设备维护与管理中设备效能的评估与测度

设备维护与管理的重要目标之一就是要提高设备效能,减少各类损失和资源浪费,提高企业的成本竞争力,为此需要对设备综合效能进行评估与测度.系统地分析了影响设备效能的六大损失,即故障停机损失、换装和调试损失、空闲和短暂停顿损失、减速损失、质量缺陷和返工损失、启动损失.针对制造加工业给出了设备综合效能水平的评估标准体系,提出了用设备综合效能指标来测度设备效能的方法.设备综合效能集成了设备有效性、设备性能和合格品率指标,反映了设备的全部生产能力,使设备维护与管理的内涵和外延都有了很大拓展.最后,用算例验证了用OEE方法的效度和信度.     

从生产工厂的产出综合效能到整厂综合效能的研究

为了研究一台设备运行性能,人们提出了设备综合效能OEE。而为了研究生产系统(单元)中设备之间的关系,探讨系统运行性能的情况,2003年一些科研人员在OEE的基础上提出了产出综合效能OTE。在介绍一台机器的设备综合效能OEE和生产系统(单元)的产出综合效能OTE的基础之上,引出了制造型工厂的整厂综合效能OFE的计算方法,并且通过Witness仿真软件建模和仿真来验证OFE计算方法的正确性,最后将其应用在太阳能电池制造厂的生产实际当中。     

基于OEE的企业设备效率诊断研究

设备综合效率（OEE）是全面生产维护（TPM）的重要组成部分.现如今,OEE在现代工业领域得到了越来越广泛的应用.文中引入Cycle Time（单循环时间）对传统OEE计算公式加以改进,在此基础上以设备综合效率作为衡量指标进行诊断分析,并以国内某企业生产线为例,对其进行了对设备利用率、人员效率以及质量合格率三方面进行了诊断研究,并提出了改进意见,对产能的提高起到了积极的作用.     

Characterization and compensation of dynamic errors of a scanning coordinate measuring machine

The necessity for reducing production cycle times while achieving better quality compels metrologists to look for new and improved ways to perform the inspection of parts manufactured. The advent of coordinate measuring machines led to a significant boost in accuracy, flexibility and reliability for measurement tasks. However, these machines are in some instances lagging behind machine tools and need improvement. One major limitation is the execution of measurements with low uncertainty at a reasonably fast rate to make it possible to measure more parts. This would ensure more reliability to the end product and better information to control the manufacturing process. Coordinate measuring machines with scanning capabilities offer the option to output high data density for parts at high speed. However, they are still considerably less accurate at faster measurement speeds and need to be improved. In this work a scanning measuring machine was extensively tested and a compensation model that accounts for part of its dynamic errors affecting measurement of circular features is proposed.     

Using neural network and decision tree for machine reliability prediction

Overall equipment efficiency (OEE) is widely used in industry. OEE is the combination of availability efficiency (AE), operation efficiency (OE), rate efficiency (RE), and quality efficiency (QE). In general, OEE, AE, OE, RE, or QE are only calculated as part of a management consultancy exercise. In the present research, a group of washing machines from a TFT-LCD manufacturing company was used for the case study. Because AE is strongly related to the reliability of a machine, this research aims to use collected AE data for predicting the reliability of the machine. Four methods are proposed for predicting the machine’s reliability. The results show that the combination of neural networks and decision trees based on the previous eight AE values has the best performance in predicting the reliability of TFT-LCD washing machines.     

Automating factory performance diagnostics using overall throughput effectiveness (OTE) metric

The overall equipment effectiveness (OEE) metric is a powerful tool that can be used to measure performance and also perform diagnostics at the equipment level. Although important, gains made in OEE are insufficient; because the ultimate objective is a highly efficient integrated system, not brilliant individual equipment. Factory level performance monitoring and diagnostics can be facilitated by classifying the entire manufacturing system layout into unique subsystems including “series,” “parallel,” “assembly,” and “expansion.” The overall throughput effectiveness (OTE) metric is then derived for each of these subsystems. Factory level metric can be computed by synthesizing the subsystem level metrics, capturing their interconnectivity information. The objective of this paper is to present the algorithms developed to automate the factory-level performance monitoring and diagnostics process using OTE. The algorithms are implemented into a software tool called SIMPRO. SIMPRO allows factory professionals to efficiently measure performance and conduct factory level diagnostics (i.e., identify bottlenecks/hidden capacity). A glass manufacturing case study is used to illustrate automated performance diagnostics and the benefits obtained by using the approach.     

设备综合效能的应用框架体系研究

分别从设备综合效能的经典定义、相关工业标准、不足之处及其发展方向等几方面阐述了设备综合效能的相关理论。分析了设备综合效能和设备综合效率的异同点,指出设备综合效能在企业应用中的不足之处。建立了基于制造执行系统的设备综合效能应用框架体系,阐述了设备综合效能在设备维护系统和制造执行系统中的应用,并分析了设备综合效能的关键使能技术。     

The role of extrinsic factors in industrial task-specific uncertainty

The measurement of large components using portable measuring equipment is important to many industries, including ship-building and aerospace. Portable measuring instruments – such as laser trackers, laser radar, indoor GPS, and other systems – are used to obtain measurement data for process control, assembly alignment, or geometric conformance decisions. Traditional uncertainty estimations often focus on the measuring instrument and its performance as a primary contributor to the overall uncertainty for specific measurands. The research reported here focuses on the uncertainty contributors that are due to extrinsic effects such as part deformation due to gravitational loads and thermal distortion of the workpiece, where the uncertainty contribution from the instrument is considered insignificant in comparison.     

The NANOMEFOS non-contact measurement machine for freeform optics

Aspherical and freeform optics are applied to reduce geometrical aberrations as well as to reduce the required number of components, the size and the weight of the system. To measure these optical components with nanometre level uncertainty is a challenge. The NANOMEFOS machine was developed to provide suitable metrology (high accuracy, universal, non-contact, large measurement volume and short measurement time) for use during manufacturing of these surfaces. This paper describes the design, realization and testing of this machine. In particular it describes the design and testing of the air-bearing motion system with parallel stage configuration, and the separate metrology system with Silicon Carbide metrology frame and an interferometry system for direct displacement measurement of the optical probe. Preliminary validation measurements demonstrate the nanometer level repeatability for freeform surface measurement.     

The uncertainty in a current meter measurement

All measurements of physical quantities are subject to uncertainties. These may be due to bias errors in the equipment used for calibration and measurement, or to random scatter caused by, for example, a lack of sensitivity of the equipment used for the measurement [1]. Every day, throughout the world, numerous current meter measurements are made in open channels to measure flow without any report on the uncertainty of the measurement.. The uses made of these measurements in the design and operation of river works and in water resources management generally, require an assessment of the reliability of the measurements and in such cases it is important that the uncertainty of the measurements is reported [1]. New international recommendations involve the analysis of Type A and Type B methods of evaluation of uncertainty, the result to be reported as a combined uncertainty with symbol u_i and a coverage factor of 2 corresponding to a confidence level of approximately 95% [2].     

Camera based precision measurement in improving measurement accuracy

This paper presents a vision based software system which is developed in order to improve the precision measurement in machining technology. Precision measurement, monitoring and control are very important in manufacturing technology. In order to increase the accuracy of the measurement system; application of camera or vision is very useful. Automatic control is also vital for the measurement performance to be improved. During measurement of the gear profile; human monitoring sometimes may face danger as this is a stylus contact scanning system and the stylus is very small and thin as well as the probe moves with a maximum speed of 10 mm/s. The existing methods for gear measurement are either time consuming or expensive. This paper presents the successful implementation of the vision system in precision engineering which saves times and increases safety of the measurement system with the increment of the measurement performance. Color based stylus tracking algorithm is implemented in order to acquire better performance of the developed system. Stylus tracking based measurement is the key issue of the present research.     

Uncertainty Analysis of Temperature Measurement System using Analytical and Interval Algorithm

Abstract

This paper presents an uncertainty analysis of a temperature measurement system. This has been carried out by analytical methods and verified by the algorithms based on interval arithmetic. A resistance temperature detector (RTD) based temperature measurement system is considered to illustrate the analysis.     

寄生式时栅传感器测量不确定度的分析与评定

为了全面分析寄生式时栅误差和不确定度来源,提高寄生式时栅的测量精度,建立符合国际GUM规范检测结果的不确定度评定模型,以84对级的寄生式时栅为研究对象,根据其测量原理分析所测量角度的计算公式,进而将不确定度来源分为插补脉冲个数的误差、插补脉冲信号的量化误差、行波信号的周期误差和环境误差四大类,从理论上建立各不确定度分量之间的理论传递关系,应用现代不确定度理论,推导出合成测量不确定度计算公式。搭建实验平台,利用示波器等仪器的测量结果评定各不确定分量具体数值大小,计算被测角度的合成测量不确定度值。通过与寄生式时栅整圆周的实际测量误差相比较,可以看出利用该评定方法评定的传感器角度测量不确定度与实际误差相符,因此可以用于寄生式时栅传感器的实际评定。     

空压机排气量测量结果的不确定度分析

通过对影响空气压缩机排气量测量结果的各个要素及误差组成的综合分析,提出了提高测量结果准确度的方法,总结出采用电测传感器和计算机数据采集技术的排气量测量装置的不确定度及测试设备的精度。     

A study on mutative scale straightness measurement based on uncertainty analysis

Mutative Scale Measurement is often used to measure the characteristics of mechanical and electrical equipments/components in manufacturing industry. A typical case is the straightness measurement of large-scale rails. Due to the uncertainty of surface error distribution, and difference in the size and the locations of sample points, the evaluated value has a certain degree of uncertainty, which reduces the accuracy of the measurement. Since the decrease of uncertainty is at the expense of higher measurement cost, optimization of measurement cost for an acceptable uncertainty becomes a significant issue. This paper describes the composition of the uncertainty that caused by the measuring process and analyzes the uncertainty caused by sample size insufficiency. On the basis of these arguments, a model has been proposed to calculate the minimum sample size which meets the requirement of measurement uncertainty. Case studies are carried out to demonstrate the application of the derived methodology on sampling strategy.     

Evaluation of coordinate measurement uncertainty with use of virtual machine model based on Monte Carlo method

Advances in modern manufacturing techniques implies more efficient production but also new tasks for coordinate metrology. The main of them is evaluation of accuracy of the measurement, because according to technological requirements, results of measurements are useful only when they are given with their accuracy. Currently used methods for uncertainty assessment are difficult and require knowledge and measuring experience. It is therefore important to implement correct and validated methods that will also be easy to implement and will not require broad metrological knowledge from the personnel. Presented here simulation method, based on Monte Carlo method is one of them. The article presents the conception, implementation and validation of this method.     

A new method for defining the measurement-uncertainty model of CNC laser-triangulation scanner

This article examines the measurement uncertainty in terms of the incident angle, the object colour and the measurement distance for a Computer Numerical Control (CNC) laser-scanning process. It describes a new method for predicting the measurement uncertainty that simultaneously considers all three parameters. A set of measurements with different values for these parameters was made in order to describe the measurement uncertainty for the whole measuring range of the laser-scanning device. The final result of this research is an equation model that allows an accurate prediction of the measurement uncertainty within the investigated measurement field while the results of the extrapolated measurement field give an accuracy of the prediction that is better than 15%. In general, the model can also be useful as a measuring guideline for any other laser-triangulation measuring device, although the values would need to be adapted to each particular device. The, thus, obtained equation model could then be implemented into automatic inspection/control lines or used for self-adaptive measuring CNC paths to perform measurements in the optimal measuring range for a particular surface.     

Reliability analysis of a phaser measurement unit using a generalized fuzzy lambda-tau(GFLT) technique

Nowadays power consumption is increasing day-by-day. To fulfill failure free power requirement, planning and implementation of an effective and reliable power management system is essential. Phasor measurement unit(PMU) is one of the key device in wide area measurement and control systems. The reliable performance of PMU assures failure free power supply for any power system. So, the purpose of the present study is to analyse the reliability of a PMU used for controllability and observability of power systems utilizing available uncertain data. In this paper, a generalized fuzzy lambda-tau (GFLT) technique has been proposed for this purpose. In GFLT, system components' uncertain failure and repair rates are fuzzified using fuzzy numbers having different shapes such as triangular, normal, cauchy, sharp gamma and trapezoidal. To select a suitable fuzzy number for quantifying data uncertainty, system experts' opinion have been considered. The GFLT technique applies fault tree, lambda-tau method, fuzzified data using different membership functions, alpha-cut based fuzzy arithmetic operations to compute some important reliability indices. Furthermore, in this study ranking of critical components of the system using RAM-Index and sensitivity analysis have also been performed. The developed technique may be helpful to improve system performance significantly and can be applied to analyse fuzzy reliability of other engineering systems.     

Prediction of surface roughness in CNC turning by model-assisted response surface method

Various statistical approaches such as classical regression and modern machine learning methods have been applied to measurement data for estimating the status of manufacturing processes, which is now boosted by the movement of Internet of Things (IoT). In this study, we attempt to integrate an analytical tool model of surface roughness and measurement data of CNC turning to develop a modeling approach which does not depend too much on data, but also effectively uses existing analytical models. As in previous researches, we use cutting speed, feed rate, depth of cut and three acceleration components from an accelerometer to predict surface roughness. Co-Kriging method is employed to integrate the above measurements and a well-known model of surface roughness in turning. It was confirmed that the approach improved the prediction accuracy when only small amount of data is available for model construction. Meanwhile, the accuracy of ordinary Kriging method, which only depends on data, is suitable when measurement data sufficiently spans the parameter space, being expected that it may be rare in actual operations. We also attempted to detect outlier of measurements using the Co-Kriging method, which might be a non-trivial task when there is no additional information to evaluate the validity of the measurement data.     

Discovery of hidden maintenance opportunities in automotive assembly lines: MOW and GMOW

In manufacturing systems, many maintenance tasks require equipment to be locked out for safety. However, such stoppage might directly cause short-term production losses although maintenance is performed to increase the long-term system reliability. In this paper, we investigate how long we can strategically stop equipment for maintenance during production operating without affecting system throughput. We extend the concept of maintenance opportunity windows (MOWs) to various system configurations and introduce a new concept of group maintenance opportunity windows (GMOWs). GMOW is the maximum time window that allows to perform a group maintenance without jeopardizing the flow of a production line. Moreover, we also provide how to calculate MOW and GMOW via simulations which can deal with uncertainties in production lines, such as random machine failures, starvations, blockages, etc.