Enhancing Risk Assessment of Bridge Construction: applying an Integrated Failure Mode and Effect Analysis and Analytic Hierarchy Process Methods

PT X is a manufacturing company that produces high-precision components, using 13 units of CNC machines as production tools. The target of achieving technical availability for each machine unit is at least 85% in one year. One of the machine units, namely the CNC vertical turning lathe machine in this company, was only able to reach 64% of the technical availability value due to the impact of the damage. This study aims to determine the causes of component failure in machine units that have low technical availability, namely the CNC vertical turning lathe, using the Failure Mode and Effect Analysis method. The results showed that during one year, the CNC vertical turning lathe was damaged 19 times, on 7 different machine components. With the results of data processing using the Failure Mode and Effect Analysis method, it is known that of the 7 components that were damaged, the component that had the highest risk priority number value was the electronic component with an RPN value of 405.

The apartment is a vertical building used for residential purposes. It is included in a high rise building category with high occupational risk accident level due to its work complexity, or high elevation factors. This research discussed the risk assessment of occupational accident at one of the apartment constructions in Surabaya in order to determine its dominant risk factors and mitigation. Failure Mode and Effect Analysis (FMEA) method was applied to this research. It is a risk assessment method based on severity, occurrence, and detection. Following the relevant assessment, it resulted in 3 types of occupational accidents with the highest Risk Priority Number, namely height work accident, falling material from tower crane, and risk of landslide excavation.

This paper introduces a formulation of appropriate risk estimation methods that can be used for improving of processes in the electronics area. Two risk assessment methods have been chosen with regard to the specifics of adhesive joining based on electrically conductive adhesives. The paper provides a combination of a failure mode and effect analysis (FMEA) and fault tree analysis (FTA) for optimizing of the joining process. Typical features and failures of the process are identified. Critical operations are found and actions for avoiding failures in these actions are proposed. A fault treehas been applied to the process in order to get more precise information about the steps and operations in the process, and the relations between these operations. The fault tree identifies potential failures of the process. Then the effects of the failures have been estimated by the failure mode and effect analysis method. All major differences between failure mode and effect analysis and fault tree analysis are defined and there is a discussion about how to use the two techniquescomplement each other and achieve more efficient results.

Objective To analyze the risks of hypertonic glucose injection ( 20%) (hypertonic glucose) in clinical application using failure mode and effect analysis (FMEA) method and improve the relevant management measures. Methods A study group on risk prevention strategies of hypertonic glucose was established in the First People′s Hospital of Hefei. Domestic and foreign literature on medication error cases, preventive measures or management strategies, and data from questionnaires and on-the-spot investigations were collected. The failure modes in the process of hypertonic glucose application were analyzed and assessed. Severity (S), frequency of occurrence (O), and likelihood of detection (D) of the risks related to these failure modes were scored and the risk priority numbers (RPN) were determined. The failure modes with higher RPN were screened out and the corresponding prevention strategies were formulated. The incidence of medication errors and potential hazards, cognition rate of knowledge on drugs, qualification rate of drug storage, and satisfaction rate for management measures before and after the improvement were analyzed comparatively. Results According to the results from literature search, questionnaires, and on-the-spot investigations, a total of 24 failure modes were found in the 6 links relevant with hypertonic glucose application in clinical, which included links of prescription writing and delivery, pharmacist dispensing, nurse dispensing, post-administration monitoring, drug management, and information technology. Ranking the RPN from high to low, 7 major failure modes with higher RPN were selected from the 24 failure modes, including the existence of drugs with similar name and drugs with similar package, wrong drug dispensing, absence of post-administration monitoring, lack of marked labels for drugs, garbles caused by lack of medication knowledge, and untimely record and report of medication errors. The incidences of medication errors and potential safety hazards before and after management improvement were 3.2% (7/216) and 0.4% (1/234), respectively and the difference had no statistical significance (P=0.058). The average cognitive rates of physicians, nurses and pharmacists before and after the improvement were 65.2%(15/23), 54.2%(13/24), 67.9%(19/28) and 95.8%(23/24), 91.7%(22/24), 95.5%(21/22), respectively and the differences were statistically significant (P<0.05 for all). The qualification rates of drug storage before and after management improvement were 70.2%(151/215) and 98.7%(230/233), respectively and the difference was statistically significant (P<0.05). The average satisfaction degrees of medical staff with hyperosmotic glucose management were 81.3%(61/75) and 95.7%(65/70), respectively before and after the management improvement and the difference was statistically significant (P<0.05). Conclusion Failure modes in the process of hypertonic glucose use can be effectively identified using the FMEA method, and the risk events can be effectively reduced after the corresponding improvement measures. Key words: Healthcare failure mode and effect analysis; Glucose solution, hypertonic; Hospital administration; High-alert medicine

Quality control is a proactive of systematic effort to identify and eliminate the root causes of defects in Crude Palm Oil (CPO) by focusing resources on process points that have the highest risk of failure. The goal is to achieve optimal product quality consistency at PT. Kebun Ganda Prima. The application of the Failure Mode and Effect Analysis (FMEA) method in the processing of oil palm fresh fruit bunch (FFB) into CPO at PT. Kebun Ganda Prima PKS Kembayan can serve as an effective alternative to identify, evaluate, and analyze potential failures that may occur during the production process. This study aims to enhance CPO quality by minimizing product defects and optimizing production efficiency through the tracing of critical points in the process that are susceptible to failure. The results of the FMEA analysis indicate that the highest-risk failure mode occurs at the Fresh Fruit Bunch (FFB) reception stage, specifically poor oil palm fruit quality, with the highest Risk Priority Number (RPN) value of 128.85. This condition is characterized by a high proportion of overripe or rotten fruit, which is the primary cause of the increased Free Fatty Acid (FFA) content in the CPO. Additionally, other potential failures were identified in the form of imperfect stripping (threshing) and malfunction of key equipment, such as the sterilizer and thresher. Based on these findings, quality control efforts should be focused on strict supervision of initial raw material quality and the implementation of preventive maintenance on critical machinery. The proposed recommendations include tightening the Standard Operating Procedures (SOPs) at the FFB reception stage and optimizing the preventive maintenance schedule to ensure that the processing runs consistently and produces CPO that meets quality standards.

PT. DALWA ANUGRAHHASANIAH, a company that produces Packaged Drinking Water (AMDK) using ozone technology, this company also produces various sizes of glasses, bottles, and uses two types of raw materials - mineral water and demineralized water. This study aims to ensure that the AMDK production process does not experience defects. In an effort to reduce product defects, the Failure Mode and Effect Analysis (FMEA) method is used. FMEA is a proactive risk management method used to identify potential failures in a system, design, process, or service before it reaches the consumer. The goal is to prevent failure, maintain product quality, and reduce associated costs. The Failure Mode and Effect Analysis (FMEA) method is detailed, focusing on identifying failure modes, effects, causes, severity, occurrence, detection, and risk prioritization. Successful FMEA implementation is defined by a 30%-50% reduction in the new RPN value compared to the initial RPN value.

BackgroundMedical ultrasound device has been more and more widely used in the hospital and Its safety risk is significantly increased when failures occur. However, there is a lack of quantitative risk assessments of different types of failure modes for medical ultrasound device. This study utilizes a failure mode, effect and criticality analysis (FMECA) approach for quantitative risk evaluation of different failure modes for ultrasound devices.MethodsThe 4216 medical ultrasound device failure records at various hospitals were investigated. A failure mode and effect analysis method was developed for the quantitative evaluation of the risks of different failure modes. Visual correlation analysis was conducted for all categories to identify the causes of various failure modes. Based on the severity, occurrence and detectability of the failure causes determined, the risk priority number (RPN) for each failure mode was back-calculated through the obtained tracking diagram.ResultsThe failure modes of unclear images, unable to power on and dark shadows on an image had the highest RPNs. One failure mode could be caused by various factors, and the failure location was not necessarily related to the cause of the failure.ConclusionsThis quantitative approach more accurately evaluated the risks of different failure modes, and the results of the corresponding analysis of failure modes and causes could support the rapid determination of the causes of failures in clinical practice.

Groundwater resources are essential for drinking water, irrigation, and the economy mainly in semiarid environments where rainfall is limited. Currently, unpredictable rainfall due to climate change and pollution on the Earth’s surface directly affects groundwater resources. In this area, most people depend on groundwater resources for irrigation and drinking purposes, and every summer, most of the area depends on groundwater in a semiarid environment. Hence, we selected two popular methods, the analytical hierarchy process (AHP) and multiple influence factor (MIF) methods, which can be applied to map groundwater potential zones. Nine thematic layers, such as land use and land cover (LULC), geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps, were selected for this study using remote sensing and geographic information system (GIS) techniques. These layers are integrated in ArcGIS 10.5 software with the help of the AHP and MIF methods. The map of the groundwater potential zones in the study area revealed four classes, i.e., poor, moderate, good, and very good, based on the AHP and MF methods. The groundwater potential zone area is 241.50 (ha) Poor, 285.64 (ha) moderate, 408.31 (ha) good, and 92.75 (ha) very good using the AHP method. Similarly, the MIF method revealed that the groundwater potential classes were divided into four classes: 351.29 (ha) poor, 511.18 (ha), moderate, 123.95 (ha) good, and 41.78 (ha) very good. The results were compared to determine which methods are best for planning water and land resource development in specific areas that have basaltic rock and drought conditions. Both groundwater potential zone maps were validated with water yield data. The receiver operating characteristic (ROC) curve and area under the curve (AUC) model results are found to be 0.80 (good) and 0.93 (excellent) using the MIF and AHP methods, respectively; hence, the AHP method is best for delineation of groundwater potential zone maps and groundwater resource planning. The present study’s framework and the results will be valuable for improving the efficiency of irrigation, conserving rainwater and maintaining the ecosystem in India.

To solve the problems such as uncertain evaluation information, high dependence on experts, and no consideration of the degradation of machine operating performance to failure risk in the practical application of FMEA in CNC machine tool operation and maintenance, a dynamic failure mode and effect analysis (FMEA) method for CNC machine tool in service is proposed, operation and maintenance data is introduced to the traditional failure risk analysis, which makes semantics criteria and data-driven method are systematically integrated, resulting in better performance of quantitative assessment and risk ranking of dynamic fault risk. Afterward, the fault classification and maintenance strategy of the CNC machine tool based on risk priority number (RPN) is proposed, which provides decision support for efficient operation and maintenance of the CNC machine tool. Finally, a machining center is taken as an example to verify the feasibility and effectiveness of the method.

Objective To explore the effect of failure mode and effect analysis (FMEA) method in strengthening the management of critical value of blood specimens in hospital. Methods According to the procedures of FMEA, critical values management team were established, drew flow chart of generating test specimens and crisis value, explored the potential failure mode and failure cause, analyzed the severity, possibility and critical value, and formulate and implement countermeasures according to the research outcome. Results The crisis value of the failure mode fell from 1 320 to 151 after the implementation of FMEA, and rate of decline was 88.56% ; number of unqualified blood samples decreased from 510 cases to 78 cases, and the difference is statistically significant (χ2=407.27, P < 0.05); critical value processing defects decreased from 85 cases (a total of 236 cases) to 3 cases (a total of 229 cases), and the difference was statistically significant (χ2=91.26, P < 0.05). Conclusions FMEA method is helpful to improve the accuracy and precision of critical value management of clinical blood samples, so as to ensure the safety of patients in hospitals. Key words: Failure mode and effect analysis; Critical value management

Risk assessment based on failure mode and effects analysis (FMEA) and WASPAS methods under probabilistic double hierarchy linguistic term sets

Risk evaluation is an important part of the product design and product manufacturing process; it entails the pursuit of the highest product quality and preventing failure under the constraints of limited resources. The failure mode and effects analysis approach is one of the most widely applied risk evaluation tools that uses the product of the three risk elements of product failure items, severity, occurrence probability, and detection probability, to calculate the risk priority number, the priority of failure risk. However, the typical failure mode and effects analysis method ignores the consideration of objective weights, which may lead to incorrect evaluation results. Moreover, the method of expressing information about product failure provided by experts also directly affects the results of risk assessment. To comprehensively assess the risk of product failure, in this study, the hybrid of the Fermatean fuzzy set and entropy method was used to prioritize product failure items risk. This study used a service failure mode and effects analysis numerical example of self-service electric vehicles to illustrate and test the correctness of the proposed new hybrid Fermatean fuzzy set and entropy method. The mathematical operation results were also compared with the listing of different calculation methods. The test results prove that the proposed new hybrid Fermatean fuzzy set and entropy method can fully consider the cognitive information provided by experts to provide more accurate risk ranking results of failure items.

In HRC production at PT XYZ which is carried out continuously to pursue the production target will be in effect on the HRC production component with the risk management methods is Failure Mode, Effect and Criticality Analysis (FMECA). The purpose of this study is to identify the source of potential failure in HRC production, analyze the RPN value, and determine control recommendations. Data collection methods are carried out by means of direct observation of HRC production, interviews, and literature studies. The results on the risk assessment by the FMECA method are leakage and operational failure of the burner device with a RPN value of 420, the Refractory Brick Furnace crack of 324, the scale piece bounced off the 294 reservoir, the oil leak on the flat pass, the work roll, and the backup roll of 252 , damage to the roller table machine is 240, operational failure on the Looper engine of 240, and the failure of the HRC product binding manually is 240. Risk control in HRC production is the use of flame rod indicators, ultraviolet sensors, ultrasonic tests, installation of slab pieces cover, thermal infrared camera, LOTO use, quadratic linear inverse system or predictive control, distance guard, and periodic maintenance.

Evaluating the academic scientific laboratories' safety by applying failure mode and effect analysis (FMEA) at the public university in Lebanon

Aims: The growth of population and people’s need for health care have increased medical wastes productions. The aim of this study is the hazardous waste risk assessment of hospital by using of two methods: failure mode and effects analysis and preliminary hazard analysis (PHA). Methods: The first, worksheets related to fracture mode and effects analysis were distributed among hospital experts and then the potential hazard for the type of wastes was determined. Results: At method of failure mode and effects analysis, 8 cases had the risk priority number &gt;100 and according to the results of the PHA, the sharp, infectious, human anatomical, chemical/pharmaceutical, and radioactive wastes, respectively, had a high potential of risk. Conclusion: failure mode and effects analysis can be used as a new approach to preventing errors and improving processes with the aim of increasing safety and reducing of probability danger in long term.