Failure Mode and Effect Analysis for a military nose landing gear project

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 corrective actions, which are applied in the stage of conceptual and detailed design of the product. All approaches to FMEA methods in the scientific literature converge to achieve three goals, namely: the ability to predict the type of failure that may occur, the ability to predict the effects of the failure on system operation, and the establishment of the steps to prevent failure and its effects on the system operation. The FMEA for the project of a nose landing gear analyzes the failure modes of the product and their effects in operation, as a consequence of project deficiencies and identifies or confirms critical functions. To apply the FMEA method to the project of the nose landing gear of a military training aircraft, the following steps need to be accomplished: product description and identification of components; identification of functions; identification of potential ways of failure; estimating the frequency of causes of failure; appreciation of the severity of effects; assessment of difficulties in detecting defects; calculation of the Risk Priority Number (RPN); establishing the measures and corrective actions for the analyzed project.

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

SAMRIDDHI A Journal of Physical Sciences Engineering and Technology ◽

10.18090/samriddhi.v8i2.7139 ◽

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.

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

Jurnal Manajemen Kesehatan Indonesia ◽

10.14710/jmki.8.2.2020.105-113 ◽

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.

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Analisa defect produk sheet area corrugator 301 menggunakan metode SPC dan FMEA di PT Indah Kiat

Operations Excellence Journal of Applied Industrial Engineering ◽

10.22441/oe.2020.v12.i3.006 ◽

2020 ◽

Vol 12 (3) ◽

pp. 332

Author(s):

Evan Mandala Putra ◽

Sri Mukti Wirawati ◽

Pugy Gautama

Keyword(s):

Process Control ◽

Production Process ◽

Statistical Process Control ◽

Failure Mode ◽

Failure Modes ◽

Uneven Surface ◽

Statistical Process ◽

Effect Analysis ◽

Product Defect ◽

Fmea Method

This study aims to analyze defects in the sheet production process in the 301 Corrugator area by analyzing the total number of sheets produced and the number of sheets that have been damaged over a certain period of time using the Statistical Process Control (SPC) method and Failure Modes and Effect Analysis (FMEA). Based on the research results, there are 6 defects, namely untidy cuts, wrinkled sheets, uneven surface, curved sheets, uneven sides, loose sheet layers. The most dominant defect is uneven surface, which is 185.141 Kg or 60%. Based on the value of the RPN table, the product defect that has the highest value is the loose sheet layer with an RPN value of 245 from the calculation stage of the RPN value, a suggestion is made to reduce defects resulting from the loose sheet layer. From the stage of making improvements, the company should prioritize and focus on the types of disabilities and types of disabilities that have the highest RPN ranking when using the Failure Mode and Effect Analysis (FMEA) method.

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

International Journal of Health Care Quality Assurance ◽

10.1108/ijhcqa-09-2015-0113 ◽

2017 ◽

Vol 30 (2) ◽

pp. 175-186 ◽

Cited By ~ 15

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.

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Risk identification of a hospital laboratory pre-analytics through failure mode and effect analysis

Asian Journal of Medical Sciences ◽

10.3126/ajms.v12i4.33380 ◽

2021 ◽

Vol 12 (4) ◽

pp. 31-38

Author(s):

Debdatta Das ◽

Krishna Pal ◽

Sudip Roy ◽

Moushumi Lodh

Keyword(s):

Patient Safety ◽

Failure Mode ◽

Laboratory Testing ◽

Failure Modes ◽

Risk Identification ◽

Post Intervention ◽

Effect Analysis ◽

Laboratory Errors ◽

Corrective Actions ◽

Analytical Phase

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

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An Improving failure Mode and Effect Analysis Method for Pallet Exchange Rack Risk Analysis

10.21203/rs.3.rs-330920/v1 ◽

2021 ◽

Author(s):

Chuanxi Jin ◽

Yan Ran ◽

Genbao Zhang

Keyword(s):

Risk Factors ◽

Failure Mode ◽

Evaluation Method ◽

Failure Modes ◽

Programming Model ◽

Distance Measures ◽

Analysis Method ◽

Effect Analysis ◽

Fmea Method ◽

Picture Fuzzy Sets

Abstract In order to enhance quality and reliability of mechanical and electrical products, the methods of taking corresponding corrective measures to eliminate or alleviate product failure in advance have been widely concerned. Failure mode and effects analysis (FMEA) is a typical prevention reliability analysis method. However, there are some drawbacks in traditional FMEA method. To overcome these drawbacks, we propose a hybrid risk evaluation method, which combines picture fuzzy sets (PFSs), the PF-linear programming model (PF-LPM) method and the PF-weighted aggregated sum product assessment (PF-WASPAS) method. We adopt PFSs to evaluate risks of products. In order to overcome drawback of the traditional distance between PFSs, some new distance measures between PFSs based on the Dice similarity and the Jaccard similarity are proposed by us. The PF-LPM method which considers the subjective weights of risk factors and calculates synthetical deviation with the Dice similarity-based distance is utilized to calculate the weights of risk factors. Moreover, the PFWA operator and the PFWG operator are used by us to fuse experts’ evaluation information. Then, the PF-WASPAS method is utilized to rank failure modes. Finally, an illustrative example with respect to pallet exchange rack is introduced, and the rationality, effectiveness and applicability of the proposed method are verified by a discussion and comparison.

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Failure Mode and Effect Analysis for Cyber-Physical Systems

Future Internet ◽

10.3390/fi12110205 ◽

2020 ◽

Vol 12 (11) ◽

pp. 205

Author(s):

João Oliveira ◽

Gonçalo Carvalho ◽

Bruno Cabral ◽

Jorge Bernardino

Keyword(s):

Failure Mode ◽

Cyber Security ◽

Failure Modes ◽

Data Transfer ◽

Cyber Physical Systems ◽

Critical Infrastructures ◽

Effect Analysis ◽

Physical Systems ◽

Novel Approach ◽

Fmea Method

Cyber-Physical Systems (CPS) are a prominent component of the modern digital transformation, which combines the dynamics of the physical processes with those of software and networks. Critical infrastructures have built-in CPS, and assessing its risk is crucial to avoid significant losses, both economic and social. As CPS are increasingly attached to the world’s main industries, these systems’ criticality depends not only on software efficiency and availability but also on cyber-security awareness. Given this, and because Failure Mode and Effect Analysis (FMEA) is one of the most effective methods to assess critical infrastructures’ risk, in this paper, we show how this method performs in the analysis of CPS threats, also exposing the main drawbacks concerning CPS risk assessment. We first propose a risk prevention analysis to the Communications-Based Train Control (CBTC) system, which involves exploiting cyber vulnerabilities, and we introduce a novel approach to the failure modes’ Risk Priority Number (RPN) estimation. We also propose how to adapt the FMEA method to the requirement of CPS risk evaluation. We applied the proposed procedure to the CBTC system use case since it is a CPS with a substantial cyber component and network data transfer.

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Pendekatan Fuzzy FMEA dalam Analisis Faktor Risiko Kecelakaan Kerja

Jurnal Rekayasa Sistem Industri ◽

10.26593/jrsi.v6i1.2425.29-38 ◽

2017 ◽

Vol 6 (1) ◽

pp. 29

Author(s):

Ronald Sukwadi ◽

Frederikus Wenehenubun ◽

Tarsina Wati Wenehenubun

Keyword(s):

Risk Factors ◽

Fuzzy Logic ◽

Risk Factor ◽

Failure Mode ◽

Failure Modes ◽

Effect Analysis ◽

Fuzzy Fmea ◽

Work Accident ◽

Work Accidents ◽

Fmea Method

This study aims to identify and analyze the risk factors of work accidents. Failure Mode and Effect Analysis (FMEA) and Fuzzy Logic approach are applied. The information obtained from the workers is expressed using fuzzy linguistics terms, and a FMEA method is proposed to determine the risk priority of failure modes. The results indicate that injuries caused when struck by an object are the highest risk factor of work accident (FRPN = 886). Some work improvements are suggested to reduce or eliminate the work risks.Keywords: Risk factors, work accident, FMEA, Fuzzy

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FMEA method in operational reliability of forest harvesters

Open Engineering ◽

10.1515/eng-2021-0003 ◽

2020 ◽

Vol 11 (1) ◽

pp. 29-38

Author(s):

Ján Kováč ◽

Pavol Ťavoda ◽

Jozef Krilek ◽

Pavol Harvánek

Keyword(s):

Failure Mode ◽

Working Conditions ◽

Operational Reliability ◽

Human Potential ◽

Information Analysis ◽

Effect Analysis ◽

Operational Conditions ◽

Its Analysis ◽

Fmea Method ◽

Operational Data

AbstractThe article deals with the research of operational reliability of forest felling machines by FMEA method (Failure Mode and Effect Analysis). It describes collection of operational data and its analysis. It explains the procedure of realization for the method FMEA in the organization. Harvesters John Deere 1070D in the Company Lesy SR B. Bystrica were chosen for this research. The research was held in real operational conditions. Application of the FMEA method allows flexibility in case of unexpected situations and optimization of human potential abilities. FMEA tool is a tool preventing outages operational reliability and preventive tool for ensuring the maintenance of facilities. The method of information analysis mentioned below is simple ale precise enough for implementation in real working conditions.

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Failure mode and effect analysis (FMEA) to improve collaborative project-based learning: Case study of a Study and Research Path in mechanical engineering

International Journal of Mechanical Engineering Education ◽

10.1177/0306419021999046 ◽

2021 ◽

pp. 030641902199904

Author(s):

Elena Bartolomé ◽

Paula Benítez

Keyword(s):

Active Learning ◽

Failure Mode ◽

Mechanical Engineering ◽

Failure Modes ◽

Collaborative Study ◽

Project Based Learning ◽

Educational Process ◽

Effect Analysis ◽

Questions And Answers

Failure Mode and Effect Analysis (FMEA) is a powerful quality tool, widely used in industry, for the identification of failure modes, their effects and causes. In this work, we investigated the utility of FMEA in the education field to improve active learning processes. In our case study, the FMEA principles were adapted to assess the risk of failures in a Mechanical Engineering course on “Theory of Machines and Mechanisms” conducted through a project-based, collaborative “Study and Research Path (SRP)” methodology. The SRP is an active learning instruction format which is initiated by a generating question that leads to a sequence of derived questions and answers, and combines moments of study and inquiry. By applying the FMEA, the teaching team was able to identify the most critical failures of the process, and implement corrective actions to improve the SRP in the subsequent year. Thus, our work shows that FMEA represents a simple tool of risk assesment which can serve to identify criticality in educational process, and improve the quality of active learning.

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