Priority risk mapping for halal meat production using FMEA method in medium-scale chicken slaughterhouse

Abstract: This study evaluates the cause and effect of financing problems on Baitul Mal wa Tamwil (BMT) during COVID-19 and analyzes the strategy taken by BMT to handle financing problems. This study is qualitative research. The primary and secondary data were obtained from observations, interviews, and documentation. The informants of the study are top management and members of BMT Al Hidayah Kotaraja Lombok Timur. The data are analyzed using the FMEA (Failure Mode and Effect Analysis) approach. The FMEA method is a systematic method used to identify and prevent problems in a company's product or business process. All process is calculated in a score, namely Risk Priority Number (RPN), and shown in the Pareto diagram. Financing problems are categorized as substandard, doubtful, and bad financing. The causes of financing problems are, among others, the employee’s lack of ability to assess the personality of the prospective debtors in fulfilling their installments, and natural disasters (the COVID-19 pandemic) that may affect someone’s financial ability. Financing problems have an impact on the emergence of financing risk. BMT Al Hidayah Kotaraja is also directly impacted by the inefficient money flow because monthly profit sharing still needs to be distributed to the members. The main factor causing this problem is staff members' inability to evaluate potential debtors. Additionally, the company's approach to these financing problems has not been working. The management, in that case, focused on the debtors instead of their employee’s capability. In that circumstance, the management ought to focus on improving the capacity of their staff to evaluate potential members. According to this study's findings, the FMEA is applicable in resolving finance issues in BMT. Originality/Value: The research related to risk management in BMT, especially NPF caused by the COVID-19 pandemic, using the FMEA (Failure Mode and Effect Analysis) method. FMEA is a systematic method used to identify and prevent problems with a company's products or business processes from occurring. FMEA is used to examine risk management in banking and provides convenience to the management in making decisions for planning, maintenance, and development purposes. The FMEA method in this study identifies and prevents problems in BMT.

Abstract: This study evaluates the cause and effect of financing problems on Baitul Mal wa Tamwil (BMT) during COVID-19 and analyzes the strategy taken by BMT to handle financing problems. This study is qualitative research. The primary and secondary data were obtained from observations, interviews, and documentation. The informants of the study are top management and members of BMT Al Hidayah Kotaraja Lombok Timur. The data are analyzed using the FMEA (Failure Mode and Effect Analysis) approach. The FMEA method is a systematic method used to identify and prevent problems in a company's product or business process. All process is calculated in a score, namely Risk Priority Number (RPN), and shown in the Pareto diagram. Financing problems are categorized as substandard, doubtful, and bad financing. The causes of financing problems are, among others, the employee’s lack of ability to assess the personality of the prospective debtors in fulfilling their installments, and natural disasters (the COVID-19 pandemic) that may affect someone’s financial ability. Financing problems have an impact on the emergence of financing risk. BMT Al Hidayah Kotaraja is also directly impacted by the inefficient money flow because monthly profit sharing still needs to be distributed to the members. The main factor causing this problem is staff members' inability to evaluate potential debtors. Additionally, the company's approach to these financing problems has not been working. The management, in that case, focused on the debtors instead of their employee’s capability. In that circumstance, the management ought to focus on improving the capacity of their staff to evaluate potential members. According to this study's findings, the FMEA is applicable in resolving finance issues in BMT. Originality/Value: The research related to risk management in BMT, especially NPF caused by the COVID-19 pandemic, using the FMEA (Failure Mode and Effect Analysis) method. FMEA is a systematic method used to identify and prevent problems with a company's products or business processes from occurring. FMEA is used to examine risk management in banking and provides convenience to the management in making decisions for planning, maintenance, and development purposes. The FMEA method in this study identifies and prevents problems in BMT.

Overview of Failure Mode and Effects Analysis (FMEA): A Patient Safety Tool.

Background and Objectives: Risk management is considered an integral part of laboratory medicine to assure laboratory quality and patient safety. However, the concept of risk management is philosophical, so actually performing risk management in a clinical laboratory can be challenging. Therefore, we would like to develop a sustainable, practical system for continuous total laboratory risk management. Materials and Methods: This study was composed of two phases: the development phase in 2019 and the application phase in 2020. A concept flow diagram for the computerized risk registry and management tool (RRMT) was designed using the failure mode and effects analysis (FMEA) and the failure reporting, analysis, and corrective action system (FRACAS) methods. The failure stage was divided into six according to the testing sequence. We applied laboratory errors to this system over one year in 2020. The risk priority number (RPN) score was calculated by multiplying the severity of the failure mode, frequency (or probability) of occurrence, and detection difficulty. Results: 103 cases were reported to RRMT during one year. Among them, 32 cases (31.1%) were summarized using the FMEA method, and the remaining 71 cases (68.9%) were evaluated using the FRACAS method. There was no failure in the patient registration phase. Chemistry units accounted for the highest proportion of failure with 18 cases (17.5%), while urine test units accounted for the lowest portion of failure with two cases (1.9%). Conclusion: We developed and applied a practical computerized risk-management tool based on FMEA and FRACAS methods for the entire testing process. RRMT was useful to detect, evaluate, and report failures. This system might be a great example of a risk management system optimized for clinical laboratories.

PT. Makassar Tene is one of the manufacturing industries that produce refined sugar from raw sugar as basic materials. Most of the refined sugar production process has been carried out automatically, but it still requires regular supervision and monitoring from the operator to ensure the smoothness and accuracy of the sugar processing steps in reducing the number of defect products significantly. Failure Mode and Effect Analysis (FMEA) is a method to identify product failures based on potential causes. FMEA is used to determine the value of Risk Priority Number (RPN), then further identified as the main focus in determining the root of the potential cause using the Fault Tree Analysis (FTA). The application of FTA can provide suggestions for improvements and controls in order to help companies reduce the risk of production failure. Based on the results of the research using FMEA method, it can be seen that the process stage with the greatest risk of failure lies in the stages of sugar evaporation/crystallization and the packaging stage in the packaging bin. The next step is to identify the type of problem at each stage of the process selected using Pareto diagram so that the results show that the evaporation/crystallization stage CV deviation often happened which can produce sugar dust, while at the packaging stage the problem that often occurs is metal detection, torn sack, and sweeping sugar. Then proceed with the use of the FTA method to identify the underlying causes of each failure that arises at the chosen process stage, and the results show that most of the failures that arise are caused by operator negligence, the operation process is still done manually, and the design of operating equipment is less optimal.

Failure Mode and Effects Analysis (FMEA) can be used as a structured method to prioritize all possible vulnerable areas (failure modes) for design review of safety-critical supervisory control and data acquisition (SCADA) Systems. However, the traditional RPN based FMEA has some inherent limitations. Thus the main purpose of this study was to propose a new pattern recognition based FMEA to evaluate, prioritize and correct a SCADA system’s failure modes. In the new FMEA method, a vague set based Risk Priority Number (RPN) is proposed to measure safety risk status of failure modes and a rule based pattern recognition method is also proposed to prioritize action priorities of failure modes. Finally, a case study was conducted to demonstrate that the proposed new FMEA method is not only capable of addressing its inherent problems but also is effective and efficient to be used as the basis for continuous improvement of a safety-critical SCADA system.

In order to reduce the maintenance cost, the design of complex electronic devices need to consider Failure Modes and Effects Analysis (FMEA). Traditional FMEA method in face of complex devices is usually lack of a formal specification in analysis process of failure modes and causes, which is easy to cause confusion and chaos; the results are prone to duplication or omission; the support for design phase is also weak. Above all, this paper presents a FMEA method for electronic devices based on annotating functional roles. Firstly, the functional roles and their corresponding failure modes are introduced; secondly, possible failures, that each functional role may experience, are analyzed and a formalized analysis method based on stress event is proposed; finally, analysis process of the FMEA method is illustrated with avionics system battery as an example. The method presented in this paper can effectively improve the efficiency and accuracy of failure analysis for electronic devices, and improve the ability of FMEA to support the design phase.

An asymmetric cost consensus based failure mode and effect analysis method with personalized risk attitude information

Purpose: To examine the ability of traditional Failure mode and effects analysis (FMEA) and a light version of Healthcare FMEA (HFMEA), called Scenario analysis of FMEA (SAFER) by comparing their outputs in terms of the risks identified and their severity rankings. Methods: We applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation are based on risk priority number (RPN). RPN is a product of three indices: occurrence, severity and detectability. The SAFER approach; utilized two indices-frequency and severity-which were defined by a multidisciplinary team. A criticality matrix was divided into 4 categories; very low, low, high and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. Results: Two methods were independently compared to determine if the results and rated risks were matching or not. Our results showed an agreement of 67% between FMEA and SAFER approaches for the 15 riskiest SIG-specific failure modes. The main differences between the two approaches were the distribution of the values and the failure modes (No.52, 54, 154) that have high SAFER scores do not necessarily have high FMEA RPN scores. In our results, there were additional risks identified by both methods with little correspondence. In the SAFER, when the risk score is determined, the basis of the established decision tree or the failure mode should be more investigated. Conclusion: The FMEA method takes into account the probability that an error passes without being detected. SAFER is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allow the prioritization of risks and mitigation measures, and thus is perfectly applicable to clinical parts of radiotherapy.

PT PJB UBJOM Paiton Baru as the O & M Service Manager of PLTU Paiton Baru 1 x 660 MW has approved the concepts and policies of PT PJB on the Reliability Management Program using the FMEA method along with the Failure Defense Task (FDT). However, the FMEA method that has been impelemented not yet effective. First, because first has not been aligned with existing reference books and international journals where there is no process of determining the value of Severity (S), Occurrence (O), and Detection (D), and calculation of Risk Priority Number (RPN), and the process of decreasing the risk value by using the right Failure Defense Task. Second, based on the evaluation of the results of the site visit at UBJOM Paiton Baru for Main Equipment and Sub Equipment for Seawater Desalination Systems, among 21 Sub-Systems in the Seawater Desalination System using Reverse Osmosis Technology, only 7 Sub-Systems have conducted The FMEA and FDT Workshop or 33.3% of the total Sub-Systems, and 14 Sub- Systems have not conducted FMEA and FDT Workshops or 66.6% of the total Sub-Systems. Third, based on further research on the results of the FMEA and FDT Workshop at UBJOM Paiton Baru in 5 Sub- systems namely Mechanical Accelerated Clarifier, Air Scouring Filter, Self Cleaning Filter, Ultra Filtration Device, Energy Recovery Device, that for determining Failure Mode sourced from Manual Book , PM Base, Existing Unit, and Browsing the Internet, so there is no data in identifying Failure Mode. Then FDT for interval 1Y (Annually) is an Overhaul with several types of inspections that have not been implemented / executed for Mechanical, Electrical, Control & Instrumentation Skills which include Assembly and Disassembly, Visual Inspection, repair or replacement if needed according to the results of Visual Inspection, testing, I / O Check , and calibration, so that FDT with Frequency 1Y (Annually) has not been effective. Meanwhile, based on the results of the Workshop on Failure Mode and Effect Analysis (FMEA) and FDT which has been aligned with reference books and international journals, by calculating the Risk Priority Number (RPN) on Failure Mode - Failure Mode identified and assessed Severity , Occurrence and Detection Levels for 6 Sub Systems, 14 Failure Modes have been mapped with risk categories of Major Risk, 31 Failure Modes with risk categories of Moderate Risk and 2 Failure Mode with risk categories of Minor Risk according to Ranking based on Risk Priority Number. From 47 Failure Modes that have been mapped risk categories, have been submitted for approval Proposed Maintenance Strategy as an effort in recalculating the value of Risk Priority Number (RPN), based on the results of Review and Evaluation of FMEA and Existing FDT Workshop Data Results and Analysis of Equipment Condition

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Probabilistic double hierarchy linguistic risk analysis based on failure mode and effects analysis and S-ARAS method

Failure modes and effect analysis (FMEA) is a risk prioritization technique mainly used by manufacturing and process industries. In FMEA, the impact of a particular failure mode is calculated using three risk factors. These are severity (S), occurrence (O), and detection (D). This method is suitable for failure determination in processes, designs, products, software, supply chains, etc. This paper includes a systematic review of the advancements in conventional FMEA. Initially, the drawbacks of traditional FMEA are listed to show the scope for improvement. Then the concept of assigning weight to each factor using the analytic hierarchy process (AHP) is studied. The AHP-FMEA with other risk factors is provided in the next part. The second session of this paper contains an overview of seven types of FMEA integration. They are failure mode and effect anticipatory analysis (FMEAA), fuzzy FMEA, FMEA using fuzzy logic and grey relation theory (GRT), hybrid multilevel fault tree analysis (FTA)-FMEA method, FMEA based on Dempster-Shafer Theory (DST), geometric mean FMEA based on information quality, and ambiguity measure weighted risk priority number (AMWRPN) model.

The FMEA (Failure Mode and Effects Analysis) method consists in analysis of failure modes and evaluation of their effects based on determination of cause-effect relationships for formation of possible product or process defects. Identified irregularities which occur during the production process of piston castings for internal combustion engines were ordered according to their failure rates, and using Pareto-Lorenz analysis, their per cent and cumulated shares were determined. The assessments of risk of defects occurrence and their causes were carried out in ten-point scale of integers, while taking three following criteria into account: significance of effects of the defect occurrence (LPZ), defect occurrence probability (LPW) and detectability of the defect found (LPO). A product of these quantities constituted the risk score index connected with a failure occurrence (a so-called “priority number,” LPR). Based on the observations of the piston casting process and on the knowledge of production supervisors, a set of corrective actions was developed and the FMEA was carried out again. It was shown that the proposed improvements reduce the risk of occurrence of process failures significantly, translating into a decrease in defects and irregularities during the production of piston castings for internal combustion engines.

STR Workshop is a company engaged in the automotive manufacturing sector. The production activities involve modifying motorcycle engines to enhance their performance using racing spare parts. However, during the production process, failures were encountered with the components themselves. Therefore, it is necessary to conduct research to assess the extent of damage to the engine using the FMEA (Failure Mode and Effects Analysis) method. Based on the research findings, there are four types of component failures in the engine, including broken valve springs, hollow pistons, broken valve springs, and cracked liner bores. Using the FMEA method, several factors were identified, resulting in a Severity rating of 7, Occurrence rating of 6, and Detection rating of 3, leading to a Risk Priority Number (RPN) of 126 for the piston. This indicates that the engine modification experienced failures during the assembly process.Furthermore, the measurement of motorcycle engine performance using a dynamometer showed that after modifications were made to the Vario 150 cc motorcycle—where the standard piston diameter increased from 57.3 mm to 60 mm, and the compression ratio changed from 10.6:1 to 11.3:1—the horsepower increased from 9.7 at 8500 RPM to 19.0 at 11000 RPM.Keywords: Performance, Defect, Motorcycle Engine, FMEA