failures (problems, errors, risks and concerns) can occur and it has been used in a wide range of industries. Traditional method uses a Risk Priority Number to evaluate the risk level of a component or process. This is obtained by finding the multiplication of three factors, which are the severity of the failure (S), the probability/occurrence of the failure (O), and the probability of not detecting the failure (D). There are significant efforts which have bee

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Duncan, James R., Daniel Harwood, Bruno Maranhao, Ellen Wertenberger, Jacob Grant, and Mona Ostman. "Failure mode and effects analysis applied to central venous catheter placement." BMJ Open Quality 14, no. 1 (2025): e003173. https://doi.org/10.1136/bmjoq-2024-003173.

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Despite diligent efforts, complications continue to occur during the placement of central venous catheters (CVCs). Healthcare Failure Mode and Effect Analysis has been promoted as a process improvement tool and this review describes the strategic application of Failure Mode and Effects Analysis (FMEA) to CVC placement. The objective is to demonstrate the utility of FMEA first as a tool for identifying quality or safety issues and second for guiding mitigation efforts.

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Ünlükal, Ceren, Mine Şenel, and Bilgin Şenel. "Risk Assessment with Failure Mode and Effects Analysis and Grey Relational Analysis Method in Plastic Injection Process." ITM Web of Conferences 22 (2018): 01023. http://dx.doi.org/10.1051/itmconf/20182201023.

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This study aims to evaluate the risks that may arise during the production process in a plastic injection manufacturing enterprise with traditional Failure Mode and Effect Analysis (FMEA) and Grey Relational Analysis (GRA). Although it is a widely used analytical technique that helps to identify and reduce the risks of failure in a process, the Failure Mode and Effects Analysis (FMEA) has some drawbacks that the different risks can have the same risk priority values and the weight of risk factors is not take into consideration. This situation has been tried to be eliminated by integrating the

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Shan, Hongmei, Qiaoqiao Tong, Jing Shi, and Qian Zhang. "Risk Assessment of Express Delivery Service Failures in China: An Improved Failure Mode and Effects Analysis Approach." Journal of Theoretical and Applied Electronic Commerce Research 16, no. 6 (2021): 2490–514. http://dx.doi.org/10.3390/jtaer16060137.

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With the rapid growth of express delivery industry, service failure has become an increasingly pressing issue. However, there is a lack of research on express service failure risk assessment within the Failure Mode and Effects Analysis (FMEA) framework. To address the research gap, we propose an improved FMEA approach based on integrating the uncertainty reasoning cloud model and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The cloud model describing randomness and fuzziness in uncertainty environment is adopted to achieve the transformation between the q

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Zuber, Mujeeb Shaikh. "A Case Study on Recall of used Scopes in the Endoscopy Department by using a Failure Mode & Effect Analysis (FMEA) Proactive Risk Management." International Journal of Health Sciences and Pharmacy (IJHSP) 4, no. 1 (2020): 13–24. https://doi.org/10.5281/zenodo.3766843.

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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.

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Askari, Roohollah, Milad Shafii, Sima Rafiei, Mohammad Sadegh Abolhassani, and Elaheh Salarikhah. "Failure mode and effect analysis: improving intensive care unit risk management processes." International Journal of Health Care Quality Assurance 30, no. 3 (2017): 208–15. http://dx.doi.org/10.1108/ijhcqa-04-2016-0053.

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Purpose Failure modes and effects analysis (FMEA) is a practical tool to evaluate risks, discover failures in a proactive manner and propose corrective actions to reduce or eliminate potential risks. The purpose of this paper is to apply FMEA technique to examine the hazards associated with the process of service delivery in intensive care unit (ICU) of a tertiary hospital in Yazd, Iran. Design/methodology/approach This was a before-after study conducted between March 2013 and December 2014. By forming a FMEA team, all potential hazards associated with ICU services – their frequency and severi

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Genter, David, Stephanie Bauer, and Shamil Baldeosingh. "Concept Design Failure Modes and Effects Analysis Using System Level Assessment." INCOSE International Symposium 34, no. 1 (2024): 239–48. http://dx.doi.org/10.1002/iis2.13144.

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AbstractDesign Failure Mode and Effects Analysis (DFMEA) is a process to identify and mitigate risks of failure of a product to perform the intended function(s) for the customer. DFMEAs can be performed at all stages of design from product concept to system to component. Several issues with concept level design FMEAs have been identified by Henshall, et al in 2014: large documents, focus on components with poorly defined connections, focus on hardware rather than integrated electro‐mechanical systems. As a result of these challenges, improvements to the system‐level product concept are unlikel

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Bhangu, N. S., Rupinder Singh, and G. L. Pahuja. "Failure Mode and Effect Analysis of a Thermal Power Plant for Enhancing its Reliability." Applied Mechanics and Materials 110-116 (October 2011): 2969–75. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.2969.

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Failure Mode and Effect Analysis (FMEA) has a well deserved reputation for systematic and thorough evaluation of failures at the system, sub-system or component level in all manufacturing and processing sectors. These organizations are looking for the final product to be “safe and reliable”. FMEA helps designers to identify and eliminate/control dangerous failure modes, minimizing damage to the system and its users. This paper, as an extension to the prior research work, introduces an insight into the reasons of failure and its effects in a thermal power plant opted for the case study, based o

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Panyukov, D. I., V. N. Kozlovskii, D. V. Aidarov, and M. V. Shakurskii. "Improved Effects Assessment in Failure Mode and Effects Analysis (FMEA)." Russian Engineering Research 43, no. 8 (2023): 1023–26. http://dx.doi.org/10.3103/s1068798x23080233.

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Pramono, Elvina, Sunday Noya, and Yurida Ekawati. "Defect Analysis Using Failure Mode and Effects Analysis and Fault Tree Analysis." Jurnal Sains dan Aplikasi Keilmuan Teknik Industri (SAKTI) 4, no. 1 (2024): 17–30. http://dx.doi.org/10.33479/sakti.v4i1.88.

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Quality control is a vital aspect of product manufacturing, ensuring adherence to predefined standards and meeting consumer expectations. This study focuses on quality control within the cigarette production process, specifically in PT PID Ongkowidjojo, a prominent manufacturer located in Malang, Indonesia. Despite meticulous production processes, defects in cigarette sticks persist, leading to waste of resources, time, and potential degradation in product quality. The research employs Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) to identify, analyze, and propose solu

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Zuniawan, Akhyar. "A Systematic Literature Review of Failure Mode and Effect Analysis (FMEA) Implementation in Industries." IJIEM - Indonesian Journal of Industrial Engineering and Management 1, no. 2 (2020): 59. http://dx.doi.org/10.22441/ijiem.v1i2.9862.

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Failure mode and effects analysis (FMEA) is a risk assessment tool that mitigates potential failures in systems, processes, designs, or services and has been used in a wide range of industries. The conventional risk priority number (RPN) method has been criticized for having many shortcomings. Various risk priority models have been proposed in various literature to improve the performance of the FMEA itself. However, there has been no literature review on this topic. This study reviewed 50 FMEA papers published between 1998 and 2019 in international journals and categorized them according to v

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Földešiová, Daniela, Maroš Korenko, Martina Ferancová, and Pavol Kaplík. "Analysis of Risk Using FMEA." Advanced Materials Research 801 (September 2013): 81–85. http://dx.doi.org/10.4028/www.scientific.net/amr.801.81.

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Failure mode and effects analysis (FMEA) was performed in RIBE Slovakia, k.s. (limited partnership) in Nitra, Slovakia. Analysis was done in the process of cold forming where potential errors (failures) were identified. Subsequently, there was assigned a mark in the FMEA form expressing severity, frequency and undetectability, and a risk priority number (RPN) was calculated. If the risk priority number (RPN) is too high, corrective measures are proposed and adopted in order for the risk to be minimized or completely eliminated.

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Zhou, Deyun, Yongchuan Tang, and Wen Jiang. "A Modified Model of Failure Mode and Effects Analysis Based on Generalized Evidence Theory." Mathematical Problems in Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/4512383.

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Due to the incomplete knowledge, how to handle the uncertain risk factors in failure mode and effects analysis (FMEA) is still an open issue. This paper proposes a new generalized evidential FMEA (GEFMEA) model to handle the uncertain risk factor, which may not be included in the conventional FMEA model. In GEFMEA, not only the conventional risk factors, the occurrence, severity, and detectability of the failure mode, but also the other incomplete risk factors are taken into consideration. In addition, the relative importance among all these risk factors is well addressed in the proposed metho

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Kulcsár, Edina, Tamás Csiszér, and János Abonyi. "Pairwise comparison based failure mode and effects analysis (FMEA)." MethodsX 7 (2020): 101007. http://dx.doi.org/10.1016/j.mex.2020.101007.

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Nasim, Faria, Joseph T. Poterucha, Lisa M. Daniels, et al. "Practical Implementation of Failure Mode and Effects Analysis for Extracorporeal Membrane Oxygenation Activation." American Journal of Medical Quality 33, no. 5 (2018): 523–29. http://dx.doi.org/10.1177/1062860618754703.

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Extracorporeal membrane oxygenation (ECMO) is used to treat severe hypoxemic respiratory failure and as a rescue therapy for patients with cardiopulmonary arrest within a narrow window of time. A failure modes and effects analysis (FMEA) was conducted to analyze the clinical and operational processes leading to delays in initiating ECMO. FMEA determined these highest-risk failure modes that were contributing to process failure: (1) ECMO candidacy not determined in time, (2) no or incomplete evaluation for ECMO prior to consult or arrest, (3) ECMO team not immediately available, and (4) cannula

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Wehrli-Veit, Michel, Jeffrey B. Riley, and Jon W. Austin. "A Failure Mode Effect Analysis on Extracorporeal Circuits for Cardiopulmonary Bypass." Journal of ExtraCorporeal Technology 36, no. 4 (2004): 351–57. http://dx.doi.org/10.1051/ject/2004364351.

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Although many refinements in perfusion methodology and devices have been made, extracorporeal circulation remains a contributor to neurological complications, bleeding coagulopathies, use of blood products, as well as systemic inflammatory response. With the exposure of these adverse effects of cardiopulmonary bypass, the necessity to re-examine the safety of extracorporeal circuits is vital. A failure mode effect analysis (FMEA) is a proven proactive technique developed to evaluate system effect or equipment failure. FMEA was used to evaluate the six different types of extracorporeal circuits

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Ivančan, Jelena, and Dragutin Lisjak. "New FMEA Risks Ranking Approach Utilizing Four Fuzzy Logic Systems." Machines 9, no. 11 (2021): 292. http://dx.doi.org/10.3390/machines9110292.

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Process equipment and plant maintenance problems are complex in the oil refinery business, since effective maintenance needs to ensure the reliability and availability of the plant. Failure Mode and Effects Analysis (FMEA) is a risk assessment tool that aims to determine possible failure modes, and to reduce the ratio of unknown failure modes, by identifying business-critical systems and the risks of their failures. For the identified failure modes, FMEA determines risk mitigation action(s). The goal is to prevent failure and keep assets and plants running at peak performance by providing full

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Donţu, Andrei Ionuţ, Tudor-Marian Ulian, and Edward Rakosi. "Functional Analysis of a New Concept of WIM Sensor by Using Failure Mode and Effects Analysis (F.M.E.A.)." Bulletin of the Polytechnic Institute of Iași. Machine constructions Section 67, no. 1 (2021): 51–58. http://dx.doi.org/10.2478/bipcm-2021-0006.

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Abstract The overloading vehicle become an important problem for Europe Union, protecting the environment and increase the traffic safety. WIM or weigh-in-motion systems can monitor the traffic, determine the volume and type of traffic and detect the overload vehicles which are illegal. This paper discusses about applying the Failure Mode and Effect Analysis method for developing a new concept of WIM sensor, designed in PhD thesis from “Gheorghe Asachi” Technical University of Iaşi. FMEA method or also called potential failure modes and effects analysis is a step-by-step approach for determine

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TU, PHAM VAN. "APPLICATION OF THE FUZZY ANALYTIC HIERARCHY PROCESS TO THE FAILURE MODE AND EFFECTS ANALYSIS." Computational Nanotechnology 8, no. 2 (2021): 29–36. http://dx.doi.org/10.33693/2313-223x-2021-8-2-29-36.

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FMEA - is a technique used to study potential failures of various products. The probability of occurrence (O), the likelihood of severity (S) and the probability of detecting defects (D) can be used as an indicator of the priority risk number (PRN). Comparison of various methods for determining the priorities of failure modes in the calculated FMEA analysis is carried out. The value of the fuzzy PRN and fuzzy analytic hierarchy process (AHP) is proposed for determining the weights of risk factors. A method is proposed to eliminate some of the disadvantages of the traditional approach. As a res

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Hendarti, Devina Rosa. "PERANCANGAN SISTEM PERAWATAN PULVERIZER MODEL MVM31F MENGGUNAKAN METODE FAILURE MODE AND EFFECT ANALYSIS (FMEA) DI PT. XYZ." Jurnal Permadi : Perancangan, Manufaktur, Material dan Energi 6, no. 03 (2024): 243–53. http://dx.doi.org/10.52005/permadi.v6i03.162.

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The continuous increase in population growth leads to a rising demand for electrical energy. PT. XYZ as a supplier of electrical energy, relies heavily on the reliability of its components to meet this demand. The frequency of failures in pulverizer machines is one of the factors that reduce production capacity. This study uses the FMEA method combined with LTA to determine the failure consequences caused by failure modes, resulting in appropriate maintenance actions for critical components. From the FMEA analysis, 10 failure modes were identified along with their causes and effects if failure

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Pires, Ana, and Paula Sobral. "Application of failure mode and effects analysis to reduce microplastic emissions." Waste Management & Research: The Journal for a Sustainable Circular Economy 39, no. 5 (2021): 744–53. http://dx.doi.org/10.1177/0734242x211003133.

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A complete understanding of the occurrence of microplastics and the methods to eliminate their sources is an urgent necessity to minimize the pollution caused by microplastics. The use of plastics in any form releases microplastics to the environment. Existing policy instruments are insufficient to address microplastics pollution and regulatory measures have focussed only on the microbeads and single-use plastics. Fees on the use of plastic products may possibly reduce their usage, but effective management of plastic products at their end-of-life is lacking. Therefore, in this study, the micro

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Kaliaperumal, Muthukrishnan, Milindar S. Dharanendrakumar, Santosh Prasanna, et al. "Cause and Mitigation of Lithium-Ion Battery Failure—A Review." Materials 14, no. 19 (2021): 5676. http://dx.doi.org/10.3390/ma14195676.

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Lithium-ion batteries (LiBs) are seen as a viable option to meet the rising demand for energy storage. To meet this requirement, substantial research is being accomplished in battery materials as well as operational safety. LiBs are delicate and may fail if not handled properly. The failure modes and mechanisms for any system can be derived using different methodologies like failure mode effects analysis (FMEA) and failure mode methods effects analysis (FMMEA). FMMEA is used in this paper as it helps to identify the reliability of a system at the component level focusing on the physics causing

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Bonato, Jasminka, Martina Badurina, and Julijan Dobrinić. "Parameters Assessment of the FMEA Method by Means of Fuzzy Logic." Journal of Maritime & Transportation Science 2, Special edition 2 (2018): 123–32. http://dx.doi.org/10.18048/2018-00.123.

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The paper aims at presenting the FMEA method based on the fuzzy technique, representing a new approach to the failure analysis and its effects on the observed system. The FMEA (Failure Mode and Effect Analysis) method has assigned the risks a coefficient i.e. a numerical indicator that very clearly defines the degree of risk. The risk is calculated as a mathematical function of RPN which depends on the effects S, probability O that some case will lead to a failure and to a probability that a failure D can not be detected before its effects are realized. RPN = S O D. The FMEA method, based on t

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Samjun, Aysha, Kasumawati Lias, Mohd. Zulhilmi Firdaus Rosli, Hazrul Mohamed Basri, Chai Chee She, and Kuryati Kipli. "Fuzzy adaptive resonance theory failure mode effect analysis non-healthcare setting for infectious disease: review." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 1 (2024): 236–47. https://doi.org/10.11591/ijeecs.v33.i1.pp236-247.

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Fuzzy adaptive resonance theory (ART) is an ART network that is developed as one of the alternative methods to evaluate risk priority number (RPN) in failure mode and effect analysis (FMEA). Not only is FMEA are common technique as an analysis tool in industrial sectors, but also, especially during the global emergency COVID-19 pandemic hits, FMEA is used in prevention and mitigation measures. Many alternative methods have been proposed. However, not many investigations use clustering models such as Fuzzy ART in FMEA. This paper aims to provide a comprehensive review and then propose a model f

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Cebeci, Ufuk, Ugur Simsir, and Onur Dogan. "Risk Analysis of Five-Axis CNC Water Jet Machining Using Fuzzy Risk Priority Numbers." Symmetry 17, no. 7 (2025): 1086. https://doi.org/10.3390/sym17071086.

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The reliability and safety of five-axis CNC abrasive water jet machining are critical for many industries. This study employs Failure Mode and Effects Analysis (FMEA) to identify and mitigate potential failures in this machining system. Traditional FMEA, which relies on crisp numerical values, often struggles with handling uncertainty in risk assessment. To address this limitation, this paper introduces an Interval-Valued Spherical Fuzzy FMEA (IVSF-FMEA) approach, which enhances risk evaluation by incorporating membership, non-membership, and hesitancy degrees. The IVSF-FMEA method leverages t

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