基于半马尔科夫决策过程的风力机状态维修优化

恶劣的工作环境、昂贵的维修成本和停机损失对风力机及其部件的维修提出挑战。以齿轮箱、叶片等风力机核心机械部件为对象,将部件退化过程离散成有限的退化状态;以长期折扣成本最低为目标,考虑风速、备件物流、停机损失等因素的影响,建立基于半马尔科夫决策过程的状态维修优化模型。分析各退化状态下的维修策略、检测间隔时间以及不同退化状态间的转移概率,并采用策略迭代算法求解模型。以某风力机齿轮箱为例,通过对等周期、非等周期检测条件下检测间隔时间和维修成本的分析,得到优化的维修决策。研究结果表明,该模型能有效描述风力机核心部件的退化过程,实现风力机维修优化。     

如何通过加强设备管理优化备件库存控制

从备品备件信息、维修模式、维修现场需求等方面入手,分析维修备件系统与一般零件库存系统的区别,从设备管理的角度出发,研究设备信息、PM工作、设备状态监测及仓库布局优化对备件库存的影响,得出通过加强设备管理达到优化备件库存控制的方法。     

[数据驱动的智能服务]数据驱动的复杂产品智能服务技术与应用

随着传感器、数据采集装置和其他具备感知能力的模块在复杂产品服务运行阶段的应用,复杂产品运维系统的数字化和智能化程度越来越高,具有实时、多源、异构、海量等特性的数据成为提高复杂产品系统可靠和低成本运行的决策依据,数字孪生技术提供了一种有效途径。介绍了数据驱动的复杂产品智能服务研究进展;分析了数据驱动的智能服务基本特征与框架模型;提出了数据驱动的复杂产品智能服务方法,主要包括面向服务的复杂产品建模与仿真方法、数据驱动的服务需求获取与精准分析预测方法、基于数字孪生的设备故障识别与动态性能预测方法、数据驱动的装备视情维修与备件库存联合多目标决策优化方法、基于数字孪生的复杂产品辅助维修技术、多要素协同的复杂装备能效精准分析预测方法、基于数据挖掘的复杂产品运行优化控制方法等;给出了智能服务系统的应用案例。所提出的框架和方法可为现代制造服务的智能化转型升级提供参考。     

Application of an efficient modified particle swarm optimization algorithm for process planning

In the modern manufacturing system, many flexible manufacturing system and NC machines are introduced to improve the production efficiency. Therefore, most parts have a large number of flexible process plans. However, a part can use only one process plan in the manufacturing process. So, the process planning problem has become a crucial problem in the manufacturing environment. It is a combinatorial optimization problem to conduct operations selection and operations sequencing simultaneously with various constraints deriving from the practical workshop environment as well as the parts to be processed. It is a NP-hard problem. In order to solve this problem effectively, this paper proposes a novel modified particle swarm optimization (PSO) algorithm to optimize the process planning problem. To improve the performance of the approach, efficient encoding, updating, and random search methods have been developed. To verify the feasibility and effectiveness of the proposed approach, seven cases have been conducted. The proposed algorithm has also been compared with the genetic algorithm and simulated annealing algorithm. The results show that the proposed modified PSO algorithm can generate satisfactory solutions and outperform other algorithms.     

Joint decision making for maintenance and production scheduling of production systems

Deteriorated equipment has a significant impact on the product quality and maintenance policies. In this paper, we present a decision-making architecture to determine maintenance and product dispatching policies based on condition-monitoring information and the relationship between machine degradation and associated product quality. We use a Markov decision process for the long-term decision making and integer programming for the short-term decision making with a multi-product, multi-station system. We demonstrate the advantage of the proposed approach by comparing the proposed policy with traditional decision-making approaches. Furthermore, we illustrate the improvement of the proposed policy over the current usage-based maintenance policy with a semiconductor manufacturing process application.     

Maintenance Integration in Manufacturing Systems: From the Modeling Tool to Evaluation

In manufacturing systems, wear-out and eventual failure are unavoidable. However, to reduce the rate of their occurrence and to prolong the life of equipment or the capacity for extended productive use of the equipment under the necessary technological functioning and servicing, maintenance can be performed. For large manufacturing systems, maintenance integration involves a particular development concerned with both complexity models and computing time. This paper presents an effective way of modeling complex manufacturing systems through hierarchical and modular analysis by using stochastic Petri nets and Markov chains. In the proposed approach, the integration of maintenance policies in a manufacturing system is facilitated by the development of a generic model. With this generic modeling, the user doesn't need to code the strategies but only to instantiate the generic model with the structure of the manufacturing system. This method allows various maintenance strategies to be coded in the generic model with the aim of studying their influence on system dependability and performance.     

基于METRIC的民机初始备件数量确定及配置模型

针对航空公司备件保障中如何以合理备件费用最大化机队可用度问题,根据维修组织结构及备件送修过程在建模过程中的影响,建立了基于METRIC(multi-echelon technology for recoverable item control)理论的多级库存优化模型。首先,分析了两级库存系统中备件的状态转移流程;其次,根据波音模型的求解过程,对比给出多级库存模型;再次,以备件短缺总量为目标、费用为约束,利用边际分析法进行多级库存优化求解;最后,以某航空公司购买的波音737-800的初始备件为对象,运用METRIC理论对其数量进行优化,并分别以相同费用或相同的总短缺量为条件进行对比,结果证明了METRIC模型的优越性。     

Planning performance based contracts of repairable system using discrete event simulation

This paper investigates a discrete event simulation approach for managing performance based contracts of repairable systems. We focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose a simulation model to calculate system availability comprehending four performance drivers: life time distribution, repair time distribution, spare parts inventory, and repair facility. This simulation model allows the service supplier to minimize the total cost by optimizing the four performance drivers. In this simulation model, the failure time and repair time can follow arbitrary distribution. This will allow the customer to monitor the supplier’s service through comparing the actual availability and its theoretical value. The costs of three maintenance policies also can be studied under the performance based contracts framework. Two cases are considered in this paper. One is a system containing single unit, one warehouse, and one repair center. Another is a system containing two fleets with different installed units, two spare part warehouses with one for each fleet, and a central repair depot.     

基于剩余寿命的备件管理研究

备件管理的好坏直接影响着设备维修时间、维修质量、设备的可开动率以及设备的正常运行,而且进一步影响到企业产品的产量、质量、成本、交货期、安全和环保等诸多方面。由于备件管理系统涉及因素多,在有些情况下,现有的解析方法目前还不能解决这些问题。因此,我们运用剩余寿命预测法对维修管理系统进行研究,以便更全面地解决备件管理中遇到的主要问题。本文以齿轮为例说明了基于剩余寿命备件管理的基本思路和方法。     

基于企业工艺BOM和CAPP平台的产品售后维修信息化系统

针对某矿用汽车制造公司售后维修服务现状,提出在ERP中工艺BOM基础上科学构建维修BOM新模块.充分利用ERP和CAPP信息平台,进行维修技术和维修资源电子信息化管理,解决了长期存在的配件和备件相对滞后、产品大修流程不畅等维修服务问题,也解决了由于矿车制造数据与维修服务数据不同步而产生的问题.维修流程优化再造,实现了该公司矿车产品的维修技术、电子信息化技术和公司管理的初步融合,使维修服务质量高、效率高.开发和推广应用维修BOM信息系统,对矿车售后服务延伸价值链、保障矿车在工况中的安全运营、提高企业的可持续发展和更高获利能力具有重要意义.     

[智能设计与计划调度]大数据在设备健康预测和备件补货中的应用

提出了一种设备健康预测和库存优化方法。使用自编码器提取监测信号特征,基于深度神经网络模型进行时序预测,构建设备健康度指标;采用统计分布判定和参数拟合的预测方法实现库存优化;最后,根据设备健康状态与备件数量实现生产主动预警。实例结果表明,该方法预测精度高于LSTM算法,可对设备故障进行精确预警,且备件库存优化模型的可靠性高达90.4%,可有效减少备件库存。     

基于脆弱性的制造设备故障智能诊断与维护

制造设备故障智能诊断与维护是保障制造系统安全运行的重要手段。为准确地诊断制造设备的健康状态、识别设备故障的关键因素,建立高效的健康维护系统,提出了基于脆弱性的设备故障智能诊断与维护方法。该方法将考虑脆弱性的设备故障智能诊断与维修决策模块嵌入到设备的过程控制系统(Process control system,PCS)中,它基于系统脆弱性的定义和性能劣化理论建立了设备脆弱性评估模型实时判断设备的脆弱状态,利用非线性核映射方法实时监测制造设备的运行参数是否超出预设边界,建立设备参数的高斯核函数模型准确识别故障的关键因素,将设备的脆弱性状态与维护模式相结合建立维修决策模型避免维修过度和维修不足。以某机器人的伺服系统为例,证实了所提方法能有效提高故障诊断效率、智能化诊断故障因素,优化设备维修决策。     

维修决策建模和优化技术综述

对国内外在维修决策建模及其优化研究领域取得的进展和研究现状进行了综述。以视情维修为重点,从维修策略、维修决策建模方法、维修决策优化方法、维修效果建模、系统状态不完全可观以及维修备件的库存和定购问题等几个方面对维修决策模型理论研究现状进行了介绍。最后论述了维修决策建模和优化技术的应用现状,并指出了当前该技术在理论和应用方面存在的问题。     

Intelligent Predictive Decision Support System for Condition-Based Maintenance

The high costs in maintaining today’s complex and sophisticated equipment make it necessary to enhance modern maintenance management systems. Conventional condition-based maintenance (CBM) reduces the uncertainty of maintenance according to the needs indicated by the equipment condition. The intelligent predictive decision support system (IPDSS) for condition-based maintenance (CBM) supplements the conventional CBM approach by adding the capability of intelligent condition-based fault diagnosis and the power of predicting the trend of equipment deterioration. An IPDSS model, based on the recurrent neural network (RNN) approach, was developed and tested and run for the critical equipment of a power plant. The results showed that the IPDSS model provided reliable fault diagnosis and strong predictive power for the trend of equipment deterioration. These valuable results could be used as input to an integrated maintenance management system to pre-plan and pre-schedule maintenance work, to reduce inventory costs for spare parts, to cut down unplanned forced outage and to minimise the risk of catastrophic failure.     

Maintenance scheduling to support the operation of manufacturing and production assets

Manufacturing and production plants operate physical assets that deteriorate with usage and time, thus, maintenance actions are required to restore the assets back to their original predetermined operational conditions. In this paper, we extend previous work on maintenance scheduling to considering a multi-component system that optimises both cost and reliability simultaneously. The model uses the concept of imperfect maintenance and includes factors such as ageing due to the operation rate of the system, downtime for maintenance and lead time for spare parts. For each maintenance planning period, the model predicts which of the three possible actions (namely, maintaining the component, replacing the component or doing nothing) for each component should be taken, such that the reliability is at least at a required level and the net present cost for the entire planning period is minimised. The entire approach is illustrated through the use of a numerical example and the evaluation of the model is done by using an evolutionary algorithm.     

Determination of Surface Roughness in Wire and Arc Additive Manufacturing Based on Laser Vision Sensing

Wire and arc additive manufacturing(WAAM) shows a great promise for fabricating fully dense metal parts by means of melting materials in layers using a welding heat source. However, due to a large layer height produced in WAAM, an unsatisfactory surface roughness of parts processed by this technology has been a key issue. A methodology based on laser vision sensing is proposed to quantitatively calculate the surface roughness of parts deposited by WAAM.Calibrations for a camera and a laser plane of the optical system are presented. The reconstruction precision of the laser vision system is verified by a standard workpiece. Additionally, this determination approach is utilized to calculate the surface roughness of a multi-layer single-pass thin-walled part. The results indicate that the optical measurement approach based on the laser vision sensing is a simple and effective way to characterize the surface roughness of parts deposited by WAAM. The maximum absolute error is less than 0.15 mm. The proposed research provides the foundation for surface roughness optimization with different process parameters.     

Determination of Surface Roughness in Wire and Arc Additive Manufacturing Based on Laser Vision Sensing

Wire and arc additive manufacturing (WAAM) shows a great promise for fabricating fully dense metal parts by means of melting materials in layers using a welding heat source. However, due to a large layer height produced in WAAM, an unsatisfactory surface roughness of parts processed by this technology has been a key issue. A methodology based on laser vision sensing is proposed to quantitatively calculate the surface roughness of parts deposited by WAAM. Calibrations for a camera and a laser plane of the optical system are presented. The reconstruction precision of the laser vision system is verified by a standard workpiece. Additionally, this determination approach is utilized to calculate the surface roughness of a multi-layer single-pass thin-walled part. The results indicate that the optical measurement approach based on the laser vision sensing is a simple and effective way to characterize the surface roughness of parts deposited by WAAM. The maximum absolute error is less than 0.15 mm. The proposed research provides the foundation for surface roughness optimization with different process parameters.     

基于协同服务平台的备件信息管理系统

针对备件库存管理中高成本和低效率现状,在传统备件信息管理系统的基础上引入了协同服务模式的备件管理方式,使设备用户和备件供应商也参与到设备服务商的备件管理中,实现数据信息的共享和传递。基于B／S三层结构实现备件库存管理及相关业务流程,以满足不同地区设备用户和服务商业务需求,同时最大限度地减少设备服务商库存成本,提高服务效率和质量。     

基于免疫粒子群算法的民机备件库存配置优化方法研究

针对民机维修保障的工程实际,建立了一种基于多维修层级、多设备层级的民机备件库存配置优化模型,运用适于多变量、非线性NP难解问题的免疫粒子群算法进行求解。本模型在最大限度地控制总预算资金投入的基础上,使各备件项目在各库存地点的配置最优,并最终保障飞机的签派可靠度。通过具体的实例分析验证了模型的有效性。     

Product design reuse with parts libraries and an engineering semantic web for small- and medium-sized manufacturing enterprises

The design reuse of products is vital for mass customization. In small- and medium-sized manufacturing enterprises (SMMEs), employing design reuse is a challenging issue because of the limited level and scale of these enterprises. Previous studies have not considered this issue and have attempted to rebuild a complete novel system. In this study, we propose a design reuse approach based on an engineering semantic web (ESW) and implement a design reuse system. This system does not rebuild the current parts library in SMMEs. In our approach, we construct an ESW and a mapping relation to introduce engineering semantic information into the existing parts library. In addition, we employ ant colony optimization (ACO) for the retrieval of design information. A design reuse prototype system is implemented for solving the problem of design reuse in SMMEs.