Factors Affecting Quality of Equipment Maintenance Based on Structural Equation Modeling

Factors affecting equipment maintenance quality usually include personnel,equipment and facilities,raw materials and spare parts, craft, environment and quality management. These six factors affecting maintenance quality are not all the same degree. In order to find out which factor can influence equipment maintenance quality greatly and achieve sophisticated management,characteristic quantities of six factors are presented. A structural equation modeling( SEM) is designed using the six factors as latent variables and their characteristic quantities as the observed variable.According to the basic data obtained from the questionnaire survey,calculate the standardized regression weight by parameter estimation of the SEM. Then the key factors affecting the quality of the equipment maintenance are determined with the help of the standardized regression weight.

Hierarchical Colored Timed Petri Nets for Maintenance Process Modeling of Civil Aircraft

Civil aircraft maintenance process simulation model is an effective method for analyzing the maintainability of a civil aircraft. First, we present the Hierarchical Colored Timed Petri Nets for maintenance process modeling of civil aircraft. Then, we expound a general method of civil aircraft maintenance activities, determine the maintenance level for decomposition, and propose the methods of describing logic of relations between the maintenance activities based on Petri Net. Finally, a time Colored Petri multi-level network modeling and simulation procedures and steps are given with the maintenance example of the landing gear burst tire of a certain type of aircraft. The feasibility of the method is proved by the example.

Some Insights in Novel Risk Modeling of Liquefied Natural Gas Carrier Maintenance Operations

这研究在海上的环境讨论各种各样的当模特儿的途径和对液化天然气(LNG ) 搬运人操作适用的维护技术的分析。各种各样的新奇建模技术被讨论；包括基因算法，模糊逻辑并且证据的推理。我们也在风险评价并且维护建模的区域在 LNG 搬运人工业识别这些算法的实用性。

Comprehensive kinetostatic modeling and morphology characterization of cable-driven continuum robots for in-situ aero-engine maintenance

In-situ maintenance is of great significance for improving the efficiency and ensuring the safety of aero-engines.The cable-driven continuum robot(CDCR)with twin-pivot compliant mechanisms,which is enabled with flexible deformation capability and confined space accessibility,has emerged as a novel tool that aims to promote the development of intelligence and efficiency for in-situ aero-engine maintenance.The high-fidelity model that describes the kinematic and morphology of CDCR lays the foundation for the accurate operation and control for in-situ maintenance.However,this model was not well addressed in previous literature.In this study,a general kinetostatic modeling and morphology characterization methodology that comprehensively contains the effects of cable-hole friction,gravity,and payloads is proposed for the CDCR with twin-pivot compliant mechanisms.First,a novel cable-hole friction model with the variable friction coefficient and adaptive friction direction criterion is proposed through structure optimization and kinematic parameter analysis.Second,the cable-hole friction,all-component gravities,deflection-induced center-of-gravity shift of compliant joints,and payloads are all considered to deduce a comprehensive kinetostatic model enabled with the capacity of accurate morphology characterization for CDCR.Finally,a compact continuum robot system is integrated to experimentally validate the proposed kinetostatic model and the concept of in-situ aero-engine maintenance.Results indicate that the proposed model precisely predicts the morphology of CDCR and outperforms conventional models.The compact continuum robot system could be considered a novel solution to perform in-situ maintenance tasks of aero-engines in an invasive manner.

Research of Consistency Maintenance Mechanism in Real-Time Collaborative Multi-View Business Modeling

Real-time collaborative editing(RTCE)can support a group of people collaboratively work from distributed locations at the same time.However,consistency maintenance is one key challenge when different types of conflicts happen.Therefore a common synchronous mechanism is proposed to support consistency maintenance in the process of multi-view business modeling.Based on operation analysis on different views of models in the real-time collaborative editing system,detection of potential conflicts is realized by means of a decision-making tree.Then consistency maintenance provides a comprehensive and applicable conflicts detection and resolution for collaborative business modeling.Finally,a prototype of collaborative multi-view business modeling system is introduced to verify the approach.The point is that the mechanism proposes a comprehensive solution for collaborative multi-view business modeling.

Wind Turbine Optimal Preventive Maintenance Scheduling Using Fibonacci Search and Genetic Algorithm

Maintenance scheduling is essential and crucial for wind turbines (WTs) to avoid breakdowns andreduce maintenance costs. Many maintenance models have been developed for WTs’ maintenance planning, suchas corrective, preventive, and predictive maintenance. Due to communities’ dependence on WTs for electricityneeds, preventive maintenance is the most widely used method for maintenance scheduling. The downside tousing this approach is that preventive maintenance (PM) is often done in fixed intervals, which is inefficient. In thispaper, a more detailed maintenance plan for a 2 MW WT has been developed. The paper’s focus is to minimize aWT’s maintenance cost based on a WT’s reliability model. This study uses a two-layer optimization framework:Fibonacci and genetic algorithm. The first layer in the optimization method (Fibonacci) finds the optimal numberof PM required for the system. In the second layer, the optimal times for preventative maintenance and optimalcomponents to maintain have been determined to minimize maintenance costs. The Monte Carlo simulationestimates WT component failure times using their lifetime distributions from the reliability model. The estimatedfailure times are then used to determine the overall corrective and PM costs during the system’s lifetime. Finally,an optimal PM schedule is proposed for a 2 MW WT using the presented method. The method used in this papercan be expanded to a wind farm or similar engineering systems.

Study on Simulation Modeling and Evaluation of Equipment Maintenance

Aiming at the actual demand for the maintenance support of new general equipments, this paper analyzes the structure and circulation of maintenance support system, builds the simulation model of running process by entity flow chart method, and constructs the basic frame of the simulation model. The generating method of random variables and the advancing process of the simulation clock are described, and the accurate prediction of maintenance equipment is realized. Moreover, the material readiness rate is analyzed in statistics objective to evaluate the simulation result. The research is of significance for improving the efficiency of equipment maintenance and the promotion of material readiness rate.

A copula-based approach to accommodate intra-household interaction in workers' daily maintenance activity stop generation modeling

A new stop frequency model was developed to predict the daily number of maintenance activity stops made by individual household heads during a typical weekday. This new model was based on the modification of a conventional multivariate ordered probit(MOP) model by maintaining the probit assumption for the marginal distributions while introducing nonnormal dependence among the error terms using copula functions. Therefore, the copulabased MOP model would relieve the restriction of imposing joint normality on the error terms in the conventional MOP model. The new MOP model would not only account for the intrahousehold interactions in stop-making decisions, but also allow the best functional form to be determined for representing dependencies among household heads. Using the New York Metropolitan Transportation Council’s 2010/2011 regional household travel survey data, the copula-based MOP model was employed to examine stop-making behavior for individual household heads residing in New York City and its adjacent counties in Mid-Hudson Valley and New Jersey. Empirical results provided useful insights into the observed effects of sociodemographics, land use density, transportation service, and work schedule together with potential unobserved common effects on the inter-relatedness of spousal stop-making decisions at the household level. The results show that the MOP model with a Clayton copula structure provides the best data fits and there is a very strong positive dependence among error terms of stop-making equations. Furthermore, the dependence among the maintenance activity propensities of household heads is asymmetric, with a stronger tendency of household heads to simultaneously have low maintenance activity levels than to simultaneously have high maintenance activity levels.

Modeling and Analysis of Complex Equipment Maintenance Dynamics

An equipment maintenance system is naturally a complex dynamical system. The effective mamanagement must be based on the knowledge of the system＇s intrinsic dynamics. And the strueture of the maintenance system determines its behavior. This paper analyzes the basic structures and elements of a maintenance system for complex multi-components equipment. The maintenance system is considered as a dynamic system whose behavior is influenced by its structure＇s feedback and interaction, and the system＇s available resources. Building the dynamical model with Simulink, we show some results about the maintenance system＇s nonlinear dynamics, ods. The model can be used for understanding and which operational adjustments of maintenance which are never given by stochastic process methdetermining maintenance system behavior, towards n of maintenance requirements and timely supply of maintenance resources can be made in a more informed way.

Modeling of HV Devices Maintenance

The paper presents an approach to mathematical modeling of maintenance procedures.With regard to the random characteristic of states changes and damage of electrical power devices,the maintenance models of these processes based on Markov random processes theory have been proposed.Simulations based on the proposed models concern the analysis of reliability and probability of damage of electrical power devices as a function of time.

A generic framework for qualifications of digital twins in maintenance

Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digital twin facilitates the diagnosis and prognosis of critical assets,forming the basis for smart maintenance planning and reducing downtime.However,there is a lack of standardized approaches for the qualifications of digital twins in maintenance,leading to low trustworthiness and limiting its application.This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars,namely fidelity,smartness,timeliness,integration,and standard compliance.We demonstrate the effectiveness of the framework through two case studies,showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance.Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently,leading to significant benefits in terms of cost reduction,performance improvement,and sustainability.

Pavement performance model for road maintenance and repair planning: a review of predictive techniques

This paper provides a review of predictive analytics for roads,identifying gaps and limitations in current methodologies.It explores the implications of these limitations on accuracy and application,while also discussing how advanced predictive analytics can address these challenges.The article acknowledges the transformative shift brought about by technological advancements and increased computational capabilities.The degradation of pavement surfaces due to increased road users has resulted in safety and comfort issues.Researchers have conducted studies to assess pavement condition and predict future changes in pavement structure.Pavement Management Systems are crucial in developing prediction performance models that estimate pavement condition and degradation severity over time.Machine learning algorithms,artificial neural networks,and regression models have been used,with strengths and weaknesses.Researchers generally agree on their accuracy in estimating pavement condition considering factors like traffic,pavement age,and weather conditions.However,it is important to carefully select an appropriate prediction model to achieve a high-quality prediction performance system.Understanding the strengths and weaknesses of each model enables informed decisions for implementing prediction models that suit specific needs.The advancement of prediction models,coupled with innovative technologies,will contribute to improved pavement management and the overall safety and comfort of road users.

基于“一中心四平台”的公立医院后勤运营管理实践研究

目的探讨基于“一中心四平台”的医院后勤运营管理模式成效。方法以医院智慧管理分级评估标准为依据,依托大数据、物联网、互联网+、人工智能等技术运用,打造后勤智慧运维管理中心以及设备管控信息化平台、安全防范信息化平台、能耗监测信息化平台、运营管理信息化平台的“一中心四平台”运营管理模式。结果经过样本医院的管理实践证明:基于“智慧联动”的设备故障处置能力得到显著提升,2022年故障报警次数同比2021年下降28.63%,其中高级、普通报警次数同比2021年分别下降69.53%、33.15%;基于“一站式”的后勤服务保障能力得到显著提升,2022年同比2021年维修次数下降2.92%,维修质量有所提高,反复维修频次降低;基于“数据挖掘”的能耗管控能力得到显著提升,2022年万元收入能耗支出同比2021年下降8.71%。结论“一中心四平台”可以显著提高后勤运维管理水平。

汽车故障知识图谱构建及应用研究

知识图谱技术对汽车高效的故障诊断具有重要的意义,现有汽车故障知识图谱构建存在着实体识别模型效果不佳、无法解决嵌套实体等问题。针对上述问题,通过采用全词掩码的预训练语义模型、加入对抗训练和改进嵌套实体识别模型的方式提高实体识别模型效果,提出了一种改进的嵌套实体识别模型。实验结果表明,所提模型F1值(F_(1))、精确率(P)和召回率(R)相比基线模型分别提高了3.56%、4.08%、3.05%,相比其他模型也有不同程度的提高,验证了所提模型对汽车维修领域实体识别具有显著效果。同时,基于构建的汽车故障知识图谱,实现了汽车故障知识智能问答原型系统,展示了知识图谱技术在汽车故障诊断与维护领域的应用前景。

维持性血液透析尿毒症患者动静脉内瘘急性血栓形成的危险因素分析及Nomogram预测模型构建

目的探讨维持性血液透析(MHD)尿毒症患者动静脉内瘘急性血栓形成的危险因素及Nomogram预测模型构建。方法选择2020年12月至2022年12月于新乡医学院第三附属医院门诊行MHD治疗的418例尿毒症患者为研究对象。根据动静脉内瘘是否形成急性血栓将患者分为急性血栓组(n=32)与非急性血栓组(n=386)。应用单因素及多因素logistic回归分析影响行MHD的尿毒症患者动静脉内瘘急性血栓形成的影响因素;根据尿毒症患者动静脉内瘘急性血栓形成的独立危险因素建立Nomogram预测模型,并应用Bootstrap来验证Nomogram模型的有效性。结果急性血栓组患者合并糖尿病患、合并低血压、透析时穿刺失败占比、钙磷乘积、超敏C反应蛋白(hs-CRP)、总胆固醇(TC)、低密度脂蛋白胆固醇(LDL-C)水平均显著高于非急性血栓组(P<0.05);logistic回归分析显示,糖尿病、低血压、透析时穿刺失败、钙磷乘积升高、高水平hs-CRP、高水平LDL-C是影响行MHD的尿毒症患者动静脉内瘘急性血栓形成的独立危险因素(P<0.05);依据6个独立危险因素构建了Nomogram预测模型,该模型的一致性指数为0.893(95%置信区间:0.833~0.928);且其校正曲线和标准曲线拟合较好,曲线下面积为0.918。结论糖尿病、低血压、透析时穿刺失败、钙磷乘积升高、高水平hs-CRP和LDL-C是行MHD的尿毒症患者动静脉内瘘急性血栓形成的危险因素,依据独立危险因素构建的Nomogram模型预测行MHD的尿毒症患者动静脉内瘘急性血栓形成的效果较好,有助于临床急性血栓形成患者的早期筛查。

维持性血液透析患者甲状旁腺切除术后早期骨饥饿综合征风险预测模型的构建与验证

目的:甲状旁腺切除术(parathyroidectomy,PTX)是治疗难治性继发性甲状旁腺功能亢进(secondary hyperparathyroidism,SHPT)的有效方法,但PTX后极易出现骨饥饿综合征(hungry bone syndrome,HBS),严重威胁维持性血液透析(maintenance hemodialysis,MHD)患者的生命健康。目前已有研究分析PTX后并发HBS的风险因素,但风险预测模型的预测性能和临床适用性仍待进一步验证。本研究旨在构建MHD伴SHPT患者PTX后并发HBS的风险预测模型,并验证其预测效果。方法:回顾性收集2020年1月至2021年12月在长沙捷奥肾病医院行PTX的MHD伴SHPT的368例患者为训练集,按照是否发生HBS分为HBS组和non-HBS组,对2组的一般资料、手术相关信息、生化指标等进行比较,应用多因素logistic回归筛选HBS的影响因素,建立风险预测模型。采用受试者操作特征(receiver operator characteristic,ROC)曲线、决策曲线、校准曲线对模型进行评价。收集2022年1至12月在中南大学湘雅三医院行PTX的MHD伴SHPT的170例患者为验证集进行外部验证。结果:MHD伴SHPT患者PTX后HBS发生率为60.60%,logistic回归分析结果显示:术前骨骼受累(OR=3.908,95%CI 2.179~7.171)、术前血钙(OR=7.174,95%CI 2.291~24.015)、术前全段甲状旁腺激素(intact parathyroid hormone,i PTH)(OR=1.001,95%CI 1.001~1.001)、术前碱性磷酸酶(alkaline phosphatase,ALP)(OR=1.001,95%CI 1.000~1.001)、术后第1天血钙(OR=0.006,95%CI0.001~0.038)是MHD患者伴SHPT行PTX后并发HBS的独立危险因素(均P<0.01)。构建的风险预测模型在内部训练集和外部验证集中均表现出良好的预测结果,内部验证集的准确度为0.821,灵敏度为0.890,特异度为0.776,约登指数为0.666,曲线下面积(area under curve,AUC)为0.882(95%CI 0.845~0.919);外部验证集的准确度为0.800,灵敏度为0.806,特异度为0.799,约登指数为0.605,AUC为0.863(95%CI 0.795~0.932)。结论:术前骨骼受累、术前血钙、术前iPTH、术前ALP、术后第1天血钙水平是MHD伴SHPT患者行PTX后并发HBS的影响因素,基于上述因素构建的风险预测模型可靠。

基于BIM和语义网的轨道智能运维管理方法

建筑信息模型(BIM)技术对提高轨道运维管理效率具有重要的推进作用。然而,不同的检查和维护活动产生的数据异构性高、时空关系复杂,阻碍了BIM解释和整合数据的进程。为此,开发了一个基于工业基础类(IFC)和语义Web技术的轨道运维本体(TOMO),其具有3个功能:①基于轨道运维生命周期的应用需求,简化BIM模型信息;②引入映射规则,建立数据提取与转换模块,集成多源异构数据,结构化定义数据之间复杂的时空关系;③结合数据驱动技术,研究轨道精调智能优化的方法,提供弹性决策支持。最后,以某高速铁路静检数据为例,验证了该框架的有效性与实用性,对于促进领域数据互操作性、降低运维人员劳动强度和提高运维管理智能化程度具有实际的工程指导意义。

医护-社工联动康复模式对美沙酮维持治疗患者心理状况的影响

目的 探究医护-社工联动康复模式对美沙酮维持治疗患者心理状况的影响。方法 纳入94例美沙酮维持治疗服务的患者,随机分为观察组(48例)和对照组(46例)。对观察组运用医护-社工联动康复模式进行个体化干预,对照组则运用常规美沙酮治疗服务模式进行干预。分别在干预前、干预3个月及6个月三个时间点对两组受试者的焦虑状态、抑郁状态及生活质量进行评估。结果 观察组受试者在接受医护-社工联动康复模式干预6个月后在抑郁状态和焦虑状态方面均较干预前显著改善,并且无论是BDI评分和BAI评分均显著低于对照组(P <0.05)。同时,观察组受试者中“有抑郁”的人数占比和“有焦虑”的人数占比均显著低于对照组(P <0.05)。干预6个月后,观察组受试者的生活质量评分(183.77±8.90)显著高于对照组(174.76±11.14)(P <0.01)。结论 医护-社工联动康复模式在改善美沙酮维持治疗患者的心理状态方面具有一定的优越性,值得被推广应用。