scholarly journals Failure mode and effect analysis-based quality assurance for dynamic MLC tracking systems

2010 ◽  
Vol 37 (12) ◽  
pp. 6466-6479 ◽  
Author(s):  
Amit Sawant ◽  
Sonja Dieterich ◽  
Michelle Svatos ◽  
Paul Keall
Keyword(s):  
Quality Assurance ◽  
Failure Mode ◽  
Tracking Systems ◽  
Effect Analysis

SU-GG-J-14: Failure Mode and Effect Analysis (FMEA)-Based Quality Assurance for Dynamic MLC Tracking Systems

2010 ◽  
Vol 37 (6Part9) ◽  
pp. 3147-3148
Author(s):  
A Sawant ◽  
S Dieterich ◽  
M Svatos ◽  
P Keall
Keyword(s):  
Quality Assurance ◽  
Failure Mode ◽  
Tracking Systems ◽  
Effect Analysis

Risk analysis of cutting system under intuitionistic fuzzy environment

2020 ◽  
Vol 1 (1) ◽  
pp. 162-173
Author(s):  
Dinesh Kumar Kushwaha ◽  
◽  
Dilbagh Panchal ◽  
Anish Sachdeva ◽  
◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Thermal Power ◽  
Failure Detection ◽  
Engineering System ◽  
Effect Analysis ◽  
Intuitionistic Fuzzy ◽  
Mode Effect ◽  
Cutting System ◽  
Failure Mode Effect Analysis

Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.

scholarly journals Utility of Failure Mode and Effect Analysis to Improve Safety in Suctioning by Orotracheal Tube

2017 ◽  
Vol 32 (1) ◽  
pp. 28-37 ◽  
Author(s):  
Agustín Vázquez-Valencia ◽  
Andrés Santiago-Sáez ◽  
Bernardo Perea-Pérez ◽  
Elena Labajo-González ◽  
Maria Elena Albarrán-Juan
Keyword(s):  
Failure Mode ◽  
Effect Analysis ◽  
Orotracheal Tube

FMEA method in operational reliability of forest harvesters

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.

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

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.

Application of failure mode and effects analysis to reduce microplastic emissions

2021 ◽  
pp. 0734242X2110031
Author(s):  
Ana Pires ◽  
Paula Sobral
Keyword(s):  
Failure Mode ◽  
Quantitative Methods ◽  
Policy Instruments ◽  
Effect Analysis ◽  
Advantages And Disadvantages ◽  
Heuristic Technique ◽  
Single Use ◽  
Regulatory Measures ◽  
Plastic Products

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 microplastic–failure mode and effect analysis (MP–FMEA) methodology, which is a semi-qualitative approach capable of identifying the causes and proposing solutions for the issue of microplastics pollution, has been proposed. The innovative feature of MP–FMEA is that it has a pre-defined failure mode, that is, the release of microplastics to air, water and soil (depending on the process) or the occurrence of microplastics in the final product. Moreover, a theoretical recycling plant case study was used to demonstrate the advantages and disadvantages of this method. The results revealed that MP–FMEA is an easy and heuristic technique to understand the failure-effect-causes and solutions for reduction of microplastics and can be applied by researchers working in different domains apart from those relating to microplastics. Future studies can include the evaluation of the use of MP–FMEA methodology along with quantitative methods for effective reduction in the release of microplastics.

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