scholarly journals Quality Control of the Continuous Hot Pressing Process of Medium Density Fiberboard Using Fuzzy Failure Mode and Effects Analysis

2020 ◽  
Vol 10 (13) ◽  
pp. 4627 ◽  
Author(s):  
Yunlei Lv ◽  
Yaqiu Liu ◽  
Weipeng Jing ◽  
Marcin Woźniak ◽  
Robertas Damaševičius ◽  
...  
Keyword(s):  
Failure Mode ◽  
Hot Pressing ◽  
Failure Modes ◽  
Medium Density Fiberboard ◽  
Medium Density ◽  
Hamming Code ◽  
Thickness Control ◽  
Board Thickness ◽  
Thickness Deviation ◽  
Fmea Method

In this paper, a fuzzy failure mode and effects analysis (FMEA) method is proposed by combining fault theory and a failure analysis method. The method addresses the problem of board thickness control failure and the problem of thickness deviation defect blanking, which can occur during continuous hot pressing (CHP) process, which is one of the most important processes in the production of medium-density fiberboard (MDF). The method combines the fault analysis with the Hamming code method and using the Hamming code to calculate and represent the cylinder array of the continuous hot-pressed thickness control execution unit to analyze and process the potential fixed thickness failure modes in MDF hot press production, and then summarizes the decision rules for controlling the board thickness and the level of sheet deviation. By combining the fuzzy FMEA method of the Hamming code and the logical OR operation of the experimental analysis, the method of thickness deviation and recognition control fault information for the CHP of MDF, which is proposed in this paper, permits the increase of the number of error levels, which makes optimization for controller more convenient and improves the efficiency to recognize errors.

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.

Heat Transfer Hot-Pressing Model of Medium Density Fiberboard

2014 ◽  
Vol 875-877 ◽  
pp. 1083-1086
Author(s):  
Hong Peng Li ◽  
Xing Jian Wang ◽  
Chun Rui Zhang
Keyword(s):  
Heat Transfer ◽  
Temperature Difference ◽  
Hot Pressing ◽  
Medium Density Fiberboard ◽  
Medium Density ◽  
Pressing Time ◽  
The Relationship

This by ratiocinating the theoretical formations of the pressing time of Cylindrical fiberboard and analyzing the relationship between the pressing time and Temperature difference and wood-based radius.

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

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.

Fuzzy-FMSA: Evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Carlos Alberto Murad ◽  
Arthur Henrique de Andrade Melani ◽  
Miguel Angelo de Carvalho Michalski ◽  
Adherbal Caminada Netto ◽  
Gilberto Francisco Martha de Souza ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Failure Mode ◽  
Failure Modes ◽  
Monitoring Techniques ◽  
Knowledge Based ◽  
Diagnosis And Prognosis ◽  
Kaplan Turbine ◽  
Shaft System ◽  
Fmea Method ◽  
Criticality Analysis

Abstract Failure mode and symptoms analysis (FMSA) is a relatively new and still not very much employed variation of failure modes, effects and criticality analysis (FMECA), a technique broadly used in reliability, safety, and quality engineering. While FMECA is an extension of the well-known failure mode and effects analysis (FMEA) method, primarily used when a criticality analysis is required, FMSA focuses on the symptoms produced by each considered failure mode and the selection of the most appropriate detection and monitoring techniques and strategies, maximizing the confidence level in the diagnosis and prognosis. However, in the same way as FMECA and FMEA, FMSA inherits some deficiencies, presenting somewhat biased results and uncertainties intrinsic to its development, due to its own algorithm and the dependence on knowledge-based inputs from experts. Accordingly, this article presents a fuzzy logic application as a complement to FMSA in order to mitigate such uncertainties' effects. As a practical example, the method is applied to a Kaplan turbine shaft system. The monitoring priority number (MPN) obtained through FMSA is compared to the fuzzy monitoring priority number (FMPN) resulting from fuzzy logic application, demonstrating how the proposed method improves the evaluation of detection and monitoring techniques and strategies.

A hybrid risk prioritization approach in construction projects using failure mode and effective analysis

2020 ◽  
Vol 27 (9) ◽  
pp. 2661-2686 ◽  
Author(s):  
Amirhossein Karamoozian ◽  
Desheng Wu
Keyword(s):  
Failure Mode ◽  
Construction Projects ◽  
Failure Modes ◽  
Fuzzy Decision Making ◽  
Suggested Approach ◽  
Content Type ◽  
Risk Prioritization ◽  
Fuzzy Fmea ◽  
Fmea Method ◽  
Effective Analysis

PurposeConstruction projects involve with various risks during all phases of project lifecycle. Failure mode and effective analysis (FMEA) is a useful tool for identifying and eliminating possible risk of failure modes (FMs) and improving the reliability and safety of systems in a broad range of industries. The traditional FMEA method applies risk priority number method (RPN) to calculate risk of FMs. RPN method cannot consider the direct and indirect interdependencies between the FMs and is not appropriate for complex system with numerous components. The purpose of this study is to propose an approach to consider interdependencies between FMs and also using fuzzy theory to consider uncertainties in experts' judgments.Design/methodology/approachThe proposed approach consist of three stages: the first stage of hybrid model used fuzzy FMEA method to identify the failure mode risks and derive the RPN values. The second stage applied Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) method to determine the interdependencies between the FMs which are defined through fuzzy FMEA. Then, analytic network process (ANP) is applied in the third stage to calculate the weights of FMs based on the interdependencies that are generated through FDEMATEL method. Finally, weight of FMs through fuzzy FMEA and FDEMATEL–ANP are multiplied to generate the final weights for prioritization. Afterward, a case study for a commercial building project is introduced to illustrate proficiency of model.FindingsThe results showed that the suggested approach could reveal the important FMs and specify the interdependencies between them successfully. Overall, the suggested model can be considered as an efficient hybrid FMEA approach for risk prioritization.Originality/valueThe originality of approach comes from its ability to consider interdependencies between FMs and uncertainties of experts' judgments.

scholarly journals Risk Assessment for Failure Mode and Effects Analysis Using the Bonferroni Mean and TODIM Method

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 536 ◽  
Author(s):  
Jianghong Zhu ◽  
Bin Shuai ◽  
Rui Wang ◽  
Kwai-Sang Chin
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Failure Modes ◽  
Bonferroni Mean ◽  
Psychological Behavior ◽  
Analysis Technique ◽  
Safety And Reliability ◽  
Preference Interdependence ◽  
Fmea Method ◽  
Grey Relational

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) is utilized by experts to provide preference information with regard to failure modes’ evaluation and risk factors’ weight. Then, to depict the interdependent relationships between experts’ preferences, the Bonferroni mean operator is extended to IVPFN to aggregate the experts’ preference. Subsequently, an extended TODIM approach in which the dominance degree of failure modes is calculated by grey relational analysis is utilized to determine the risk priority of failure modes. Finally, a practical example concerning the risk assessment of a nuclear reheat valve system is provided to demonstrate the effectiveness and feasibility of the presented method. In addition, a sensitivity analysis and comparison analysis are conducted, and the results show that the preference interdependence and psychological behavior of experts have an important effect on the risk priority of failure modes.

scholarly journals Risk analysis of warehouse operation in a power plant through a Modified FMEA

2018 ◽  
Vol 154 ◽  
pp. 01089
Author(s):  
Sri Indrawati ◽  
Kharina Novia Karunia Ningtyas ◽  
Alfina Budi Khoirani ◽  
Riadho Clara Shinta
Keyword(s):  
Power Plant ◽  
Risk Analysis ◽  
Needs Assessment ◽  
Failure Mode ◽  
Failure Modes ◽  
Basic Needs ◽  
Risk Priority Number ◽  
West Java ◽  
Warehouse Operation ◽  
Fmea Method

Currently, electricity becomes basic needs for human’s life sustainability. Most of activities require electricity. Some power plant are demanded to be able to fulfil above necessity by distributing electricity as it required within time. Therefore, to accommodate good performance, it needs assessment on risk analysis, specifically at the warehousing division. A risk analysis is needed for assuring a good performance warehouse. A Modified FMEA method is used to analyse the risk. This method id done by identifying sources and root causes of a problem based on the value of risk priority number (RPN). The research is conducted in an Indonesian power plant, located in West Java. There are 10 types of failure modes. The result shows that the failure mode priority is inventory discrepancies. There are no difference ranking on the most impacted failure to be prioritized using FMEA and modified FMEA method.

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

2021 ◽  
Vol 13 (4) ◽  
pp. 205-212
Author(s):  
Ilie NICOLIN ◽  
Bogdan Adrian NICOLIN
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Military Training ◽  
Landing Gear ◽  
System Operation ◽  
Effect Analysis ◽  
Equipment Failures ◽  
Corrective Actions ◽  
Fmea Method ◽  
Product Description

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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