scholarly journals A New Hybrid Dynamic FMECA with Decision-Making Methodology: A Case Study in an Agri-Food Company

2021 ◽  
Author(s):  
Mario Di Nardo ◽  
Teresa Murino ◽  
Gianluca Osteria ◽  
Liberatina Carmela Santillo
Keyword(s):  
Failure Modes ◽  
Entropy Method ◽  
Objective Method ◽  
Dynamic Aspect ◽  
Manufacturing Companies ◽  
Effect Analysis ◽  
New Approach ◽  
Unknown Factor ◽  
Criticality Analysis

The Failure Mode and Effect Analysis (FMEA) is often used to improve a system's reliability. This paper proposes a new approach that aims to overcome the most critical defects of the traditional FMEA. This new methodology combines the Entropy and Bwm methodology with the EDas and System Dynamics, FMECA: The EN-B-ED Dynamic FMECA. The main innovation’s point of the proposed work is the presence of an unknown factor (Cost) in order to take into consideration the economic aspect; the evaluation of the four-factor through both an objective method (Entropy method) and a subjective method (BWM); the ranking method used (EDAS method), much more accurate than RPN; the development of a dynamic criticality analysis to take in consideration the dynamic aspect of the system. This work aims to give manufacturing companies an easy and replicable method to analyze the possible failure modes and prevent the fault.

scholarly journals Integrated RMA with FMECA analysis using a graphical inteface: case study recycling iso-butane pump (CP2K)

2020 ◽  
Vol 5 (1) ◽  
pp. 53-57
Author(s):  
El-Arkam MECHHOUD ◽  
Riad BENDIB ◽  
Youcef ZENNIR
Keyword(s):  
System Analysis ◽  
Failure Modes ◽  
Automated Analysis ◽  
Petrochemical Plant ◽  
New Approach ◽  
System Description ◽  
Automated Method ◽  
Analysis System ◽  
Criticality Analysis

The objective of our work is the implementation of a new approach for the dependability enhancement of a recycling iso-butane pump (Skikda CP2K petrochemical plant) based on automateddependability analysis system including the automation of the RMA (Reliability, Maintainability, Availability) study and FMECA (Failure Mode Effect and Criticality Analysis) method. After the system description, we present briefly the principle of the automated method. The system analysis in degraded mode is realized by using FMECA method. This automated analysis brings out the different failure modes, their causes and their consequences of each component. The result is risks minimization and reliability enhancement of the considered system.

A New Approach for Prioritization of Failure Mode in FMECA Using Encouragement Variable Weight AHP

2013 ◽  
Vol 289 ◽  
pp. 93-98 ◽  
Author(s):  
Shu Zhong Zhang ◽  
Qin Da Zeng ◽  
Gong Zhang
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Risk Level ◽  
Analytic Hierarchy ◽  
New Approach ◽  
Variable Weight ◽  
Potential Applications ◽  
Criticality Analysis ◽  
Hierarchy Process

The traditional failure mode, effect, and criticality analysis (FMECA) uses risk priority number (RPN) to evaluate the risk level of a failure mode. The RPN index is calculated by multiplication of severity, occurrence and detection factors. The most critically debated disadvantage of this approach is that various combinations of these three factors may produce an identical value of RPN. This paper reviews the drawbacks in traditional FMECA and proposes a new approach to overcome these shortcomings. The proposed approach evaluates risk of failure mode by encouragement-variable-weighted analytic hierarchy process (EVW-AHP) that can prioritize failure modes even if two or more failure modes have same RPN. An example is provided to show the potential applications of the proposed approach and the detailed computational process is presented. The results based on the case study show the proposed new methodology solves the limitations of traditional FMECA approach and is feasible.

scholarly journals A FMEA Based Method for Analyzing and Prioritizing Performance Risk at the Conceptual Stage of Performance PSS Design

2021 ◽  
Vol 1 ◽  
pp. 81-90
Author(s):  
John Bake Sakwe ◽  
Marcus Pereira Pessoa ◽  
Sipke Hoekstra
Keyword(s):  
Failure Modes ◽  
Manufacturing Companies ◽  
Performance Risk ◽  
Performance Contracts ◽  
Product Service ◽  
Optical Sorting ◽  
Fmea Method ◽  
Performance Challenges ◽  
Product Service Systems

AbstractWith the quest for enhancing competitive position, fulfilling customer and sustainability demands, increasing profitability, asset manufacturing companies are now adapting assets towards product service systems (PSS) offered through performance contracts. Despite several benefits, the shift to performance PSS exposes industrial asset manufacturers' to performance challenges and risks. Currently, PSS designers face a challenge to exhaustively identify potential failures during PSS development. Knowledge of Product failures is critical prior to the engineering of PSS. This paper proposes a failure modes and effects analysis (FMEA) method to support designers' prioritise critical failures in performance PSS development. A case study of an optical sorting machine is used to demonstrate the method's application.

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.

Fuzzy risk assessment for electro-optical target tracker

2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Linear Equations ◽  
Mode Analysis ◽  
Failure Behavior ◽  
Membership Functions ◽  
Design And Development ◽  
Effect Analysis ◽  
Content Type ◽  
Criticality Analysis

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 technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

Interval type-2 fuzzy inference-based failure mode and effect analysis model in a group decision-making setting

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
İlker Gölcük
Keyword(s):  
Failure Modes ◽  
Fuzzy Inference ◽  
Real Life ◽  
Effect Analysis ◽  
Inference System ◽  
Content Type ◽  
Proposed Model ◽  
Interval Type

PurposeThis paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.Design/methodology/approachThis paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.FindingsThe proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.Originality/valueMamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.

scholarly journals Integration of FMECA and statistical snalysis for predictive maintenance

2021 ◽  
Vol 2 (1) ◽  
pp. 33
Author(s):  
Rabia Ghani
Keyword(s):  
Production Line ◽  
Manufacturing Industry ◽  
Failure Modes ◽  
Remaining Useful Life ◽  
Predictive Maintenance ◽  
Time To Failure ◽  
Failure Data ◽  
Criticality Analysis

<p>The estimation of time-to-failure of machines is of utmost importance in the Manufacturing Industry. As the world is moving towards Industry 4.0, it is high time that we progress from the traditional methods, where we wait for a breakdown to occur, to the prognostics based methods. It is the need of the era to be aware of any incident before it occurs. This study provides application of Statistical-based Predictive maintenance. A BOPP Production line has been considered as a case study for this research. Since the inception of the line in 2013, it is evident that 60% of breakdowns are due to lack of maintenance and timely replacement of bearings. Therefore, the research is based on the application of FMECA (Failure Modes, Effects and Criticality Analysis) to determine which bearing in the production line is most prone to failure and determination of which statistical model best fits the failure data of the most critical bearing. The result provides the best distribution fit for the failure data and the fit can be utilized for further study on RUL (Remaining Useful Life) of the bearing through Bayesian Inference.</p>

scholarly journals Assessing the Technical Specifications of Predictive Maintenance: A Case Study of Centrifugal Compressor

2021 ◽  
Vol 11 (4) ◽  
pp. 1527 ◽  
Author(s):  
Helge Nordal ◽  
Idriss El-Thalji
Keyword(s):  
Centrifugal Compressor ◽  
Failure Modes ◽  
Predictive Maintenance ◽  
Event Tree ◽  
Tree Analysis ◽  
Detection Techniques ◽  
Technical Specifications ◽  
Physical Assets ◽  
Criticality Analysis

Dependability analyses in the design phase are common in IEC 60300 standards to assess the reliability, risk, maintainability, and maintenance supportability of specific physical assets. Reliability and risk assessment uses well-known methods such as failure modes, effects, and criticality analysis (FMECA), fault tree analysis (FTA), and event tree analysis (ETA)to identify critical components and failure modes based on failure rate, severity, and detectability. Monitoring technology has evolved over time, and a new method of failure mode and symptom analysis (FMSA) was introduced in ISO 13379-1 to identify the critical symptoms and descriptors of failure mechanisms. FMSA is used to estimate monitoring priority, and this helps to determine the critical monitoring specifications. However, FMSA cannot determine the effectiveness of technical specifications that are essential for predictive maintenance, such as detection techniques (capability and coverage), diagnosis (fault type, location, and severity), or prognosis (precision and predictive horizon). The paper proposes a novel predictive maintenance (PdM) assessment matrix to overcome these problems, which is tested using a case study of a centrifugal compressor and validated using empirical data provided by the case study company. The paper also demonstrates the possible enhancements introduced by Industry 4.0 technologies.

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