On-machine measurement using a noncontact sensor based on a CAD model

Once a machining process is finished, an inspection process is carried out to check whether the part is within dimensional tolerances. A coordinate measuring machine (CMM) is a general metrological device for assessment of dimensions on the shop floor. It cannot be ignored, however, that CMM measurements require significant resources in operating time and cost, which has led to many studies into on-machine measurement (OMM) systems. This study aims to develop an OMM system with a noncontacting laser displacement sensing apparatus and a computer-aided design (CAD) model for ease of operation, improved operating speed, and free form profiling. The system is composed of two software modules, one for sensor alignment with the machine tool and the other for measurement based on CAD/CAM (computer-aided machining). Consequently, the system was verified on the shop floor at a numerical control (NC) machining center.     

A Multi-Agent-Based Agile Shop Floor Control System

The ability of an enterprise to deliver new products quickly and efficiently to market is often the chief determinant of competitive success. The shop floor control system must be an open dynamic system with the capability of adapting and accepting radical unpredictable changes in its structures and industrial practices. This paper presents a new architecture for an agile shop floor control system. The architecture is based on the methodology of multi-agent systems in distributed artificial intelligence (DAI). The multi-agent system has some common characteristics such as: distribution, autonomy, interaction, and openness, which are helpful for transferring traditional architecture to a distributed, cooperative architecture for a shop floor control system. A bidding method based on the required production cost and processing time is also proposed. Using a distributed object-oriented technique, a CORBA-based multi-agent framework for an agile shop floor control system is constructed to integrate all the activity of the shop floor into a distributed intelligent open environment. To implement the framework, a coordination model between agents and behavioural models of some representative agents are established.     

Object oriented modelling and development of a dispatching algorithm for automated guided vehicles

The main problem for an automated guided vehicle (AGV) dispatching system is to assign vehicles to transport demands which optimise some predetermined objectives of a manufacturing shop. This paper presents a framework for an AGV dispatching system based on an object oriented approach using the unified modelling language (UML), and the development of a dispatching algorithm to facilitate a human controller to dispatch efficiently a fleet of AGVs in response to calls from any shop floor (or machine) operator. The main reason for this work is to model an AGV dispatching system as well as to develop a dispatching algorithm which can record details of the AGV position and movement and ensure their allocation of new orders. The provision of both immediate and pre-booked orders for an AGV is also incorporated in the proposed AGVs dispatching system. The underlying AGV dispatching system and algorithm are capable of dispatching a vehicle automatically to handle a call at the required time. In order to overcome difficulties associated with tackling immediate orders, pre-booked orders, and processing of information related to AGVs, a comprehensive dispatching algorithm is developed which aims to minimise lateness, traveling time and distance of empty vehicles in a simulated job-shop scenario. The effectiveness of the proposed framework for an AGV dispatching system is shown through a test problem.     

Development of an intelligent multisensor chatter detection system in milling

The development of a chatter detection system based on multiple sensors and suitable for application in industrial conditions was investigated in this paper. The signals obtained from a monitoring system composed of accelerometers mounted on the machine head and an axial force sensor were processed by using advanced signal analysis techniques such as wavelet decomposition. The statistical parameters obtained from wavelet decomposition were used to detect chatter by using an artificial intelligence classification system based on neural networks. The outputs of the neural networks for each sensor signal were further combined by using different strategies in order to obtain a multisensor chatter indicator. The performances of different strategies were evaluated by using experimental data, evidencing that it is possible to obtain an efficient chatter detection system both in terms of accuracy and of robustness against malfunctions and compatible with modern machine tool operation and automation.     

一种动态识别瓶颈机床的启发算法

瓶颈机床是影响车间生产和调度的关键因素。针对Jobshop调度中的瓶颈机床确定问题,提出了动态识别瓶颈机床的搜索算法框架。并详细讨论了算法框架中的工序开始时间窗、搜索空间的概率模型和动态启发算法。最后用算例验证了动态启发算法的有效性。     

NOISE REDUCTION SCHEDULING METHOD IN A SHOP FLOOR AND ITS CASE STUDY

Noise reduction in a shop floor is one of the important parts of green manufacturing. In ashop floor, machine tools are the main noise sources in a shop floor.A new approach is discovered byinvestigation that the noise can be obviously reduced in a shop floor by optimizing the schedulingbetween work pieces and machine tools. Based on the discovery a new method of noise reduction isproposed. A noise reduction scheduling model in a shop floor is established, and the application of themodel is also discussed. A case is studied, which shows that the method and model are practical.     

基于无线传感器网络的自治制造车间控制

为应对制造环境不可预知和动态的变化,基于无线传感器网络的自治车间控制系统,通过在制造车间中的各种物理对象（产品、设备等）上嵌入无线传感器节点,赋予其通信、计算和决策能力,实现了基于信息素的自治控制。该算法模拟蚁群觅食过程,将复杂的车间控制问题变为多个产品自治地寻找最佳加工路径的过程。原型系统实验证实了该方法能有效地适应动态变化的制造环境,获得了满意的控制效果。     

Integration of process planning and scheduling in a job shop environment

Today’s manufacturing systems are striving for an integrated manufacturing environment. To achieve truly computer-integrated manufacturing systems (CIMS), the integration of process planning and production scheduling is essential. This paper proposes a framework for integration of process planning with production scheduling in a job shop environment for axisymmetric components. Based on the design specifications of incoming parts, feasible process plans are generated taking into account the real time shop floor status and availability of machine tools. The scheduling strategy prioritizes the machine tools based on cost considerations.     

An integrated framework for statistical change detection in running status of industrial machinery under transient conditions

Early detection of changes in machine running status from sensor signals attracts increasing attention for the monitoring and assessment of complex industrial machineries under transient conditions. This paper presents a detection method that integrates one-class SVM with a pre-defined Autoregressive Integrated Moving Average (ARIMA) regression process. Meanwhile, an automatic cyclic-analysis method is also developed as a preprocessing to suppress temporal non-stationarity in condition signal before feeding it to the monitoring process. As such, a novel framework of continuous monitoring of condition signal is finally presented to inspect whether an unexpected running status change occurs or not during continuous machine operations. The proposed framework is applied to three representative condition monitoring applications: external loading condition monitoring, bearing health condition assessment, and rotational speed condition monitoring. Comparisons with existing methods are also provided, where the proposed method demonstrates its significant improvements over others.     

Real‐Time Monitoring of Tool Fracture in Turning Using Sensor Fusion

The sensor fusion method using both an acoustic emission (AE) sensor and a built-in force sensor is introduced for on-line tool condition monitoring during turning. The cutting force was measured by a built-in piezoelectric force sensor, which was inserted in the tool turret housing of an NC lathe. FEM analysis was carried out to locate the most sensitive position for the sensor. A burst of AE signal was used as a triggering signal to inspect the cutting force. A significant drop in cutting force indicated tool breakage. The algorithm was implemented in a DSP board and the monitoring system was installed on a CNC lathe in an FMS line for in-process tool-breakage detection. The proposed system showed an excellent monitoring capability.     

基于蓝牙和Windows CE.NET的数控系统编程和通信技术

提出了一种基于蓝牙技术和Windows CE.NET且适用于车间人机协同制造的新型数控系统。该系统分为移动控制器和机床控制器两部分,前者是基于智能手机的移动控制器,后者是基于WindowsCE.NET的嵌入式机床控制器,它们彼此通过蓝牙技术通信。详细介绍了该系统的体系结构和基于.NET Compact Framework的编程模型,阐述了蓝牙技术的通信机制及其实现,并给出了简单的研究结果。     

钻头磨损检测与剩余寿命评估

对钻头的磨损程度进行实时检测有助于对钻削加工过程实施预防性维护,提醒及时换刀。针对自动化生产中的刀具监测问题,给出一个基于主轴电流检测的钻头磨损状态分析和剩余寿命预测的应用策略。通过主轴电流传感器采样加工过程的电流信号,使用一个滑动窗口从连续采样数据中得到真实加工段数据,采用小波包分解的方法进行特征提取。基于Fisher标准筛选出最能表达磨损过程的若干特征。最后利用逻辑回归法和自回归滑动平均模型相结合的方法评估当前钻削加工的可靠性,预测钻头的剩余寿命。试验证明此方法的有效性,可为换刀决策提供依据。     

Application of ORFPM system for lean implementation: an industrial case study

This paper presents an on-line radio frequency identification (RFID)-based facility performance monitoring (ORFPM) system. This system supports the implementation of Lean production in a small manufacturing facility. This system uses wireless monitoring via RFID to automatically generate a real-time value stream map (VSM) using computer-aided programming. Creating the VSM automatically saves time, reduces errors, and makes the VSM more visible to supervisors at any time. This up-to-date information allows supervisors to make more accurate, real-time shop floor decisions. The results of this study indicate that the ORFPM system can successfully track performance variations when production has low time consumption requirements and is labor intensive. Several Lean improvement suggestions are also proposed based on the collected data from the ORFPM system.     

网络化制造环境下车间层信息交互模型及实现

网络化制造中，车间层的信息化水平在一定程度上可通过信息交互方式进行衡量。针对现有网络化制造环境下车间层信息交互和资源共享过程中存在的问题，提出了基于对等网络和移动Agent的车间层信息交互模型，重点阐述了该模型的体系结构、通信过程及系统安全性等；设计了用于实现以上模式的信息终端和系统，并结合某汽车焊装自动化生产线网络化监控与管理系统，分析了它在实际应用中所表现出来的特点。     

An autonomous low-Cost infrared system for the on-line monitoring of manufacturing processes using novelty detection

This paper describes the implementation of a process monitoring system using a low-cost autonomous infrared imager combined with a novelty detection algorithm. The infrared imager is used to monitor the health of several manufacturing processes namely: drilling, grinding, welding and soldering. The main aim is to evaluate the use of low-cost infrared sensor technology combined with novelty detection to distinguish between normal and faulty conditions of manufacturing processes. The ultimate aim is to improve the reliability of the manufacturing operations so as to ensure high part quality and reduce inspection costs. The paper describes several case studies, which have shown that the new low-cost technology could provide an inexpensive and autonomous methodology for monitoring manufacturing processes. Novelty detection is used to compare normal and faulty conditions in order to provide an automated system for fault detection.     

Condition monitoring of planetary gearbox by hardware implementation of artificial neural networks

The hazards of planetary gearboxes’ failures are the most crucial in the machinery which directly influence human safety like aircrafts. But also in an industry their damages can cause the large economic losses. Planetary gearboxes are used in wind turbines which operate in non-stationary conditions and are exposed to extreme events. Also bucket-wheel excavators are equipped with high-power gearboxes that are exposed to shocks. Continuous monitoring of their condition is crucial in view of early failures, and to ensure safety of exploitation. Artificial neural networks allow for a quick and effective association of the symptoms with the condition of the machine. Extensive research shows that neural networks can be successfully used to recognize gearboxes’ failures; they allow for detection of new failures which were not known at the time of training and can be applied for identification of failures in variable-speed applications. In a majority of the studies conducted so far neural networks were implemented in the software, but for dedicated engineering applications the hardware implementation is being used increasingly, due to high efficiency, flexibility and resistant to harsh environmental conditions. In this paper, a hardware implementation of an artificial neural network designed for condition monitoring of a planetary gearbox is presented. The implementation was done on a Field Programmable Gate Array (FPGA). It is characterized by much higher efficiency and stability than the software one. To assess condition of a gearbox working in non-stationary conditions and for chosen failure modes, a signal pre-processing algorithm based on filtration and estimation of statistics from the vibration signal was used. Additionally, the rewards-punishments training process was improved for a selected neural network, which is based on a Learning Vector Quantization (LVQ) algorithm. Presented classifier can be used as an independent diagnostic system or can be combined with traditional data acquisition systems using FPGAs.     

A Cascading Auction Protocol as a Framework for Integrating Process Planning and Heterarchical Shop Floor Control

A new contract net-style auction protocol is proposed as a framework for integrating process planning and shop floor control in heterarchical manufacturing systems. Process planning is partitioned into on-line and off-line activities; off-line process planning decisions are represented in a graph format and used as input for on-line process planning activities performed by machine controllers. Triggered by the opening round of an auction, the final on-line stages of process planning are dovetailed with the resource allocation process in the shop floor control system. The auction process allows final process planning decisions to be based on timely information, relying on the distribution of static process planning information rather than the distribution of a model of dynamic shop floor status and allowing a controller to identify all the primary and secondary resources and operations that must be provided for the incremental processing of a part.     

A clustering-based modified variable neighborhood search algorithm for a dynamic job shop scheduling problem

The dynamic job shop scheduling (DJSS) problem occurs when some real-time events are taken into account in the ordinary job shop scheduling problem. Most researches about the DJSS problem have focused on methods in which the problem’s input data structure and their probable relationship are not considered in the optimization process while some useful information can be extracted from such data. In this paper, the variable neighborhood search (VNS) combined with the k-means algorithm as a modified VNS (MVNS) algorithm is proposed to address the DJSS problem. The k-means algorithm as a cluster analysis algorithm is used to place similar jobs according to their processing time into the same clusters. Jobs from different clusters are considered to have greater probability to be selected when an adjacent for a solution is made in an optimization process using the MVNS algorithm. To deal with the dynamic nature of the problem, an event-driven policy is also selected. Computational results obtained using the proposed method in comparison with VNS and other common algorithms illustrate better performance in a variety of shop floor conditions.     

成批生产计划调度的集成建模与优化

针对多品种批量生产类型,建立了调度约束的生产计划与调度集成优化模型。模型的目标函数是使总调整费用、库存费用及生产费用之和最小,约束函数包括库存平衡约束和生产能力约束,同时考虑了调度约束,即工序顺序约束和工件在单机上的加工能力约束,保证了计划可行性。该模型为两层混合整数规划模型,对其求解综合运用了遗传算法和启发式规则,提出了混合启发式求解算法。最后,针对某机床厂多品种批量生产类型车间进行了实例应用,对车间零件月份作业计划进行分解,得到各工段单元零件周作业计划,确定了零件各周生产批量与投产顺序。