工程装备虚拟维修技术研究现状与展望

目的 针对工程装备设计的维修性难以验证,维修训练面临装备昂贵、不易重复拆卸、危险性高等问题,运用虚拟维修技术来评估装备的维修性和开展维修训练。方法 进行文献分析,理清虚拟维修的研究范畴和热点,从维修性设计、维修训练两个应用层面和虚拟人技术、虚拟样机及环境技术、维修过程与交互技术、维修性评估技术四个关键技术层面入手,对相关研究成果进行了整理和综述。结论 分析了目前研究存在的不足,提出了还可以进一步发展基于传感器技术的沉浸式交互方式,完善核心软件技术,研究多人协同维修与团体评估方法。     

Training of the maintenance personnel to prevent failures in aircraft systems

The aircraft maintenance process plays a vital role in aviation safety. The quality of the maintenance process and the qualifications of the aircraft maintenance personnel are important factors in the safety of aircraft.In this study the aircraft maintenance training model has been developed by especially taking in to account the EASA Part 66 regulations. The progression of the aircraft maintenance personnel training was investigated and suggestions to improve training process were given so as to prevent failures in aircraft systems.     

Improving aircraft safety and reliability by aircraft maintenance technician training

Aircraft maintenance is one of the primary causes or contributing factors in aircraft accidents. It is clear that proper training of Aircraft Maintenance Technicians (AMTs) will avoid failures, reduce maintenance related accidents, improve safety and reliability in aviation and provide recovery of the increasing demand to qualified AMTs for sustainability of the market growth. In this study, European Safety Agency (EASA) based AMT licencing system in EU states (and non-EU states implementing EASA rules) has been analysed and a training model developed in accordance with EASA Part-66 requirements and delivered by e-learning methods has been introduced. The analysis of the licensing process based on EASA regulations showed that this process was based on the candidate's demonstration of knowledge and acquisition of experience. The required experience depends on the training background of the candidate. Field exercise showed that developed e-learning training model, which overcomes the disadvantages of traditional face to face training models, succeeded to improve the attendees' theoretical knowledge level and when combined with the practical trainings given to AMT candidates in maintenance organisations during their experience periods, will be very successful in improving safety and reliability in aviation maintenance operations.     

On Syllabus Design for the Specialty of Electromechanical Equipment Maintenance and Management in Vocational College

1 IntroductionWith the development of vocational education, the establishment of scienhfic and Prachcalsyllabus suitable for such education has already become a vita need. Since we staxted thespecialty of electromechanical equipment maintenance & management in 1994, we have carriedout intensive inveshgation in order to design a Prope syllabus.2 Syllabus design should achieve the training objective Of the specialty andadjust to the demand of societyVocational education belongs to apPlied high…     

基于机会维修策略的预防性维修优化模型研究

为了利用系统内故障部件维修的机会,考虑部件之间在维修方面存在的相关性情况,提出了将机会维修信息融入系统预防性维修的优化模型．该模型在比较按机会预防性维修和按计划预防性维修期望效益的基础上,以系统内故障时机为优化变量、部件维修费用率最小化为目标进行系统预防性维修优化,使确定部件在不同的故障来源时机可提前预防性维修的阈值．最后通过算例,表明不同故障的机会维修阈值对部件预防性维修效果的影响差异,为系统预防性维修决策提供有力的支持．     

考虑维修场所的动车组多部件双目标成组维修研究

为探究维修场所选择对动车组多部件维修策略制定的影响,综合考虑维修方式、维修场所类别和维修人员等因素,以减少维修成本和维修时间为目标,建立了考虑维修场所的动车组多部件双目标成组维修模型。首先,在两级非完美维修方式的基础上,引入维修场所对维修方式的约束,通过维修场所的选择进一步选择维修方式。然后,提出一种部件维修任务分配算法,实现了维修人员与部件维修任务的优化匹配,使得系统维修时间最短;同时,将该算法引入到遗传算法中,用于求解考虑维修场所和系统维修时间的成组维修模型。实例分析表明,所提出的维修策略在满足动车组部件可靠度要求的前提下,减少了系统的维修成本和维修时间。研究结果可为合理制定动车组维修策略提供理论参考。     

The Method of Mission Oriented Maintenance

In a real application,equipment in good condition sometimes have to be repaired because the equipment does not satisfy the requirements of the mission; However, it is not necessary to repair some equipment with failures because the failures do not affect the mission completion. In these cases, maintenance activity guided by present maintenance methods may sometimes affect the mission completion in time or bring about extra maintenance. To over-come the shortage of present maintenance methods, we propose an idea and method of mission oriented maintenance (MOM) to deal with the maintenance policy on these kinds of prob-lems. This method can work out different maintenance policies corresponding to different missions with full consideration of missions and mission requirements for the equipment.     

Analysing Operating Data to Measure the Maintenance Performance*

Effective maintenance decision‐making depends on information obtained by analysing system operating data. In this paper, we present a method to measure the daily, weekly, monthly and long‐term performance of the corrective repair and preventive maintenance by analysing the operating data. Operating data from a bus fleet, served successively in two routes, were observed for over 6 years. The proportional intensity model is used to evaluate the environment effects, which include temperature, humidity and rainfall. Two composite models are proposed to analyse the interplay of events, which include repair/maintenance arrival/finished time, cost, repair/maintenance number and time between failures. A maintenance performance scorecard is developed to present a snapshot of the bus fleet maintenance performance, which can assist maintenance planning and management. Copyright © 2014 John Wiley & Sons, Ltd.     

虚实融合的协同工作环境CAR-CA工程技术研究进展

采用虚实融合和协同工作技术进行大型装备的设计论证和辅助拆装维护是工程科技发展的一个新方向。面向我国自行设计生产商用大飞机的需求,在863计划支持下,正在研制用于驾驶舱布局设计和飞机关键部件辅助拆装维护的虚实融合协同工作环境CAR—CA（collaborative augmented reality for commercial aircraft design ＆ maintenance）。概要介绍CAR—cA的工程技术研究进展,包括体系结构、系统组成、关键技术研究和系统的应用前景等。     

An Analysis of the Deferences between Old and New Maintenance Concepts

Beforethe'50s,maintenancemainlywasakindofskillandwasshortofagUidetoSystematictheoryandmaintenanceprocesswasakindofrewordathardtime.AsdevelOPmentofdelveofintellectUalization,automationofequipment,maintenancecostrosesteeply.Availabilitywascontinuouslydecreasing,andexistingmaintenanceProcesscouldnotadapttoobjectiverequirements.From1960,thecivilaviationofAmericahadexploredthebasiclawofaoplanemaintenanceintheuseofmodemsciencetechnology[l].UPtothelate'6()s,reliability-centeredmaintenancetheorywa…     

Research on Selection of Equipment Maintenance Modes

1 IntroductionEquipment failure will inevitably occur during a normal production process.Severe equipment failurewill conduce long time deadlock of a production system,lower production efficiency,and add extracost on products.Effective strategy should be adopted so as to reduce failure influence on equipment,reduce production cost and enhance market competition of products.In recent years,high-tech pro-duction equipment are improved,and production rates are more rapid.For the sake of maintain…     

Transfer learning based deep learning model and control chart for bearing useful life prediction

The remaining useful life (RUL) of the machine is one of the key information for predictive maintenance. If there is a lack of predictive maintenance strategy, it will increase the maintenance and breakdown costs of the machine. We apply transfer learning techniques to develop a new method that predicts the RUL of target data using degradation trends learned from complete bearing test data called source data. The training length of the model plays a crucial role in RUL prediction. First, the exponentially weighted moving average (EWMA) chart is used to identify the abnormal points of the bearing to determine the starting point of the model's training. Secondly, we propose transfer learning based on a bidirectional long and short-term memory with attention mechanism (BiLSTMAM) model to estimate the RUL of the ball bearing. At the same time, the public data set is used to compare the estimation effect of the BiLSTMAM model with some published models. The BiLSTMAM model with the EWMA chart can achieve a score of 0.6702 for 11 target bearings. The accuracy of the RUL estimation ensures a reliable maintenance strategy to reduce unpredictable failures.     

The influence of condition-based maintenance on workforce planning and maintenance scheduling

Condition-based maintenance (CBM) is generally considered an attractive maintenance policy for a single component: it uses the operating condition of the component to predict a failure event and therefore tries to avoid any unplanned downtime and unnecessary maintenance activities. However, operations managers tend to be much more interested in optimising the performance of the entire asset-system, where the grouping of maintenance activities and the availability of maintenance workers may play a role. Therefore, this paper focuses on the impact of using either CBM or age-based replacement (ABR) in serial and parallel multi-component systems (1) without worker constraints, (2) with a single internal maintenance worker, and (3) with external maintenance workers with a significant response time. With an internal maintenance worker, the sequential execution of maintenance activities prevents efficiency gains in the serial configuration and here CBM performs better. Also in the parallel configurations, the efficiency under CBM is generally better than under ABR. However, with external maintenance workers, CBM is not able to group maintenance activities as well as ABR, which results in a lower efficiency in the serial configuration. CBM performs better than ABR with respect to total maintenance costs, while ABR results in a smoother maintenance plan.     

Selective maintenance scheduling under stochastic maintenance quality with multiple maintenance actions

Many systems are required to perform a series of missions with finite breaks between any two consecutive missions. To improve the probability of system successfully completing the next mission, maintenance action is carried out on components during the breaks. In this work, a selective maintenance model with stochastic maintenance quality for multi-component systems is investigated. At each scheduled break, a set of maintenance actions with different degrees of impact are available for each component. The impact of a maintenance action is assumed to be random and follow an identified probability distribution. The corresponding maintenance cost and time are modelled based on the expected impact of the maintenance action. The objective of selective maintenance scheduling is to find the cost-optimal maintenance action for each component at every scheduled break subject to reliability and duration constraints. A simulated annealing algorithm is used to solve the complicated optimisation problem where both multiple maintenance actions and stochastic quality model are taken into account. Two illustrative numerical examples and a real case study have been solved to demonstrate the performance of the proposed approach. A comparison with deterministic maintenance shows the importance of considering the proposed stochastic quality in selective maintenance scheduling.     

The Research State and Problems Needing Study of Green Maintenance

1 IntroductionMaintenance is a basic industry in our country; its range is very wide from small components repair to huge ships maintenance. Reasonable repair for broken-down equipment or components can reduce resource waste and lengthen the life of the products. From this aspect, maintenance has the benefit for protecting the environment and sustaining development. But maintenance also consumes energy and resources; unreasonable maintenance can produce injury and solid waste. Examples are in…     

Analysis of the Improvement Methods for Equipment Maintenance Support

According to military requirement, and based on the problems of equipment maintenance support methods in high-tech battles, each element supporting equipment maintenance is analyzed, and the methods for improving equipment maintenance are proposed.     

Applying RCM in large scale systems: a case study with railway networks

In 2000, the European Union founded a project named ‘RAIL: Reliability centered maintenance approach for the infrastructure and logistics of railway operation’ aimed to study the application of Reliability centered maintenance (RCM) techniques to the railway infrastructure. In this paper, we present the results obtained into the RAIL project, including a RCM methodology adapted to large infrastructure networks and a RCM toolkit to perform the RCM analysis, including cost aspects and maintenance planning guidance. This paper addresses the problem of applying RCM to large scale railway infrastructure networks to achieve an efficient and effective maintenance concept. Railways use nowadays very traditional preventive maintenance (PM) techniques, relying mostly on ‘blind’ periodic inspection and the ‘know-how’ of maintenance staff. RCM was seen as a promising technique from the beginning of the RAIL project because of several factors. First, technical insights obtained were better than the existing, so that several maintenance processes could be revised and adjusted. Second, the interdisciplinary approach used to make the analysis was very enriching and very encouraging for maintenance staff consulted. Third, using the RCM structured approach allowed to achieve well-documented analysis and clear decision diagrams. Our methodology includes some new features to overcome the problems of RCM observed in other projects. As a whole, our methodology and Computerized Maintenance Management Systems have produced two short-term benefits: reduction of time and paperwork because databases and tools are accessible through Internet, and creation of a permanent, accurate, and better collection of information. It will also have some long-term benefits: better PM will increase equipment life and will help to reduce corrective maintenance costs; Production will increase as unscheduled downtime decreases; purchase costs of parts and materials will be reduced; more effective and up-to-date record of inventory/stores reports; and better knowledge of the systems to help the company to chose those systems with the best LCC. The results have been corroborated with the application of our methodology to signal equipment in several railway network sections, as shown in this paper. Because of the successful conclusion of the project, the Spanish railway company (RENFE) and the German railway company (DB A.G.), not only decided to adopt RCM to enhance PM, but they have started a large project to implement Total Preventive Maintenance relying on the implantation of the RCM methodology.     

A developed autonomous preventive maintenance programme using RCA and FMEA

Total productive maintenance (TPM) was developed in Japan in 1971 and has since been phased into many manufacturing firms to promote productivity and competitiveness. Autonomous preventive maintenance (APM) systems are very special. The fundamental pillar of TPM includes a series of important systematical first-line direct labour activities. The technical cost, human resources and management issues are all considered. Failure modes and effects analysis (FMEA) and root-cause analysis (RCA) are the most popular failure analytical methods, widely adopted over different industries. They are often used to examine the potential problems in the design and manufacturing phase, discovering possible failure causes before product design and manufacturing finalisation. This study integrates the RCA and FMEA techniques to establish an APM system that meets a company’s goal of reducing manufacturing costs and promoting employee and equipment productivity. The major contribution of this study is constructing potential equipment failure modes and their risk priority number through RCA and FMEA integration transformed into a selection of items and their APM maintenance frequencies. A strategy for deploying employee technical capability upgrade through effective training is developed. This study uses the S Company – a key manufacturer of semiconductor material – as a case study to verify the model’s applicability and suitability.     

Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation

This paper tries to integrate sequential imperfect maintenance policy into condition-based predictive maintenance (CBPM). A reliability-centered predictive maintenance policy is proposed for a continuously monitored system subject to degradation due to the imperfect maintenance. It is assumed that the system hazard rate is a known function of the system condition and then can be derived directly through CBPM. A hybrid hazard rate recursion rule based on the concept of age reduction factor and hazard rate increase factor is built up to predict the evolution of the system reliability in different maintenance cycles. Whenever the system reliability reaches the threshold R, an imperfect preventive maintenance (PM) is performed on the system. The optimal reliability threshold R is determined by minimizing the cumulative maintenance cost per unit time in the residual life of the system which is based on simulation. Finally, a discussion is presented to show how the optimal results depend on the different cost parameters.     

Imperfect Preventive Maintenance Policy for Complex Systems Based on Bayesian Networks

The main challenge in maintenance planning lies in the realistic modeling of the maintenance policy. This paper is focused on the maintenance optimization of complex repairable systems using Bayesian networks. A new policy is developed for periodic imperfect preventive maintenance policy with minimal repair at failure; this policy allows us to take into consideration several types of preventive maintenance with different efficiency levels. The Bayesian networks are used for complex system modeling, allowing the evaluation of the model parameters. The Weibull parameters and the maintenance efficiency are evaluated thanks to the proposed methodology using Bayesian inference. The approach developed in this paper is applied on a real system, to determine the optimal maintenance plan for a turbo‐pump in oil industry. Copyright © 2016 John Wiley & Sons, Ltd.