Recursive operation time maximization model for the maintenance of power generation equipment

Repairable equipment requires preventive maintenance (PM) to maintain proper function. An appropriate PM strategy can extend the life of equipment and reduce variable costs. A power generation company in Taiwan that has a fixed-period PM strategy is studied. However, a fixed-period PM strategy is usually not an optimal solution for maintaining equipment those ages gradually. An age-related dynamical model is designed for creating a timely maintenance schedule that extends the life of equipment and improves its efficiency. A recursive mathematical programming model that considers regular maintenance, emergent maintenance, and maintenance improvement factors is used to obtain the optimal equipment PM schedule. An empirical experiment with the nonperiodic PM schedule computed using the proposed method was conducted. Results show a significant reduction in the PM cost and an extension of the life of equipment.     

Context enabled decision aids to support the situation awareness and performance of risk engineers carrying out loss prevention surveys

Routine inspection by insurance companies at their clients’ facility, also known as loss prevention survey, help identify the best strategies to minimize damages when there is a high-speed wind event. More specifically, wind vulnerabilities associated with a building are evaluated using a process known as windstorm risk inspection. This routine inspection helps clients reduce the extent of damages caused by high-speed wind events including hurricane and tornado. Risk engineers make use of their subjective and analytical deduction skills to successfully carry out the inspection tasks. In this research the researchers investigated the effect of context-based visualization strategies on situation awareness and their understanding of the situation. The study examined how different types of information contribute towards the three levels of situation awareness. Following a between-subjects study design, 65 participants completed the study. Each session lasted 90–120 min. A checklist based and predictive display-based decision aids were tested and found to be effective in supporting the situation awareness requirements as well as performance of risk engineers. However, the predictive display only helped with certain tasks such as understanding the interaction among different components on the rooftop. For remaining tasks such as perceiving obvious issues like membrane tear, clogged drains and vegetation growth, checklist alone was sufficient. This study helped the understanding of the advantages and disadvantages of the decision aids tested. More specifically, these decision aids can improve the mental model of novice risk engineers. Additionally, this study provided insights that could help design training materials for infrastructure inspectors.     

Industrial cost modelling and multi-objective optimisation for decision support in production systems development

Recent developments in cost modelling, simulation-based multi-objective optimisation, and post-optimality analysis have enabled the integration of costing data and cost estimation into a new methodology for supporting economically sound decision-making in manufacturing enterprises. Within this methodology, the combination of production engineering and financial data with multi-objective optimisation and post-optimality analysis has been proven to provide the essential information to facilitate knowledge-driven decision-making in real-world production systems development. The focus of this paper is to present the incremental cost modelling technique specifically designed for the integration with discrete-event simulation models and multi-objective optimisation within this methodology. A complete example, using the simulation model and data modified from a previous real-world case study, is provided in this paper to illustrate how the methodology and cost modelling are applied for the optimal investment decision support.     

考虑发电能力匹配性的输变电设备检修优化方法

为保障电网电力供应能力,减少由于发电机组与输变电设备检修计划协调性不足导致的发电受限问题,提出了一种考虑发电能力匹配性的输变电设备检修优化方法。充分考虑发电机组检修及季节性能力变化与输变电设备检修计划间的协调关系,定义了发电能力匹配性指标。该指标取值大小反映了输变电设备检修与发电机组发电能力的匹配关系,数值越大,匹配性越高。以该指标最大化为优化目标,综合考虑输变电设备检修时段、电力电量平衡等约束条件,构建了考虑发电能力匹配性的输变电设备检修优化模型。根据模型特点,提出了求解方法。最后基于IEEE-30节点系统构造算例表明,本文所提出的方法能够避免发电机组检修与输变电设备检修不协调导致的发电能力下降,从而提升电网整体运行效益。     

局域网的运维管理特点与措施

本文首先分析了局域网运行维护成本管理的特点,然后通过项目管理所提供的理念与方法,介绍了局域网运行维护成本项目化管理的模式,希望能对局域网运营商企业其他管理活动的项目化管理提供一些借鉴。     

无线传感器网络设备维修周期决策及支持软件研究*

无线传感器网络设备因为数量庞大,维修维护事项庞杂,维修周期需要决策优化。基于状态维修理论研究了无线传感器网络设备面向节能减排的维修周期决策问题,给出了三类事项的费用模型和基于粒子群算法的智能优化方法;基于WinCC开发了维修决策支持软件系统、软件所集成的事项知识和所决策的维修时机,可以有效地指导无线传感器网络设备的维修工作。     

Empirical evidence,evaluation criteria and challenges for the effectiveness of virtual and mixed reality tools for training operators of car service maintenance

The debate on effectiveness of virtual and mixed reality (VR/MR) tools for training professionals and operators is long-running with prominent contributions arguing that there are several shortfalls of experimental approaches and assessment criteria reported within the literature. In the automotive context, although car-makers were pioneers in the use of VR/MR tools for supporting designers, researchers started only recently to explore the effectiveness of VR/MR systems as mean for driving external operators of service centres to acquire the procedural skills necessary for car maintenance processes. In fact, from 463 journal articles on VR/MR tools for training published in the last thirty years, we identified only eight articles in which researchers experimentally tested the effectiveness of VR/MR tools for training service operators’ skills. To survey the current findings and the deficiencies of these eight studies, we use two main drivers: (i) a well-known framework of organizational training programmes, and (ii) a list of eleven evaluation criteria widely applied by researchers of different fields for assessing the effectiveness of training carried out with VR/MR systems. The analysis that we present allows us to: (i) identify a trend among automotive researchers of focusing their analysis only on car service operators’ performance in terms of time and errors, by leaving unexplored important pre- and post-training aspects that could affect the effectiveness of VR/MR tools to deliver training contents – e.g., people skills, previous experience, cibersickness, presence and engagement, usability and satisfaction and (ii) outline the future challenges for designing and assessing VR/MR tools for training car service operators.     

考虑劣化状态的单机调度与维修决策集成模型

大多数研究单机调度与维修决策集成问题的文献采用基于役龄的维修策略. 然而, 设备劣化状态与加工对象、加工环境和加工时间等诸多因素相关. 鉴于此, 针对设备状态可检测的系统, 采用非完美预防性视情维修、小修与故障更换相结合的维修策略, 建立一种以加工作业次序和预防维修阈值为决策变量, 加工作业的总加权期望完成时间最小为优化目标的随机期望值集成模型. 实验结果表明, 所提出的模型能更有效地避免过维修或欠维修, 并且能够降低生产持有成本.

     

联合作战指控系统效能评估仿真研究

针对联合作战指挥控制系统功能组成和特点,分析并构造了指挥控制系统的效能评估指标体系。探讨了效能评估的主要方法,根据联合作战的特点,采用了作战模拟法,设计并实现了指挥控制系统效能评估试验框架。     

导弹武器效能评估系统的设计与实现

本文介绍了一种导弹武器效能评估系统的设计与实现,利用Visual C＋＋6.0和Oracle开发完成,采用模块化结构,用对ADO对象的封装类实现数据库接口,实现了对导弹武器效能的评估。该系统在对导弹武器效能的评估和辅助决策方面都有重要的现实意义。     

Joint determination of lease period and preventive maintenance policy for leased equipment with residual value

This paper investigates the influence of the length of the lease period on the maintenance policy for leased equipment with residual value. The length of the lease period increases, however, the lessor’s income increases, and the maintenance cost of the equipment rises as well. Therefore, the lease payment and maintenance service of the equipment are crucial items in the lease contract for the lessor’s profit. If the equipment breaks down within the lease period, minimal repairs will be performed on the equipment and the lessor may incur a penalty cost if the repair time exceeds a pre-specified tolerable time. The imperfect preventive maintenance (PM) actions are carried out when the age of the equipment reaches a controlled-limit during the lease period. Under this maintenance scheme, the mathematical model of profit is constructed and then the optimal maintenance policy and the length of the lease period are obtained such that the expected total profit is maximized. Finally, numerical examples are given to illustrate the effects of the optimal length of the lease period and the maintenance policy for profit model.     

线程切换开销分析工具的设计与实现

在多片多核计算机系统中,线程切换的间接开销受到体系结构、负载模式和调度策略的影响,为了获得更为稳定的测试结果,在分析Lmbench测试程序框架和进程切换测试原理的基础上,针对多片多核处理机系统中的线程测试需求,通过集成多种负载模式和调度策略,设计和实现了新的线程切换延时测试程序LTC,为多核系统下的线程切换延时测试与分析提供了有效手段。     

基于指标相关性的网络运维质量评估模型

传统网络运维评估方法存在两方面的问题：一是在指标选取、权重指定等关键步骤过于依赖领域专家经验,难以得到精确全面的评估结果;二是通信设备用户数量不断增加带来了海量的数据,数据又来自多个厂家以及多种设备,传统方法处理此类海量异构数据的效率较低。为了解决这些问题,提出基于指标间互相关性的指标选取方法。该方法着眼于评估过程中指标选取步骤,通过比较指标数据序列间的相关性强弱,对原始指标集进行分类,在各个簇中选择代表性指标完成关键指标体系的构建;另外,结合无人工参与的数据处理方法、权重确定方法建立了网络运维质量评估模型。在实验中,所提方法选取的指标对人工指标的覆盖率为72.2%,并且比人工指标的信息重叠率少31%。所提方法能够有效减少人力参与,且评估结果对告警有较好的预测准确率。     

非侵入式车载ATC设备在线检测运维系统方案设计

列车运行控制系统中,车载ATC(Automatic Train Control)设备行车日志里记录着各子系统的整个运行周期的全部信息,分析行车日志是监测车载设备状态和分析系统故障的重要手段。但在实际维护中存在以下问题：1. 设备实际输入输出和传感器电气工作状态信息中隐含大量故障特征信息,而这些信息在既有的车载信号系统中没有有效记录;2.行车日志收集依靠人工,效率低,成本高;3.故障诊断依靠经验,诊断结果具有局限性。在此基础上,本文提出一种非侵入式车载信号设备在线检测运维系统方案,该方案利用非接触式传感器采集信号,行车日志使用车地无线通信网络传输,通过地面服务器大数据分析,以达到对各子系统和关键零部件进行状态监测,并对异常信息进行预警的目的。     

Use of (max, +) algebra for scheduling and optimization of HVLV systems subject to preventive maintenance

High-Variety, Low-Volume (HVLV) manufacturing systems are built to produce parts of several types in small quantities and under multiple production objectives. They relate to job-shop systems well known by researchers. One of the most studied assumptions of HVLV systems scheduling is considering that machines may be periodically unavailable during the production scheduling. This article deals with an analytical integrating method using (max, +) algebra to model HVLV scheduling problems subject to preventive maintenance (PM) while considering machines availability constraints. Each machine is subject to PM while maintaining flexibility for the start time of the maintenance activities during the planning period. The proposed model controls the placement of maintenance activities along the production operations. Indeed, the sequencing of maintenance activities on the machines depends on the criteria to minimize and may be different for each criteria value. For preventive maintenance, the proposed model aims to generate the best sequencing between activities while respecting the planning program that satisfy the optimal criteria values. In order to illustrate the performance of the proposed methodology, a simulation example is given.     

面向拆装训练的输油泵机组虚拟维修系统设计

针对输油泵机组实装维修训练存在的不足,设计了面向拆卸与装配训练的输油泵机组虚拟维修系统。通过现有主流虚拟现实仿真平台的对比,选择以Unity3D作为开发平台。分析了系统功能、性能需求,设计了系统多层次模块化训练体系结构。针对系统交互式拆装的核心功能需求,提出一种高效的鼠标拖拽时零部件位置更新算法;为在虚拟训练过程中正确模拟机械零部件拆装的顺序关系,研究了基于事件驱动编程的设计方法。对系统实际运行参数进行测试,满足各项功能、性能需求。系统不仅满足输油泵机组维修训练的需求,还可为其它产品的维修拆装训练系统设计提供参考。     

Two-level and hybrid ensembles of decision trees for high performance concrete compressive strength prediction

Accurate prediction of high performance concrete (HPC) compressive strength is very important issue. In the last decade, a variety of modeling approaches have been developed and applied to predict HPC compressive strength from a wide range of variables, with varying success. The selection, application and comparison of decent modeling methods remain therefore a crucial task, subject to ongoing researches and debates. This study proposes three different ensemble approaches: (i) single ensembles of decision trees (DT) (ii) two-level ensemble approach which employs same ensemble learning method twice in building ensemble models (iii) hybrid ensemble approach which is an integration of attribute-base ensemble method (random sub-spaces RS) and instance-base ensemble methods (bagging Bag, stochastic gradient boosting GB). A decision tree is used as the base learner of ensembles and its results are benchmarked to proposed ensemble models. The obtained results show that the proposed ensemble models could noticeably advance the prediction accuracy of the single DT model and for determining average determination of correlation, the best models for HPC compressive strength forecasting are GB–RS DT, RS–GB DT and GB–GB DT among the eleven proposed predictive models, respectively. The obtained results show that the proposed ensemble models could noticeably advance the prediction accuracy of the single DT model and for determining determination of correlation (R²_max), the best models for HPC compressive strength forecasting are GB–RS DT (R²=0.9520), GB–GB DT (R²=0.9456) and Bag–Bag DT (R²=0.9368) among the eleven proposed predictive models, respectively.     

钢铁企业全厂仪表维修设施设计初探

以我国某大型钢铁企业全厂仪表维修设施的设计方案为例,简要说明了仪修设施的设计原则、全厂仪表维修的一般解决方案,较详细地介绍了仪修设施专业划分、实验室及维修车间的设置和主要设备构成,为该类项目的设计和工程建设提供一定参考。