Intraoperative thermostatic nursing and failure mode and effects analysis enhance gastrectomies’ care quality

BACKGROUND Utilizing failure mode and effects analysis(FMEA)in operating room nursing provides valuable insights for the care of patients undergoing radical gastric cancer surgery.AIM To evaluate the impact of FMEA on the risk of adverse events and nursing-care quality in patients undergoing radical surgery.METHODS Among 230 patients receiving radical cancer surgery between May 2019 and May 2024,115 were assigned to a control group that received standard intraoperative thermoregulation,while the observation group benefited from FMEA-modeled operating room care.Clinical indicators,stress responses,postoperative gastroin-testinal function recovery,nursing quality,and the incidence of adverse events were compared between the two groups.RESULTS Significant differences were observed in bed and hospital stay durations between the groups(P<0.05).There were no significant differences in intraoperative blood loss or postoperative body temperature(P>0.05).Stress scores improved in both groups post-nursing(P<0.05),with the observation group showing lower stress scores than the control group(P<0.05).Gastrointestinal function recovery and nursing quality scores also differed significantly(P<0.05).Additionally,the incidence of adverse events such as stress injuries and surgical infections varied notably between the groups(P<0.05).CONCLUSION Incorporating FMEA into operating room nursing significantly enhances patient care by improving safety,expediting recovery,and reducing healthcare-associated risks.

New density clustering-based approach for failure mode and effect analysis considering opinion evolution and bounded confidence

Failure mode and effect analysis(FMEA)is a preven-tative risk evaluation method used to evaluate and eliminate fail-ure modes within a system.However,the traditional FMEA method exhibits many deficiencies that pose challenges in prac-tical applications.To improve the conventional FMEA,many modified FMEA models have been suggested.However,the majority of them inadequately address consensus issues and focus on achieving a complete ranking of failure modes.In this research,we propose a new FMEA approach that integrates a two-stage consensus reaching model and a density peak clus-tering algorithm for the assessment and clustering of failure modes.Firstly,we employ the interval 2-tuple linguistic vari-ables(I2TLVs)to express the uncertain risk evaluations provided by FMEA experts.Then,a two-stage consensus reaching model is adopted to enable FMEA experts to reach a consensus.Next,failure modes are categorized into several risk clusters using a density peak clustering algorithm.Finally,the proposed FMEA is illustrated by a case study of load-bearing guidance devices of subway systems.The results show that the proposed FMEA model can more easily to describe the uncertain risk information of failure modes by using the I2TLVs;the introduction of an endogenous feedback mechanism and an exogenous feedback mechanism can accelerate the process of consensus reaching;and the density peak clustering of failure modes successfully improves the practical applicability of FMEA.

Impact of failure mode and effects analysis-based emergency management on the effectiveness of craniocerebral injury treatment

BACKGROUND Craniocerebral injuries encompass brain injuries,skull fractures,cranial soft tissue injuries,and similar injuries.Recently,the incidence of craniocerebral injuries has increased dramatically due to the increased numbers of traffic accidents and aerial work injuries,threatening the physical and mental health of patients.AIM To investigate the impact of failure modes and effects analysis(FMEA)-based emergency management on craniocerebral injury treatment effectiveness.METHODS Eighty-four patients with craniocerebral injuries,treated at our hospital from November 2019 to March 2021,were selected and assigned,using the random number table method,to study(n=42)and control(n=42)groups.Patients in the control group received conventional management while those in the study group received FMEA theory-based emergency management,based on the control group.Pre-and post-interventions,details regarding the emergency situation;levels of inflammatory stress indicators[Interleukin-6(IL-6),C-reactive protein(CRP),and procalcitonin(PCT)];incidence of complications;prognoses;and satisfaction regarding patient care were evaluated for both groups.RESULTS For the study group,the assessed parameters[pre-hospital emergency response time(9.13±2.37 min),time to receive a consultation(2.39±0.44 min),time needed to report imaging findings(1.15±4.44 min),and test reporting time(32.19±6.23 min)]were shorter than those for the control group(12.78±4.06 min,3.58±0.71 min,33.49±5.51 min,50.41±11.45 min,respectively;P<0.05).Pre-intervention serum levels of IL-6(78.71±27.59 pg/mL),CRP(19.80±6.77 mg/L),and PCT(3.66±1.82 ng/mL)in the study group patients were not significantly different from those in the control group patients(81.31±32.11 pg/mL,21.29±8.02 mg/L,and 3.95±2.11 ng/mL respectively;P>0.05);post-intervention serum indicator levels were lower in both groups than pre-intervention levels.Further,serum levels of IL-6(17.35±5.33 pg/mL),CRP(2.27±0.56 mg/L),and PCT(0.22±0.07 ng/mL)were lower in the study group than in the control group(30.15±12.38 pg/mL,3.13±0.77 mg/L,0.38±0.12 ng/mL,respectively;P<0.05).The complication rate observed in the study group(9.52%)was lower than that in the control group(26.19%,P<0.05).The prognoses for the study group patients were better than those for the control patients(P<0.05).Patient care satisfaction was higher in the study group(95.24%)than in the control group(78.57%,P<0.05).CONCLUSION FMEA-based craniocerebral injury management effectively shortens the time spent on emergency care,reduces inflammatory stress and complication risk levels,and helps improve patient prognoses,while achieving high patient care satisfaction levels.

Comprehensive Reliability Allocation Method for CNC Lathes Based on Cubic Transformed Functions of Failure Mode and Effects Analysis

Reliability allocation of computerized numerical controlled（CNC）lathes is very important in industry.Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components,which is not applicable in some conditions.Aiming at solving the problem of CNC lathes reliability allocating,a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis（FMEA）is presented.Firstly,conventional reliability allocation methods are introduced.Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated.Subsequently,a cubic transformed function is established in order to overcome these limitations.Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence.Designers can choose appropriate transform amplitudes according to their requirements.Finally,a CNC lathe and a spindle system are used as an example to verify the new allocation method.Seven criteria are considered to compare the results of the new method with traditional methods.The allocation results indicate that the new method is more flexible than traditional methods.By employing the new cubic transformed function,the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

Risk Evaluation in Blood Donation Using Failure Mode and Effective Analysis

The recognition and management of risk in donation process and blood product is critical to ensure donor and patient safety. To achieve this goal, the failure mode and effects analysis (FMEA) is a convenient method;moreover it was used to prevent the occurrence of adverse events and look at what could go strong at each step. This study aimed to utilize FMEA in central blood bank in Khartoum to evaluate the potential risk and adverse event that may occur during the donation process. According to the severity, occurrence and the detection of each failure mode, the risk priority number (RPN) was calculated to determine which of the failures should take priority to find a solution and applying corrective action to reduce the failure risk. The statistical package for social sciences (SPSS) version 11 was used as descriptive and analytical statistics tool. The FMEA technique provides a systematic method for finding vulnerabilities in a process before they result in an error, and in this study a satisfactory outcome was reached.

Application of Fuzzy Decision-Making Theory and Conflict-Resolution Method to Failure Mode and Effect Analysis of Industrial Valve

It is not objective to rate the decision-making factors in the traditional failure mode and effect analysis,so fuzzy semantic theory is used in this paper.Six fuzzy semantic scales and their corresponding semantics are summarized,and a defuzzification method is studied to obtain the fuzzy value table of the six fuzzy semantic scales.For the conflicts between experts in the traditional failure mode and effects analysis,a conflict-resolution algorithm is studied to obtain the failure risk order.Finally,a certain type of industrial valve is used as an example to prove the validity of the theory proposed in this paper.

Failure Mode Effects and Criticality Analysis Method of Armored Equipment Based on Testability Growth

In view of the low level testability of armored equipment,the important significance of armored equipment testability growth is discussed in this paper.The failure mode effects and criticality analysis( FMECA) method to realize testability growth is introduced.Centering on the testability growth demands of new armored equipment,the deficiencies of traditional FMECA are analyzed.And an enhanced FMECA( EFMECA) method is proposed.The method increases the analysis contents,combines the information before the failure occurrence and impending failure modes together organically.Then the failure symptoms is analyzed,the failure modes and effects is determined,and the state development trend is predicted.Finally,the application of EFMECA method is illustrated by the example of the failure mode of typical armored equipment engine.

Effect of Healthcare Failure Mode and Effect Analysis on Reducing Error Risk of Neonatal Parenteral Nutrition Solution Dispensing

[Objectives]To investigate the effect of healthcare failure mode and effect analysis(HFMEA)on reducing error risk of neonatal parenteral nutrition solution dispensing.[Methods]A research team was established to identify the failure mode(FM)in each link of the formulation process of neonatal parenteral nutrition solution by HFMEA,quantify the severity(S),occurrence(O)and detection(D)of FM,and evaluate FM by risk priority number(RPN).For FM with the values of RPN>16,failure cause analysis was conducted,and corresponding improvement measures were formulated.The weight coefficient and random consistency ratio(CR)of deployment process were calculated in Matlab R2018a by compiling the Analytic Hierarchy Process(AHP)program.Six months after the implementation of improvement measures,the implementation effect was evaluated by comparing the changes of the values of RPN which was evaluated comprehensively and the rate of dispensing errors before and after the implementation of HFMEA.[Results]In the preparation process of neonatal parenteral nutrition solution,a total of 13 FMs with medium and above risk were found,the weight coefficient of medical order review,dosing and mixing was 0.2703,the weight coefficient of drug dispensing check and review was 0.1432,the weight coefficient of print label was 0.1015,the weight coefficient of distribution was 0.0716,and CR=0.0491<0.1.After six months of intervention,the total RPN value decreased by 64.81%from 127.8 to 45.0.The deployment error rates were significantly lower after the implementation,and the difference was statistically significant(P<0.05).[Conclusions]HFMEA can effectively reduce the error risk in preparation of neonatal parenteral nutrition solution,improve the quality of dispensing and promote the safety of neonatal medication.

Failure Mode and Effects Analysis （FMEA） by Fuzzy Data Envelop Analysis （Fuzzy-DEA）

Failure mode and effects analysis （FMEA） offers a quick and easy way for identifying ranking-order for all failure modes in a system or a product. In FMEA the ranking methods is so called risk priority number （RPN）, which is a mathematical product of severity （S）, occurrence （0）, and detection （D）. One of major disadvantages of this ranking-order is that the failure mode with different combination of SODs may generate same RPN resulting in difficult decision-making. Another shortfall of FMEA is lacking of discerning contribution factors, which lead to insufficient information about scaling of improving effort. Through data envelopment analysis （DEA） technique and its extension, the proposed approach evolves the current rankings for failure modes by exclusively investigating SOD in lieu of RPN and to furnish with improving sca.les for SOD. The purpose of present study is to propose a state-of-the-art new approach to enhance assessment capabilities of failure mode and effects analysis （FMEA）. The paper proposes a state-of-the-art new approach, robust, structured and useful in practice, for failure analysis.

Analysis of Potential Failure Modes in an Assembly Line by Fuzzy Expert Systems

The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. The FMEA team often demonstrates different opinions and these different types of opinions are very difficult to incorporate into the FMEA by the traditional risk priority number model. In this paper, for each of the Occurrence, Severity and Detectivity parameters a fuzzy set is defined and the opinion of each FMEA team members is considered. These opinions are considered simultaneously with weights that are given to each individual based on their skills and experience levels. In addition, the opinion of the costumer is considered for each of the FMEA parameters. Then, the Risk Priority Numbers （RPN） is calculated using a Multi Input Single Output （MISO） fuzzy expert system. The proposed model is applied for prioritizing the failures of Peugeot 206 Engine assembly line in IKCo （Iran Khodro Company）.

Effects of comprehensive nursing with cognitive behavioral therapy in orthodontic osteodilated arch treatment

BACKGROUND This work explored the effects of cognitive behavior therapy(CBT)-based comprehensive nursing intervention(CNI)mode in arch expansion to treat patients with orthodontic osteodilated arch(OOA).AIM To explore the application effect of CBT-based CNI model in orthodontic expansion arch treatment.METHODS Using convenient sampling method,81 patients with OOA were selected and rolled into a control group(Ctrl group,40 cases)and an observation group(Obs group,41 cases).During the treatment,patients in the Ctrl group received routine nursing intervention mode,and the those in the Obs group received CBT mode on the basis of this.Before and after intervention,the incidence of oral mucositis,the mastery rate of correct arch expansion method,self-rating anxiety scale score,soft scale index,and plaque index were compared for patients in different groups.In addition,satisfaction and complications were comparatively analyzed.RESULTS Incidence of oral mucositis in the Obs group was lower(14.6%vs 38.5%),and the mastery rate of correct arch expansion method was obviously higher(90.2%vs 55.0%)was obviously higher(all P<0.05).Meanwhile,the soft scale index and plaque index in the Obs group were much lower(P<0.05).The compliance(90.24%)and satisfaction(95.12%)in the Obs group were greatly higher(P<0.05).CONCLUSION The CBT-based CNI mode greatly improved the mastery rate of correct arch expansion method during arch expansion in treating patients with OOA and enhanced the therapeutic effect of arch expansion and the oral health of patients,improving the patient compliance.

System failure analysis based on DEMATEL–ISM and FMECA

A new method of system failure analysis was proposed. First, considering the relationships between the failure subsystems,the decision making trial and evaluation laboratory(DEMATEL) method was used to calculate the degree of correlation between the failure subsystems, analyze the combined effect of related failures, and obtain the degree of correlation by using the directed graph and matrix operations. Then, the interpretative structural modeling(ISM) method was combined to intuitively show the logical relationship of many failure subsystems and their influences on each other by using multilevel hierarchical structure model and obtaining the critical subsystems. Finally, failure mode effects and criticality analysis(FMECA) was used to perform a qualitative hazard analysis of critical subsystems, determine the critical failure mode, and clarify the direction of reliability improvement.Through an example, the result demonstrates that the proposed method can be efficiently applied to system failure analysis problems.

Failure Modes of Machining Center in Test Run

To analysis the early failures of machining centers,the failure mode effect and criticality analysis( FMECA) method was used. Based on the failure data collected from production lines in test run,all the failure modes of machining centers were summarized and criticality of all subsystems is figured out. And the process of FMECA was improved. The most critical subsystem was manipulator subsystem. The most critical failure mode was impacted manipulator. Reasons and effect of some important failure modes were analyzed. And some suggestions to solve failures were given.

Numerical analysis of pile–slope stability and the soil arching around two adjacent piles

Seismic pile–slope stability analysis and the formation mechanism of soil arching have not been well studied. This study used a threedimensional(3D) finite difference to determine soil and pile parameter changes in the static and seismic stability of the pile–slope caused by the interaction between stabilizing piles. Pile–slope stability analysis was performed to determine the optimal design of piles along a slope and the corresponding failure mode involving the formation of soil arching around two adjacent piles. The Factor of Safety(FS) of the slope was evaluated using the shear strength reduction method for static and seismic analyses. The results of the analysis show that suitable pile spacing(S) and a suitable pile diameter(D) in the middle of a slope result in the maximum FS for the pile–slope system and the formation of soil arching around two adjacent piles. FS of the pile–slope increased negligibly in the seismic analysis of piles located at the slope crest and toe. An optimized pile diameter and installation location afforded the maximum FS for the slope that corresponded to a specified slope failure mode for different pile locations. A pile spacing S ≤ 2.5D for piles installed in the middle of the slope is suggested for increasing the static and seismic pile–slope stability.

Critical review and functional safety of a battery management system for large‑scale lithium‑ion battery pack technologies

The battery management system(BMS)is the main safeguard of a battery system for electric propulsion and machine electrifcation.It is tasked to ensure reliable and safe operation of battery cells connected to provide high currents at high voltage levels.In addition to efectively monitoring all the electrical parameters of a battery pack system,such as the voltage,current,and temperature,the BMS is also used to improve the battery performance with proper safety measures within the system.With growing acceptance of lithium-ion batteries,major industry sectors such as the automotive,renewable energy,manufacturing,construction,and even some in the mining industry have brought forward the mass transition from fossil fuel dependency to electric powered machinery and redefned the world of energy storage.Hence,the functional safety considerations,which are those relating to automatic protection,in battery management for battery pack technologies are particularly important to ensure that the overall electrical system,regardless of whether it is for electric transportation or stationary energy storage,is in accordance with high standards of safety,reliability,and quality.If the system or product fails to meet functional and other safety requirements on account of faulty design or a sequence of failure events,then the environment,people,and property could be endangered.This paper analyzed the details of BMS for electric transportation and large-scale energy storage systems,particularly in areas concerned with hazardous environment.The analysis covers the aspect of functional safety that applies to BMS and is in accordance with the relevant industrial standards.A comprehensive evaluation of the components,architecture,risk reduction techniques,and failure mode analysis applicable to BMS operation was also presented.The article further provided recommendations on safety design and performance optimization in relation to the overall BMS integration.

Analysis of Computer Network Reliability and Criticality: Technique and Features

The paper describes modern technologies of Computer Network Reliability. Software tool is developed to estimate of the CCN critical failure probability (construction of a criticality matrix) by results of the FME(C)A-technique. The internal information factors, such as collisions and congestion of switchboards, routers and servers, influence on a network reliability and safety (besides of hardware and software reliability and external extreme factors). The means and features of Failures Modes and Effects (Critical) Analysis (FME(C)A) for reliability and criticality analysis of corporate computer networks (CCN) are considered. The examples of FME(C)A-Technique for structured cable system (SCS) is given. We also discuss measures that can be used for criticality analysis and possible means of criticality reduction. Finally, we describe a technique and basic principles of dependable development and deployment of computer networks that are based on results of FMECA analysis and procedures of optimization choice of means for fault-tolerance ensuring.

A Computer Aided System for URT Maintenance Optimization Based on a FMEA-fuzzy Model

In recent years, urban rail transit （URT） systems have rapidly developed in China, however, their existing strategies for vehicle maintenance are still based on experiential and qualitative methods which result in either high cost or emergencies. In this paper, a tentative attempt at introducing the fuzzy set theory into quantitative analysis and assessment of URT trains＇ failures was presented. Based on the proposed FMEA-fuzzy model, a com- puter aided system for URT maintenance optimization was developed. The overall structure and procedure of the system were described in detail, and the important issues, including the development environment, improvement to FMEA table, acquisition of weight distribution matrix P, and setting of fuzzy vector R, were also discussed. Initial application into the vehicle maintenance of Shanghai Metro System shows, that the proposed model and computer aided system have a good performance and consequently are worth further development.

基于FMEA与JACK的野外陆地救援担架创新设计

为有效设计符合人机工程原理的陆地救援担架,降低救援人员在使用救援担架中引发骨骼肌肉损伤的风险,研究采用潜在失效模式与效应分析(FMEA)、JACK人机工程学仿真相结合的方法。首先,计算出风险优先级数(RPN),从而确定救援担架潜在失效模式的比重。然后,通过JACK仿真数据对比分析P5和P95救援人员的肌肉骨骼疲劳程度,如下背部分析(LBA)、静态强度预测(SSP)等,并制定相应的改进措施。最后,使用JACK仿真和FMEA分析验证改进设计后的救援担架。FMEA与JACK仿真结合可精准挖掘影响人机关系的关键因素,仿真数据表明,通过改进设计,救援人员的肌肉骨骼疲劳程度均得到了有效控制,且使下担架过程更加稳定。

失效模式与效应分析在口腔综合治疗台水路污染管理中的应用

目的:分析失效模式与效应分析(failure mode and effect analysis,FMEA)在口腔综合治疗台水路(DUWLs)污染管理中的应用,为临床口腔综合治疗台水路污染防控提供依据。方法:采用便利抽样法,选取某三级甲等口腔专科医院40台口腔综合治疗台(DCU)为研究对象,应用失效模式与效应分析法风险管理工具,组建多学科团队,通过对口腔综合治疗台所在科室口腔综合治疗台管理相关人员进行隐蔽性参与式观察,发现口腔综合治疗台管理过程中潜在失效模式及潜在失效结果,对高风险失效模式制定并实施一系列干预措施。比较失效模式与效应分析法实施前后口腔综合治疗台手机端、三用枪、漱口水端开诊前及诊疗之间医务人员冲洗行为的依从率及正确率、各失效模式的风险优先指数(RPN)降低率以及诊疗用水合格率。结果:与干预前相比,实施失效模式与效应分析法管理后口腔综合治疗台手机端、三用枪、漱口水端开诊前及诊疗之间医务人员冲洗行为的依从率及正确率均提高,差异均有统计学意义(P<0.05);与干预前相比,实施失效模式与效应分析法管理后各项高风险失效模式RPN值均下降;与干预前相比,口腔综合治疗台手机端、三用枪、漱口水端诊疗用水合格率提高,差异均有统计学意义(P<0.05)。结论:运用失效模式与效应分析法风险管理工具能有效提升口腔医务人员口腔综合治疗台水路污染管理水平,提高口腔诊疗用水合格率。

基于HFMEA预防人工肝支持系统导管相关血流感染的效果评价

目的探讨医疗失效模式与效应分析(HFMEA)预防人工肝支持系统(ALSS)导管相关血流感染的效果。方法选取中山大学附属第三医院2022年1月至2023年12月行ALSS治疗的患者进行非随机对照试验,根据入院时间分成对照组(2022年1月至12月)和观察组(2023年1月至12月)。对照组338例,男283例,女55例,年龄(49.35±11.52)岁,采用ALSS导管常规护理。观察组389例,男323例,女66例,年龄(47.90±12.94)岁,应用HFMEA管理。两组均护理7 d。比较护理后两组患者ALSS导管相关血流感染失效模式风险系数(RPN)和发生率,实施HFMEA项目管理前、后科室护理人员ALSS导管维护理论和操作考核成绩。统计学方法采用t检验。结果护理后,观察组患者ALSS导管相关血流感染失效模式RPN与发生率均较对照组低[1592分比3980分、0.083‰(1/11984)比0.418‰(5/11952)]。实施HFMEA项目管理后,护理人员理论考核、操作考核成绩均高于实施前[(85.28±4.94)分比(75.56±9.72)分、(94.24±2.19)分比(84.24±2.19)分],差异均有统计学意义(t=6.490、23.506,均P<0.05)。结论应用HFMEA可前瞻性预见易导致ALSS治疗患者导管相关血流感染的高风险失效环节,降低导管相关血流感染事件发生率,提高护理人员导管维护能力。