Identifying the mean step change of UBM chart

The traditional control charts are developed based on the assumption that the successive observations are independent and identically distributed. In some processes, the independence assumption is violated when there is autocorrelation between observations. To solve this problem, two methods, classified as model-based and model-free, could be applied. When a control chart alarms an assignable cause, it is essential to detect the process change point in order to remove the root cause. In the presence of autocorrelated data, different methods for change-point identification have been applied only for model-based methods. Hence, this is considered as the research gap and an attempt is made to fill this gap by applying maximum likelihood function in unweighted batch mean control chart, one of the most applied model-free methods. In this article, an estimator is presented to determine the change point for the first-order autoregressive process, AR(1). When a real change occurs, the performance of proposed estimator is evaluated through simulation.     

Identifying time of a monotonic change in the fraction nonconforming of a high-quality process

When a signal is detected by control charts, a search begins to identify and eliminate the sources of this signal. Knowing when a process has changed is very helpful for this purpose. The unknown special point that the process changed for the first time is referred to as change point. In this paper, we propose a maximum-likelihood estimator for the behavior model of the process fraction nonconforming in a high-quality process monitored with a cumulative count of conforming (CCC) control chart. We estimate the time of change without requiring the prior knowledge of the change type rather than we assume the type of change present belongs to a family of monotonic changes. Then, we compare the performance of the proposed change point estimator relative to estimators for the process fraction nonconforming change point derived under a single step and a linear trend change assumption. We do this for a number of monotonic change types following a signal from a CCC control chart. Finally, the application of the proposed change point estimator is shown through a real case.     

Estimating multivariate linear profiles change point with a monotonic change in the mean of response variables

In this paper, a maximum likelihood estimator (MLE) is developed to estimate change point when monotonic change occurs in the mean of response variables in multivariate linear profiles in Phase II. Performance of the proposed estimator is compared to the performance of step change and linear drift estimators under different shift types. To conduct comparisons, accuracy and precision of the estimators are considered as performance measures. Simulation results show that the average change point estimate of the proposed estimator is less biased than the one for the step and drift estimators in small shifts, because \( {\overline{\widehat{\tau}}}_{\mathrm{monotonic}} \) is closer to the actual change point of 25 in small shifts. Also, the precision of the proposed estimator is approximately better than that of the step and drift estimators, because its precision values are higher. Hence, the proposed estimator has better performance in terms of both accuracy and precision in small shifts under any kinds of increasing changes. In single step and linear drift changes when the magnitude of shifts increases, the accuracy and precision of their corresponding estimators become better than the accuracy and precision of the proposed estimator. However, the proposed estimator has an advantage that it does not require assumptions about the change type, and its only assumption is that the mean of the response variables changes in an increasing manner. Additional evaluations on the effect of smoothing constant show that with smaller values of the smoothing constant, the proposed change point estimator has less biased estimates and smaller values of mean square error in small shifts rather than the step and drift estimators, leading to a better performance. Also, the larger values of smoothing constant lead to the better performance of the monotonic estimator in large shifts. Finally, the application of the proposed estimator is shown through a real case in the calibration process in the automotive industry.     

A time to change

With new regulations coming from the EC, health and safety at work practices are becoming more stringent. But, says John Martin, this can be a positive advantage for your company.     

激波管反射阶跃压力上升时间高精度估计

提出一种激波管反射阶跃压力上升时间高精度估计方法。首先,基于压力传感器阶跃响应特性,建立激波管反射阶跃压力上升时间估计理论模型;其次,采用经验模态分解实现阶跃响应信号噪声分量消除,提取衰减振铃分量;然后,基于衰减正弦拟合估计衰减振铃分量的第一峰值时间和振荡周期;最后,根据理论模型实现激波管反射阶跃压力上升时间高精度估计。仿真实验结果表明,阶跃压力上升时间估计平均相对误差为2.57%,比传统方法和直接拟合法的平均相对误差分别减小了约7.3倍和2倍。激波管实测实验结果表明,在铝膜片厚度分别为0.25和0.07 mm的条件下,反射阶跃压力上升时间估计均值分别为0.712和0.876μs,相对误差分别为0.14%和1.9%,明显小于传统方法测量相对误差(7.5%和4.3%),方法有效提高了激波管反射阶跃压力上升时间的估计精度,并且具有更强的鲁棒性。     

Modifying simple linear profiles monitoring schemes in phase II to detect decreasing step shifts and drifts

In profile monitoring, a relationship between a response variable and one or more explanatory variables is monitored. Different methods were developed for phase II monitoring of simple linear profiles. While some of the methods can be used to detect both increasing and decreasing shifts in the regression parameters, others need to be modified to enable detection of decreasing shifts in a process. In this paper, necessary modifications of the phase II methods for simple linear profile monitoring are proposed to improve their performance in detecting decreasing shifts. The paper also presents a performance comparison of several phase II methods.     

Method of generating a hydraulic step wave with a short rise time

A hydraulic step wave calibrator (HSC) was newly developed herein to generate a hydraulic step wave with a short rise time that can be utilized to investigate dynamics of hydraulic components with a short response time. The design of the HSC was similar to a general spool valve comprising a spool and a steel housing. A quick-opening mechanism and a tiny sensing cavity were utilized in the HSC to reduce the rise time of the generated hydraulic wave. The experimental results indicate that the dynamic performance of the HSC at various conditions. With the short rise time between 21 and 54 μs, the HSC can be regarded as an extension of hydraulic sock tubes towards low frequencies. The hydraulic step wave generated by the HSC covered a range of dynamic calibration of hydraulic components that current hydraulic wave generators have not achieved yet.     

A step towards real time [production monitoring and control system]

The Fraunhofer Institute for Information and Data Processing has developed a novel production monitoring and control system (PMC) for DaimlerChrysler Bremen for its C-type car which will begin production in 2007. Called the Provis.Agent, it is the first agent-based PMC system for distributed real-time production monitoring that allows integration with other shop floor related applications.     

薄层色谱法鉴定原子印油印文盖印形成时间

建立了用薄层色谱法鉴定原子印油印文盖印形成时间的新方法。详细研究了萃取剂、反应时间、反应温度等的影响,建立了萃取动力学曲线。在优化条件下,盖印时间在36个月内的新鲜原子印油印文,萃取速率值与盖印时间的线性方程为y=-0.0166x＋0.7025（R2=0.9554）,检测下线为3个月。用该方法对10余种原子印文盖印形成时间进行了鉴定,均有同样结果。     

Identifying change point of a non-random pattern on control chart using artificial neural networks

An important step in root cause analysis is the identification of the time when process first changed. The time when a disturbance first manifested itself into the process is referred to as change point. Identification of the change point could help process engineer to perform root cause analysis effectively. In this paper, an estimator for the change point of a normal process mean using artificial neural network (ANN) is proposed. Five patterns of change namely single step, linear trend, systematic, cyclic, and mixture are studied. Whenever possible, results are compared numerically to the results obtained by other methods proposed by different researchers. First the type of change to be recognized by an ANN-based pattern recognizer is identified and then the change point in the process mean is estimated. Results indicate satisfactory performance for the proposed method that could be used as an effective method for root cause analysis by process engineer.     

Decentralized identification for multivariable integrating processes with time delays from closed-loop step tests

In order to identify those multivariable processes with integrating factors in their transfer function matrices, a simple yet robust decentralized identification method from closed-loop step tests is proposed. By the frequency response matrix computed from the closed-loop system data and the knowledge of the decentralized controller, the structural information of the multivariable integrating process is determined firstly and then the continuous parametric model with dead times is approximated similarly with the parameterization of the open-loop stable process. Computer simulations and an application to a 3 x 3 integrating multiple-tank water level system verify the validation of the proposed method even if the closed-loop system is affected by some stochastic noise sources.     

优化结合二叉树和帧时隙ALOHA的防碰撞算法

分析和比较了现有无线射频识别（RFID）中采用的防碰撞算法存在的问题,提出了一种优化结合二叉树（BT）和帧时隙ALOHA的新的防碰撞算法。提出的算法在阅读器与标签开始通讯时采用帧时隙的ALOHA算法,当有时隙发生碰撞时采用BT算法对其进一步识别。该算法根据曼彻斯特译码得到碰撞位,通过估算一帧中可能出现的碰撞情况,运用数学推导并通过R软件编程计算给出数学期望值。仿真实验显示：提出的算法充分发挥了两种算法的优点,其搜索次数、传输时延、吞吐率等重要指标都明显优于ALOHA算法,尤其是新的防碰撞算法的吞吐率比ALOHA算法提高了近50%。另外,传输负担的减小还使数据传输的安全性有了更高的保障。     

Characteristics of non-newtonian power law lubricants in step bearings and hydrostatic step seals

The effects of stepped film-thickness on the various characteristics of squeeze films, conical bearings and hydrostatic step seals, using a power law fluid as lubricant have been investigated. It has been shown that the load capacities of squeeze film bearings decrease and those of conical bearings and step seals increase, with the increase in the step height. With a hydrostatic step seal, the load capacity increases as the flow behaviour index of the power law fluid increases.     

激光扫描共聚焦表面等离子体共振系统实时监测单链DNA构象变化

脱氧核糖核酸(DNA)是染色体的重要组成部分,是一种主要的遗传物质,很多实验方法与理论模型被用来研究DNA与一些重要生物物种相互作用引起的构象变化。采用激光扫描共聚焦表面等离子体共振(LSCI-SPR)系统研究了一种特定单链DNA(ssDNA)分别与其互补DNA(cDNA)和汞离子(Hg~(2+))作用后的构象变化。将一端有荧光分子的ssDNA修饰在表面等离子体共振系统传感芯片上,通过观察荧光图像的变化来确定ssDNA与cDNA及Hg~(2+)之间相互作用而导致的构象变化,并通过动力学曲线计算出二者的结合速率分别为3.33×10~(-5) s~(-1)和1.42×10~(-4) s~(-1)。对于ssDNA-cDNA的相互作用,荧光图像没有变化。对于ssDNA-Hg~(2+)的相互作用,在通入Hg~(2+)后荧光发生猝灭。这些结果表明,激光扫描共聚焦表面等离子体共振系统在高灵敏实时监测ssDNA与其他特殊生物分子作用产生的构象变化和计算动力学参数方面有着广阔的应用前景。     

Analytical time constant design for jerk-limited acceleration profiles to minimize residual vibration after positioning operation in NC machine tools

The positioning operation of the axes of numerically controlled (NC) machine tools is essential before initiating their machining operation. Residual vibration following the positioning operations of the axes deteriorates the cycle time and quality of the machined parts. This study aims to develop a novel acceleration and deceleration design method to suppress the residual vibration during the high-speed positioning of NC machine tools. The proposed method suppresses the vibration by appropriately designing the jerk-limited acceleration profile during acceleration and deceleration. To design the jerk profile, the amplitude map that can represent the relationships between the acceleration parameters and the estimated vibration amplitude is developed. The proposed method suppresses the vibration amplitude without changing the total positioning time. To evaluate the effectiveness of this method, the residual vibration following the high-speed positioning motions was measured and simulated. The results confirm that the proposed method can effectively suppress the residual vibration.