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）.

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.

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。

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.

基于多学科协作的HFMEA对医院感染的控制效果

目的:探讨基于多学科协作的医疗失效模式与效应分析(HFMEA)在降低医院感染率方面的应用效果。方法:对2022年1月至12月中山大学附属第三医院院感数据进行回顾性分析,运用HFMEA模式进行风险评估,针对高风险环节制定预防措施和整改方案,并在2023年1月至12月实施改进措施。2023年12月再进行风险评估,分析应用多学科协作的HFMEA后,医院感染的控制效果。结果:与2022年相比,2023年应用多学科协作的HFMEA后,医院感染发生率、多重耐药菌(MDRO)感染发生率和呼吸机相关性肺炎(VAP)发生率均无显著差异(P值分别为0.650、0.653和0.219),抗菌药物病原学送检率、导尿管相关性尿路感染(CAUTI)发生率、中心静脉导管相关性血流感染(CLABSI)发生率、手卫生依从率和手卫生正确率均有明显改善(P<0.05)。结论:基于多学科协作的HFMEA应用在医院感染管理中,可显著提高抗菌药物病原学送检率,显著降低CAUTI和CLABSI发生率,大幅提升手卫生依从率和正确率。

HFMEA方法联合DMAIC流程管理在眼科手术室风险管理中的应用效果

目的探究医疗失效模式与效应分析(HFMEA)方法联合六西格玛流程管理(DMAIC)流程管理在眼科手术室风险管理中的应用效果。方法采用便利抽样法选取2022年11月至2023年5月于南昌大学附属眼科医院的住院手术的患者200例,归为对照组,另选取2023年6月至11月住院手术的患者200例,归为研究组。对照组依照现行的常规流程进行手术管理,研究组实施HFMEA方法联合DMAIC流程管理的管理模式。比较2组手术不良事件发生率及患者对手术护理工作满意度。结果研究组不良事件发生率为1.50%,显著低于对照组的7.00%(P<0.05);研究组患者对手术室护理和术前术后访视的满意度得分均显著高于对照组(P<0.001)。结论HFMEA方法结合DMAIC流程管理在眼科手术室中的实践能够显著改进手术室护理工作流程,增强风险识别与防范能力,提高患者满意度,并优化手术流程管理质量与效率。

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.

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.

Reliability Analysis of Unmanned Aerial Vehicles Flight Control System Based on Reliability Analysis Technologies

The unmanned aerial vehicles( UAV) has been becoming more and more important in the aviation industry.Despite the superior performance and advanced technology,major accident of UAV happens frequently due to the impact of their systems,long distance of remote control and skill of manipulator technology.According to the application of engineering application,failure mode effects and criticality analysis( FMECA),failure reporting analysis and corrective action comprehensive analysis systems( FRACAS)and fault tree analysis( FTA)( 3 F) were combined.And also a set of user-friendly,more time,more efficient and accurate reliability analysis system were explored.

HFMEA在腹腔镜手术中转开放手术配合中的应用

目的探讨医疗失效模式与效应分析(healthfailuremode and effect analysis,HFMEA)在腹腔镜手术中转开放手术配合中的应用效果。方法选取2022年1—6月厦门大学附属第一医院收治的718例腹腔镜手术患者作为实施前;选取2022年7—12月厦门大学附属第一医院收治的662例腹腔镜手术患者作为实施后。2022年6月组建跨专业的多学科小组,梳理腹腔镜手术中转开放手术实施的关键环节,对中转开放手术实施过程中可能出现的失效模式进行严重度、发生的可能性、探测的可能性评分,根据危害评分矩阵评估风险优先指数(risk priority number,RPN),针对RPN>125分的5项失效模式进行改进。比较实施前后的RPN和应急抢救配合满意度。结果腹腔镜手术中转开放手术安全管理体系中包括手术间管理不符合要求、人员管理不符合要求、临床实施操作不规范、仪器及设备运行失效、手术护理记录不规范5个方面17个风险点;其中有8个风险点需要采取措施进行控制,实施控制措施后,8个风险点的RPN值均有下降,且均<8分。手术医护团队对于实施腹腔镜手术中转开放手术管理策略的实践均表示认可。结论基于HFMEA对腹腔镜手术中转开放手术配合应急抢救进行风险识别及评估,建立腹腔镜手术中转开放手术配合安全管理机制,可有效降低腹腔镜手术中转开放手术配合应急抢救RPN,保障腹腔镜手术中转开放手术配合顺利,保障患者安全。