基于DEA的制造系统全要素能源效率评价与优化

针对目前机械加工车间制造系统能源效率评价需要基于大量的机械加工试验来分析能量消耗,需要基于经验公式来获得能源效率指标,以及没有实现基于能效评价后的能效优化等问题,基于生产管理信息系统监测数据,提出一种制造系统全要素能源效率评价指标。用数据包络分析方法对机械加工车间制造系统全要素能源效率进行评价,使用能源效率优化分析方法构建能源效率函数关系,从而提出降低能耗和提高能源利用率的定量科学方法。最后以某变速箱装配车间为例,通过实例分析,验证该评价及优化方法的理论及应用价值。     

基于VMD和改进多分类马田系统的滚动轴承故障智能诊断

为了有效提取滚动轴承的故障信号,选择合适的智能分类器识别故障状态,提出基于变分模态分解及多重马氏距离法的多分类马田系统的故障智能诊断系统。通过变分模态分解将振动信号分解为多个本征模函数并提取相关特征;并采用了多重马氏距离法的马田系统,以特征子集代替特征参与分类器的构建,以解决特征参数众多的问题;通过正交表和信噪比,筛选出各状态的敏感模态分量,并提出多分类马田系统,用于多类故障智能识别;将其应用于滚动轴承故障数据中,验证算法的有效性,并与其他算法对比分析。结果表明,基于变分模态分解及改进的多分类马田系统算法能简化诊断系统、训练耗时少,识别准确率高,是一种更为有效的故障智能诊断方法。     

基于多特征提取和改进马田系统的滚动轴承故障分类方法研究

为提高旋转机械的使用效率,及时识别滚动轴承的潜在故障,提出一种基于多特征提取和改进马田系统(MTS)的故障分类方法。通过时域、频域和自适应白噪声的完备经验模态分解(CEEMDAN)提取多维特征,构建初始特征集。结合马田系统和有向非循环图(DAG)的特点,构建DAG-MTS多分类模型,并将其运用到轴承故障诊断中。利用滚动轴承故障数据测试该模型的有效性和实用性,结果表明,该模型能够准确识别出滚动轴承的故障。     

基于标签估计的动态最优多分支搜索防碰撞算法

针对射频识别(RFID)系统的动态二分支搜索(DBS)算法,提出了一种改进的动态多分支搜索算法,然后通过对多分支算法系统效率的分析,给出了最优分支数目的计算方法,并结合标签估计方法,得到了动态最优多分支搜索(DOMBS)防碰撞算法。理论分析和实验仿真表明,与DBS算法相比,改进算法——DOMBS防碰撞算法的查询次数较少,具有明显的性能优势。DOMBS算法的系统识别效率达58%,而DBS算法的效率仅为50%左右,如果标签估计方法能够进一步优化,DOMBS算法的效率还能得到进一步提高。     

基于模糊理论的半导体制造系统时变多目标生产调度研究

针对半导体晶圆制造系统(SWFS)调度中的多目标优化和目标时变性问题,提出了一种时变多目标(TVMO)调度算法.基于模糊理论研究了时变模糊集合与多目标重要程度的复杂非线性量化关系,进而研究了SWDS的优化调度方法.所提出的方法兼顾最大产品交期率、最大生产移动量和瓶颈机台最大产能利用率三个目标,根据时变目标权重计算出在制品的加工优先权序列号.大量的仿真实验数据证明,该调度算法能够改善系统多个绩效目标,可为大规模复杂重入型制造系统的科学生产控制与调度提供有效支持.     

Optimization of multi-tag identification for UHF RFID multi-antenna tag readers

针对现有的超高频(UHF)射频识别(RFID)标签阅读器使用单个天线,难以保证多标签识别可靠性的问题,提出了一种通过增加天线个数,以增强覆盖效果、减少识别盲区、增强多标签识别可靠性的RFID多天线识别模式,并利用遗传算法对识别过程中启用天线的个数进行优化,通过合理处理选择、交叉、变异遗传算子以提高RFID阅读器多标签识别的可靠性.实验结果表明:增加天线个数可以增强覆盖效果、减少识别盲区;基于遗传算法的识别优化算法具有良好的搜索性和收敛性,提高了系统识别的可靠性.该研究为复杂环境下应用超高频RFID技术提供了新思路.     

基于DTCNN-SVM的工业循环水系统供水泵故障诊断EI北大核心CSCD

工业循环水系统供水泵的工作状态是影响工业过程安全生产的重要因素,为及时准确地识别供水泵的工作状态,提出一种基于深度迁移卷积神经网络和支持向量机(deep transfer convolutional neural network-support vector machine,DTCNN-SVM)的故障诊断方法。将与工作状态强相关的振动信号进行信号-图像预处理,实现振动时序信号的二维灰度图化;在此基础上,采用融合迁移学习与残差神经网络的深度迁移卷积神经网络模型提取振动信号灰度图特征,并基于模糊不一致性度量对深度学习特征进行约简;采用支持向量机法建立供水泵故障诊断模型。试验结果表明,所提方法在少量样本数据和模型参数下能有效识别供水泵工作状态。     

车间生产监控系统的研制

本文针对生产车间具体情况提出了基于客户/服务器Client/Server,(简称C/S)结构的分布式车间监控系统,通过对车间生产状况和车间生产环境的实时动态监控,保障车间内物流畅通,信息共享,能源和资源合理利用,最终实现均衡生产、库存最小、提高工效。     

基于VMD-SSI的结构模态参数识别

将变分模态分解(VMD)和随机子空间法(SSI)结合,提出了基于VMD-SSI的结构模态参数识别新方法。针对VMD中的模态分层数K值确定困难的问题,提出模态重复比率准则,保证了模态信息的有效分解。依据模态重复比准则确定测量信号的最优分层数K;利用VMD方法进行信号并行分解,用奇异值分解(SVD)去噪,以提高模态参数的识别精度。用该研究提出的VMD-SSI方法识别模态固有频率和阻尼,用VMD方法辨识模态振型,将VMD-SSI法应用于外伸梁模型的模态参数识别,并利用统计理论分别检验识别的模态频率、模态阻尼和模态振型的精度。结果表明, VMD-SSI法识别模态参数的精度高于传统SSI法。     

未知激励下的无迹卡尔曼滤波新方法

无迹卡尔曼滤波（UKF）是一种识别非线性系统的有效方法,然而传统的UKF方法需要观测外部激励,这限制了UKF的应用范围。迄今为止,国内外对未知激励情况下的UKF方法的研究还非常少。该文在传统UKF的基础上,推导出在未知激励情况下的无迹卡尔曼滤波（UKF-UI）方法的递推公式,通过对观测误差的最小化,利用非线性方程求解,识别未知外部激励,进而识别非线性结构系统状态与结构未知参数。进一步采用融合部分观测的加速度响应及位移响应,消除识别结果的漂移问题。分别通过白噪声和未知地震作用下识别非线性迟滞模型的两个数值算例,考虑观测噪声对非线性系统进行识别,从而验证提出新方法的有效性。结果表明,该文所提出的UKF-UI方法,能够在部分观测结构系统响应的情况下,有效地识别非线性结构参数和未知激励。     

医院放射科病人就诊精益价值流研究

试图讨论如何消除或减少放射科病人就诊的无价值服务流程及流程时间。精益价值流程图（Value Stream Mapping,VSM）是精益制造（Learn Manufacturing）框架下的一种用来描述物流和信息流的可视化工具,在传统制造业已经广泛应用。以精益价值流理论和方法为基础,借助仿真建模方法分析华西医院医技放射科病人就诊服务流程和流程时间,找出主要瓶颈流程。针对主要瓶颈流程进一步分析其瓶颈资源约束,发现其医师班均匀分配病人、诊断病例信息、撰写诊断报告的管理问题,从而得出改善方案和策略。精益管理的资源粗能力匹配机制是改善病人就诊服务流程的一种有效方法。     

Analysis and improvement of multi-product assembly systems: an application study at a furniture manufacturing plant

In this paper, we introduce an application study of modelling, analysis and continuous improvement of an assembly system at a furniture manufacturing plant using production systems engineering methods. Analytical models have been developed to characterise the assembly system making multiple products, and recursive procedures have been derived to evaluate line production rate. Lot size analysis is carried out, and bottleneck analysis methods are introduced to identify the bottlenecks, whose improvement can lead to the largest improvement in system performance. Such methods provide a quantitative tool for plant engineers and managers to operate and improve assembly line with high productivity, and are also applicable to other large-volume manufacturing systems.     

A cross-sector review on the use of value stream mapping

Value Stream Mapping (VSM) has become a popular method for lean thinking and implementation in recent years. Previous reviews related to VSM are limited to individual sectors due to varied research objectives. The lack of studies which focus on cross-sector review of VSM studies is impeding the implementation of VSM by both lean researchers and practitioners. The paper aims to determine the-state-of-the-art development of VSM in five sectors, including manufacturing, health care, construction, product development and service sectors. A total of 131 journal articles are reviewed and analysed from the period of 1999–12/2016. The analysis covers the complete implementation cycle of VSM, including metrics for current state map, improvement techniques for future state map, benefits and achievements of VSM application, and critical success factors for VSM implementation. Cross-sector comparisons and investigations are conducted to understand the differences of VSM implementations in various sectors to facilitate VSM development and increase the number of successful VSM implementation. The results suggest that understanding value and waste in a diverse value stream environment and ensuring the suitability and usability of traditional lean metrics/techniques within the different flow settings are central to the VSM development.     

Methodology for integrated management system improvement: combining costs deployment and value stream mapping

Integrated Management System – Quality, Environment, Safety (IMS-QES) combines all related components of a business into one system for easier management and operations Quality (QMS/ISO 9001), Environmental (EMS/ISO 14001), and Health & Safety (OHSAS 18001). IMS-QES has been generally used to increase operational performance in manufacturing systems. However, the economic impact of standard approach of IMS-QES remains difficult due to the lack of alignment between IMS-QES objectives and strategic management of the company (policy of IMS-QES) and also the inadequacy between the improvement processes and the cost of losses.

Therefore, the main objective of this work is to overcome this limitation. The Framework proposed approach called IM-VCF integrates concepts from IMS-QES, Value Stream Mapping and Cost Deployment tool. It is structured in ten steps. It allows a company to assure proper alignment between IMS-QES policy and business operations and identify the categories of losses. IM-VCF allows analysing critical issues and estimating the potential savings, in terms of cost. A case study taken from the application of the IM-VSF within certified QSE chemical fertiliser port is presented.     

Tabu search-based algorithm for the TOC product mix decision

The theory of constraints (TOC) is a management philosophy that maximizes profits in a manufacturing plant with a demonstrated bottleneck. The product mix decision is one application of TOC that involves determination of the quantity and the identification of each product to produce. However, the original TOC heuristic is considered to produce unrealizable solution when a manufacturing plant has multiple resource constraints. This paper presents a tabu search-based TOC product mix heuristic to identify optimal or near optimal product mix for small problem instances under conditions where the original TOC heuristic failed. The tabu search-based TOC product mix heuristic is further used to solve large problem instances typical of practical manufacturing scenario. The experimental results for small to medium size problem show that the tabu search-based TOC heuristic compares favourably with those of optimal methods. Large size problems for which optimal methods have not been established in terms of feasibility in computation times were also solved in reasonable times with good quality solutions, thus confirming that the proposed approach is appropriate for adoption by production planners for the product mix problem in the manufacturing industry.     

Scrap value stream mapping (S-VSM): a new approach to improve the supply scrap management process

In this work, an innovative methodology to improve the Supply Scrap Management Process (SSMP), based on Value Stream Mapping (VSM), is presented. VSM is one of the best tools to map a process and eliminate its critical issues, that produces good results if applied to production processes, but can be ineffective for management processes as the SSMP. Therefore, the main objective of this work is to overcome this limitation. The proposed approach taking the name Scrap Value Stream Mapping (S-VSM) and integrates concepts from VSM and other Lean Production (LP) and World Class Manufacturing tools. It is structured in five steps. The definition of the process borders and the identification of categories of loss through the first four steps of Cost Deployment is the first step. Then, the SSMP is subdivided in its Accounting and Physical Streams and the current state is drawn. Next, wastes and critical issues are analysed and their root causes are determined using some of LP tools. In step four, improvements are proposed and the future state is drawn. Furthermore, potential savings, in terms of €, are estimated. In the last step, a methodology to monitor the effects of implemented improvements is defined. A case study taken from the application of the S-VSM within automotive company is presented.     

Data driven bottleneck detection of manufacturing systems

Bottlenecks within a production line significantly reduce the productivity. Quick and correct identification of the bottleneck locations can lead to an improvement in the operation management of utilising finite manufacturing resources, increasing the system throughput, and minimising the total cost of production. Most of the current bottleneck detection schemes focus on the long-term bottleneck detection problem and an analytical or simulation model is usually needed. Due to recent developments, short-term process control and quick decision making on the plant floor have emerged as important qualities for operation management. This research proposes a new data driven method for throughput bottleneck detection in both the short and long term. The method utilises the production line blockage and starvation probabilities and buffer content records to identify the production constraints without building an analytical or simulation model. The method has been verified both analytically and by simulation. An industrial case study has also been used in order to demonstrate the implementation and validate the efficiency of the proposed bottleneck detection method.     

Real-time performance evaluation and improvement of assembly systems with Bernoulli machines and finite production runs

Extensive research has been investigated in the past several decades to evaluate the performance of manufacturing systems under rigid production mode. Based on the deployment of the new manufacturing strategies (e.g. smart manufacturing), real-time performance analysis, continuous improvement and efficient production management of flexible production systems are urgently to be investigated. Therefore, we study the problems of real-time performance evaluation and bottleneck of assembly systems in this paper. The system is assumed to have Bernoulli machines and finite production runs. We first derive the mathematical model of the system and then, derive the analytical formulas for performance evaluation of systems with three Bernoulli machines. In addition, we propose a decomposition and aggregation-based algorithm to approximate the system performances with high accuracy and computational efficiency. The idea is then extended to generalised assembly systems. Finally, the method of bottleneck analysis by using completion time bottleneck indicator is introduced and evaluated by numerical justification.     

约束理论在电磁阀生产计划中的应用

以电磁阀生产计划控制为研究对象,将约束理论引入生产系统.通过生产类型和工艺路线分析,对可能存在瓶颈工序部件的各个工序进行工时统计、生产能力负荷比较后,找出阀门生产中的瓶颈工序.运用DBR理论,对瓶颈工序建立"前拉后推"的生产计划编排方式,提高了瓶颈工序的生产效率,瓶颈工序的在制品堆积情况有所缓解,装配停工待料情况大大减少,电磁阀生产周期缩短了20%,使得阀门能够按时出厂.