Risk Priority Number Research Articles

A comprehensive review on reliability and degradation of PV modules based on failure modes and effect analysis

Abstract This review paper aims to evaluate the impact of defects on the reliability and degradation of photovoltaic (PV) modules during outdoor exposure. A comprehensive analysis of existing literature was conducted to identify the primary causes of degradation and failure modes in PV modules, with a particular focus on the effect of defects. Based on a risk priority number (RPN) analysis of previous studies, dust accumulation on the PV surface (severity = 9), module shading (severity = 8) and humidity (severity = 7) were found to be the most significant causes of degradation. Furthermore, the degree of performance and degradation of PV modules were analyzed based on the identified failure mechanisms and modes. The analysis revealed that the decrease in efficiency ranged from 0.2 to 3%. The dust accumulation reduced the module efficiency by 3%, while corrosion in the module decreased efficiency by 1.9%. These findings highlight the importance of addressing specific defects to maintain optimal PV module performance in outdoor conditions. This review paper provides valuable insights into the effect of defects on the performance of PV modules, and critical defects occur during outdoor exposure to PV modules which depend on the type of PV technology and outdoor environment conditions and are able to mitigate the further performance of PV modules. The present study will help manufacturers improve the design and maintenance strategies of PV systems.

Application of FMEA and FTA techniques for assessing the occurrence of LOCA in a TRIGA MARK I Reactor

This study presents a framework merging failure mode and effect analysis (FMEA) and fault tree analysis (FTA) techniques to evaluate loss of coolant accident (LOCA) in the Brazilian Reactor TRIGA IPR-RI. At first, FMEA identified failure modes and prioritized risk management based on the risk priority number (RPN). Subsequently, FTA established logical relationships between these failure modes, revealing minimal cut sets. Results indicated that the path involving “loss of coolant from reactor tank” correlate to an externally caused leak, exhibiting a low probability and, consequently, a low RPN. On the other hand, the path involving “loss of coolant through primary circuit rupture without a pump shutdown” highlighted high RPN due to the lack of shutdown signals from the monitoring indicators. Finally, FTA unveiled that LOCA associates with a primary circuit rupture and the simultaneous failure of safety mechanisms, including ultimately human error.

Analisis Pengaruh Keselamatan dan Kesehatan Kerja Terhadap Risiko Kecelakaan Kerja Menggunakan Metode Failure Mode Effect and Analysis pada 888 Plast

This research aims to determine the effect of implementing Occupational Safety and Health (K3) on the risk of work accidents. The respondents of this research were 16 people who were warehouse and production employees. The data sources used are primary and secondary data. The analytical method used in this research is Failure Mode and Effect Analysis (FMEA) which is processed with Microsoft Excel. The research results show that there is a significant influence on the implementation of K3 because the root cause of work accidents is caused by the lack of use and application of available K3 facilities, such as shoes, air ventilation and socialization. From data processing using the Failure Mode and Effect Analysis (FMEA) method, it is known that there are 3 types of work accidents that have high RPN values, namely cuts by cutters with an RPN value of 45, exposure to scissors with an RPN value of 45, and exposure to machine heat with an RPN value of 40. There are The four main factors that influence problems are humans, management, work methods, and work environment.

PRIORITAS RESIKO KERJA PEMBUATAN KUSEN PINTU (STUDI KASUS: PD. SUMBER PUTRI REJEKI, TANGERANG)

PD Sumber Putri Rejeki is a trading company which operates in the sector of making door frames, door panels, glass windows, etc. located in the Tangerang Regency area. The process of making door frames involves various processes such as unloading wood, cutting wood, making profiles, smoothing, assembling and finishing the product, namely varnishing. Where every stage in production has a potential risk of work accidents which need to be evaluated and managed effectively. Work accidents can have a serious impact on the health and productivity of workers, as well as creating inconvenience and losses for the company. Based on these problems, the aim of this research is to determine the risk priority number (RPN), which is a risk priority number obtained from multiplying severity, occurrence and detection using the FMEA (Failure Mode Effect Analysis) method as a risk analysis tool. The conclusion of this research is that the potential dangers that exist in PD Sumber Putri Rejeki are injured hands, injured feet, shoulder injuries, cut limbs, respiratory problems and vision problems. The average potential hazard value with the highest level of risk is cutting work with an RPN value of 74, while the description of the potential hazard for all jobs is visual impairment due to material residue in contact with the eyes with an RPN value of 108.

HAZARD ANALYSIS AND RISK ASSESSMENT FOR SPINNING YARN PRODUCTION PROCESS BY INTEGRATED FTA-FMEA APPROCH

The hazard analysis and management is vital in textile industry to avoid accidents and wasting resources caused by the failures in production systems. Risk analysis is also very significant to decrease possible hazards and to avoid possible damage in manpower & production systems. In this study, an approach based on Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) is proposed to analyse the ring spinning yarn production process in a textile industry. First, the possible hazards in the production line, yarn production system, in an integrated company operating in the textile sector are analysed by FTA method. Then, FMEA is applied to ring spinning yarn production process in a textile industry to rank all possible risks corresponding to hazards in descending order with respect to both occupational health and safety. It is very important to remove all possible hazards in textile industry to decrease the number of risks related to occupational health and safety. Therefore, in total of 57 hazard root causes are determined in the yarn production department. Subsequently, the faults related to the hazard root causes are examined by FTA and then risk corresponding to these hazards are prioritized by FMEA. The results obtained from the proposed FTA-FMEA approach show that decision makers and engineers can easily decrease the number of hazards and risks with respect to both occupational health and safety in practice

A method based on q-rung orthopair fuzzy cognitive map and TOPSIS method for failure mode and effect analysis considering risk causal relationships

As a preventive maintenance technique, failure mode and effect analysis (FMEA) is widely applied to determine and eradicate possible failures. In recent years, many FMEA methods have been developed to address the limitations of traditional FMEA methods in failure mode (FM) assessment, weight calculation, and FM prioritization in complex uncertain environments. However, due to the complexity of equipment, systems, services, etc., there is an inevitable influence on causal relationships between FMs, which is rarely considered by existing methods. Therefore, a novel FMEA method, which integrates the technique for order preference by similarity to the ideal solution (TOPSIS) of q-rung orthopair fuzzy set (q-ROFS) and q-rung orthopair fuzzy cognitive map (q-ROFCM), is proposed for reasoning the relationships between FMs. The design of the novel method, named q-ROFCM FMEA, involves three stages. The q-ROFS is applied to evaluate the risk factors for capturing more ambiguous information in the first stage. The q-ROFCM is proposed and the causal relationship between FMs is integrated to describe the impact of the relationships on the evaluation results through the dynamic behavior of FMs in the second stage. In the third stage, the TOPSIS method is applied to determine the priority ranking of FMs based on more reliable similarity measurement results of the projection measure. The proposed new method is applied to the FM risk assessment of power units in the railway turnout system. The competitiveness and effectiveness of the proposed method have been demonstrated by comparison with other classic methods and sensitivity analysis.

A new approach to risk assessment in failure mode and effect analysis based on engineering textual data

Failure Mode and Effect Analysis (FMEA) is a valuable tool for improving the quality of products and service systems. However, traditional FMEA methods require examining various engineering textual materials and attending multiple meetings, which can be time-intensive. Additionally, accurately evaluating the severity (S), occurrence (O), and detection (D) of failure modes is essential to ensure the accuracy of FMEA results. Despite efforts by researchers to improve the efficiency of FMEA, the evaluation of these risk factors (S, O, and D) still relies too heavily on a manual and inefficient process. To address these issues, this paper proposes a machine learning-enabled FMEA approach. This new approach combines the strengths of the BERT (Bidirectional Encoder Representations from Transformers) model in transforming textual failure descriptions into word vectors, the advantages of the VSM (Vector Space Model) in determining semantic similarity between different failure modes, and the merits of TOPSIS based on objective weights in handling multicriteria risk assessment. The proposed approach was applied to an actual case study for failure mode and effect analysis in auto parts processing. Comparisons between the proposed method and conventional FMEA were conducted to demonstrate the effectiveness of the new approach.

An improved failure mode and effect analysis method for group decision-making in utility tunnels construction project risk evaluation

The risk factors of utility tunnels construction project (UTCPs) are diverse and complex, which can easily lead to serious accidents. And these accidents are usually the result of ignoring the most serious risk sources due to the lack of comprehensive risk evaluations. Therefore, this paper proposes an improved failure mode and effect analysis (FMEA) multi-criteria group decision model for utility tunnels construction project risk evaluation. First, expert groups are invited to evaluate the project risk failure modes, and k-means clustering is used to group the experts and form the aggregated matrix. Then, the CCSD (correlation coefficient and standard deviation) method, regret theory and MULTIMOORA method are used to rank the failure modes. Subsequently, the superiority of the model is illustrated by sensitive and comparative analyzes through a case study of the utility tunnels construction project for Beijing Winter Olympics. Finally, a systematic application model is proposed to provide some decision basis for project risk management.

Optimizing Footwear Manufacturing Through Defect Analysis and Spare Parts Optimization

This study investigates the causes of defects in the production line of inlay soles in footwear manufacturing, focusing on the impact of malfunctioning machine spare parts. Using Failure Mode and Effects Analysis (FMEA), critical machines—splitting, cutting, and moulding—are identified, along with their associated spare parts influencing defect occurrence. Process FMEA (PFMEA) prioritizes actions based on discussions with maintenance managers and quality staff. Results highlight top spare parts affecting defects, such as Fertinak, grinding stone, and V-belt for the splitting machine; hydraulic motor, hydraulic seal, and hydraulic filter for the cutting machine; and Solid State Relay, Thermocouple, and Heater for the moulding machine. These findings underscore the importance of maintaining machine performance and addressing spare part malfunctions to enhance product quality and operational efficiency in footwear manufacturing, providing actionable insights for industry practitioners. Hightligh: Critical Machines Identified: Splitting, cutting, and moulding machines analyzed for defect occurrence. Spare Parts Influence: Fertinak, Solid State Relay impact defect occurrence. Practical Industry Insights: Strategies for improving product quality and efficiency highlighted. Keywords: Defect analysis, Footwear manufacturing, Spare parts, Failure Mode and Effects Analysis (FMEA), Product quality.

Failure mode and effect analysis using VIKOR method based on interval-valued linguistic Z-numbers

Failure mode and effect analysis (FMEA) is an effective quality management tool used to improve product quality and reliability. However, with the application of FMEA, its shortcomings are exposed regarding risk assessment, weight determination, and failure mode risk prioritization. This paper proposes a new FMEA model using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method based on the Interval-valued linguistic Z-numbers (IVLZNs). Specifically, IVLZNs and the Interval-valued linguistic Z-numbers weighted arithmetic averaging (IVLZNWAA) operator are used to evaluate and aggregate risk information of failure modes; the maximum deviation method is used to determine the weight of risk factors; the IVLZNs-VIKOR method is used to determine the risk priority of failure modes. Then, a numerical example is given to verify the effectiveness of the proposed model. Finally, a comparative analysis is made to demonstrate the feasibility and rationality of the proposed method.

Multi-phase failure modes and effects analysis for low dose bilateral whole lung irradiation of COVID-19 positive patients requiring respiratory ventilation.

To identify high-priority risks in a clinical trial investigating the use of radiation to alleviate COVID-19 pneumonia using a multi-phase failure modes and effects analysis (FMEA). A comprehensive FMEA survey of 133 possible causes of failure was developed for the clinical trial workflow (Phase I). The occurrence, severity, and detection risk of each possible cause of failure was scored by three medical physicists. High-risk potential failure modes were identified using the risk priority number (RPN) and severity scores, which were re-scored by 13 participants in radiation oncology (Phase II). Phase II survey scores were evaluated to identify steps requiring possible intervention and examine risk perception patterns. The Phase II participants provided consensus scores as a group. Thirty high-priority failure modes were selected for the Phase II survey. Strong internal consistency was shown in both surveys using Cronbach's alpha (αc≥0.85). The 10 failures with the largest median RPN values concerned SARS-CoV-2 transmission (N=6), wrong treatment (N=3), and patient injury (N=1). The median RPN was larger for COVID-related failures than other failure types, primarily due to the perceived difficulty of failure detection. Group re-scoring retained 8/10 of the highest-priority risk steps that were identified in the Phase II process, and discussion revealed interpretation differences of process steps and risk evaluation. Participants who were directly involved with the trial working group had stronger agreement on severity scores than those who were not. The high ranking of failures concerning SARS-CoV-2 transmission suggest that these steps may require additional quality management intervention when treating critically ill COVID-19+ patients. The results also suggest that a multi-phase FMEA survey led by a facilitator may be a useful tool for assessing risks in radiation oncology procedures, supporting future efforts to adapt FMEA to clinical procedures.

Analysis Riplle Mill Machine Damage Analysis Using the FMEA Method at the PT Argo Sinergi Nusantara Palm Oil Factory

PT Agro Sinergi Nusantara (ASN), one of the industries engaged in the Palm Oil Mill (PKS) industry, is located in Teunom, Aceh Jaya Regency. The Ripple Mill machine is one of the important machines used in Palm Head Mills which functions as a separator or splitter of kernel kernels and palm shells by utilizing centrifugal force to produce Palm Kernel Oil. From the initial analysis, it is known that the use of Ripple Mill machines in the industry today often experiences donwtime or damage. The purpose of this study is to analyze the damage of the Ripple Mill machine at PT ASN's Palm Oil Mill using the Failure Mode and Effects Analysis (FMEA) method and Fishbone diagram. The results of the study obtained damage to the Ripple Mill machine in the identification of 5 (five) malfunctions or failure modes that occurred. using the FMEA method, it is known that the most dominant Ripple Mill machine failure mode occurs is the fracture of rotor bar components due to the entry of hard objects with the Risk Priority Number (RPN) which is 384 and using the fishbone diagram method, it is known that there are (four) influencing factors, namely human, machine, environmental and method factors.

Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems

The failure mode causes and effects analysis (FMCEA) is a commonly used reliability approach. It identifies, predicts, and analyzes potential failure modes affecting the proper function of equipment or the process under study, along with their roots and consequences. FMCEA aims to evaluate and assess the risks resulting from their occurrence, intending to suggest corresponding repair, adjustment, and precautionary measures to be planned during the conception, instruction, or implementation stages. However, the FMCEA has been criticized in the literature for its many inherent shortcomings related to risk assessment and prioritization. Therefore, this study presents an enhanced FMCEA method to address the deficiencies of the traditional risk priority number (RPN) and improve the reliability of risk assessments and corrective actions. A data envelopment analysis (DEA), as a non-parametric method, is used to evaluate the efficiency of these failures by considering their fixing time and cost and deciding on their final priority ranks. Sub-failure modes and their interrelationships are also taken into account. The radio frequency identification (RFID) system was chosen as an example due to its core role in Industry 4.0 and the Internet of Things (IoT) to demonstrate the effectiveness and usefulness of the proposed method. A total of 67 failures related to both hardware and software parts, including the environmental impacts of this technology, have been disclosed. The results of the conventional and the suggested FMCEA methods are found to be considerably different, with ten failure modes classified as being the most efficient.

Product Quality Improvement of Stainless Steel Round Trash Can with Six Sigma Approach and Fuzzy Analytical Hierarchy process Method at PT. XYZ

PT. XYZ is a manufacturing industry that produces various cleaning equipment. One of the products that has a high level of defects are trash bins made of stainless steel. The purpose of this research is to improve the quality of stainless steel waste products. The method used is Six Sigma and Fuzzy Analytical Hierarchy Process. In the Define stage, the types of defects found were body dents, scratches, spots, and rough covers. In the Measure stage, the initial DPMO value obtained is 3.422. In the Analyze stage, the results of the analysis process are defects with the highest Risk Priority Number of 280. The next stage is Improve, where defects with the highest RPN value are prioritized for proposed improvements using Fuzzy AHP. Based on the results of the Fuzzy AHP assessment, it was found that the highest weight was alternative 3, namely the machine must be cleaned regularly after being used at 0.4322, alternative 2, namely the addition of material handling to facilitate product transfer of 0.2048, and alternative 4, namely the establishment of SOPs for product handling. of 0.2041. After the Improve stage, the final stage in the form of Control is carried out to see whether the implementation of the proposed improvements has a positive impact on the company. The DPMO results obtained after implementation were 3.6061.

Penerapan Metode Failure Mode Effect And Analisys (FMEA) Pada Proses Penambahan Gudang

This research uses the Failure Mode Effect and Analysis (FMEA) method which is used to evaluate and analyze the causes of problems in the process of adding a new warehouse due to overstorage in the fertilizer storage warehouse. Where in this research it is known that the dominant causal factor that causes this problem is that it is difficult to obtain a warehouse according to the location needed and the warehouse procurement process takes quite a long time. From these dominant problems, alternative improvements were obtained to overcome these problems so that the process of adding a new warehouse could run effectively and efficiently in terms of time and cost

Risk identification of integral pressurized water reactor (IPWR) cooling system using a combination HAZOP, FMEA, and FTA methods

AbstractIntegral Pressurized Water Reactor (IPWR) is gaining attention for use in Indonesia due to lower initial capital investment, sitting flexibility, and high level of inherent safety. IPWR relies heavily on passive cooling systems that have many advantages but lacks operational experience because no one operates commercially. Therefore, it is necessary to carry out a risk analysis related to passive cooling system failures that may occur during operation. Even if conventional risk analysis methods are applied singularly, the results still have shortcomings. This study aims to integrate the use of the Hazard and Operability Analysis (HAZOP), Fault Tree Analysis (FTA), and Failure Mode and Effect Analysis (FMEA) methods to identify risks in the IPWR primary cooling system during normal operation. HAZOP was used to identify hazards, FTA analyzed the root causes of the critical problems, and the basic event's FMEA was developed for risk ranking and mitigation measures. This combined methodology makes risk assessment more systematic and comprehensive because it manages entity‐wide risk. The results offer valuable insights for stakeholders involved in decision‐making regarding the development of nuclear power plants (NPPs) in Indonesia.

Failure Mode and Effect Analysis (FMEA) Approach Based on Avoidance of Aggregation Discrepancy

As a powerful forward-looking risk management technique, FMEA has been widely used for reliability and security analysis in engineering management fields. In practice, the implementation of FMEA involves the participation of multiple members with distinct knowledge, experience, and cultural background, thus, FMEA is a typical multicriteria group decision-making problem. However, the existence of the aggregation discrepancy issue in FMEA problems with group decision-making leads to collective evaluation conflicts that bring about decision bias for further risk management. This article proposes an AADFMEA method based on multiple-objective optimization to promote the accuracy and reliability of collective assessment information in FMEA members, in which the 10-point qualitative scale is used for evaluation. Additionally, the AADFMEA method responds to the different individual cognitions to a specific evaluation value from multiple members by constraining the risk prioritization to derive more reasonable collective risk evaluation information. Finally, two case studies are presented to show that the AADFMEA method has a good application value, and the simulation analysis was conducted to verify the effectiveness of the proposed AADFMEA approach.

Fuzzy adaptive resonance theory failure mode effect analysis non-healthcare setting for infectious disease: review

<span>Fuzzy adaptive resonance theory (ART) is an ART network that is developed as one of the alternative methods to evaluate risk priority number (RPN) in failure mode and effect analysis (FMEA). Not only is FMEA are common technique as an analysis tool in industrial sectors, but also, especially during the global emergency COVID-19 pandemic hits, FMEA is used in prevention and mitigation measures. Many alternative methods have been proposed. However, not many investigations use clustering models such as Fuzzy ART in FMEA. This paper aims to provide a comprehensive review and then propose a model for systematic risk analysis which implement the fuzzy ART model, named clustering- transmission causes and effects analysis (c-TCEA), for the prevention and mitigation of infectious diseases.</span>

Identification of Advantages and Limitations of Current Risk Assessment and Hazard Analysis Methods when Applied on Autonomous Agricultural Machineries

Highlights The three main types of risk assessment and hazard analysis techniques applied on autonomous agricultural machines are: (1) Informal Group Analysis; (2) Hazard Analysis and Risk Assessment (HARA); and (3) Failure Mode and Effects Analysis (FMEA). Replicability is the main advantage of FMEA and HARA, while cost effectiveness is the main advantage of Informal Group Analysis. Subjectivity and the requirement for prior knowledge (data) are the main weaknesses of FMEA, HARA, and Informal Group Analysis when applied to novel and revolutionary autonomous agricultural machines. Abstract. In the last ten years, the development of automated agricultural machinery has seen noteworthy advancements. Nevertheless, the successful commercialization of these technologies depends critically on their ability to operate safely. This study evaluated the advantages and limitations of current risk assessment and hazard analysis methods currently used to ensure the safety of autonomous agricultural machines. An online survey containing 18 questions was distributed to 711 participants identified as potential individuals who are currently working or have worked on autonomous agricultural machines to determine the type and frequency of risk assessment and hazard analysis methods applied on autonomous agricultural machines, examine the advantages and limitations of each method, and investigate the perceived effectiveness of each method. Frequency analysis was used to determine the most and least utilized risk assessment and hazard analysis methods. The advantages and limitations of each risk assessment and hazard analysis approach were compared. Descriptive statistics (counts, means, medians, percent) and frequency analysis of the variables were used. The three main types of risk assessment and hazard analysis techniques applied to autonomous agricultural machines. The methods are (a) Informal Group Analysis (e.g., Brainstorming), (b) Hazard Analysis and Risk Assessment (HARA), and (c) Failure Mode and Effects Analysis (FMEA). Replicability is perceived as the main advantage of FMEA and HARA, while cost-effectiveness is the main advantage of Informal Group Analysis. The need to have pre-existing data of the autonomous agricultural machine at hand to be able to perform risk assessment and subjectivity are the main limitations of FMEA, HARA, and Informal Group Analysis dealing with novel and revolutionary autonomous agricultural machines. Industry experts do not believe that the risk assessment and hazard analysis procedures now used are reliable and efficient enough to guarantee the safety of autonomous agricultural tractors. This study reveals important information about the current state of risk assessment and hazard analysis methods in the context of autonomous agricultural machinery. This knowledge can inform future research, policy development, and industry practices to ensure the safety of autonomous agricultural machines. Keywords: Agricultural machine, Autonomous, FMEA, HARA, Hazard analysis, Informal Group Analysis, Risk assessment, Safety, Survey.

Failure mode and effect analysis with ORESTE method under large group probabilistic free double hierarchy hesitant linguistic environment

Failure Mode and Effect Analysis (FMEA) is a prospective and systematic analytical tool widely used to improve the reliability and safety of various industries. However, the existing FMEA methods have received criticism for their inherent deficiencies that limit their flexibility and effectiveness. To address these issues, we propose a novel FMEA model that combines Probabilistic Free Double Hierarchy Hesitant Linguistic Term Set (PFDHHLTS), Extended Grey Relation Analysis (EGRA), and ORESTE to determine the priorities of Failure Modes (FMs). Firstly, the PFDHHLTSs are proposed to represent experts’ assessments, improving the flexibility and accuracy of experts’ expressions. Secondly, the PFDHHLTS-EGRA is proposed to determine the evaluation matrix and the weights of risk factors in a large group environment. Furthermore, the ORESTE method is extended to the PFDHHLTS environment. Lastly, we verify the effectiveness of our method through a case study on the aluminum electrolysis process. The results demonstrate the effectiveness and flexibility of our method in expressing experts’ assessments and obtaining more accurate and reliable risk priorities.