Influence of tool path strategy on the cycle time of high-speed milling

This work at first look discusses the influence of the tool path strategy on the cycle time of high-speed milling operations. Experiments and predictions were focused on pocketing operations with a zig-zag tool path, quantifying the significant discrepancy between the programmed feed rate and the actual average feed rate. A mechanistic approach for cycle time evaluation is proposed. The mechanistic model construction is based on the experimental measurement of the machine tool acceleration and specific geometric assumptions regarding tool motion. For high feed rates, the proposed approach is capable of capturing the influence of the zig-zag tool path orientation on the machining cycle time.     

Production system with process quality control: modelling and application

Over the past decade, there has been a great deal of research dedicated to the study of quality and the economics of production. In this article, we develop a dynamic model which is based on the hypothesis of a traditional economic production quantity model. Taguchi's cost of poor quality is used to evaluate the cost of poor quality in the dynamic production system. A practical case from the automotive industry, which uses the Six-sigma DMAIC methodology, is discussed to verify the proposed model. This study shows that there is an optimal value of quality investment to make the production system reach a reasonable quality level and minimise the production cost. Based on our model, the management can adjust its investment in quality improvement to generate considerable financial return.     

Optimization of process parameters for pulsed laser milling of micro-channels on AISI H13 tool steel

This paper focuses on understanding the influence of laser milling process parameters on the final geometrical and surface quality of micro-channel features fabricated on AISI H13 steel. Optimal selection of process parameters is highly critical for successful material removal and high dimensional and surface quality for micro-sized die/mold applications. A set of designed experiments is carried out in a pulsed Nd:YAG laser milling system using AISI H13 hardened tool steel as work material. Arrays of micro-channels have been fabricated using a range of process parameters such as scanning speed (SS), pulse intensity (PI), and pulse frequency (PF). The relation between process parameters and quality characteristics has been studied with experimental modeling. Multi-criteria decision making for material and process parameter selection for desired surface quality and dimensional accuracy is investigated using an evolutionary computation method based on particle swarm optimization (PSO).     

Service process control: a method to compare dynamic robustness of alternative service processes

This paper contributes to the service engineering field by developing a procedure to compare the dynamic robustness of alternative service delivery processes. The procedure adapts an existing method for comparing the dynamic robustness of chemical process control systems. It has four steps: (a) characterisation of each type of uncertainty that affects the service plant; (b) Monte Carlo computer simulation of the process flowchart to determine how the service process responds to different combinations of uncertainties; (c) calculation of a quality index for each combination of uncertainties; and (d) plotting of a frequency distribution of these indices. The tighter the resulting distribution, the more robust the system. The procedure can be used to evaluate the effects of design and control changes in the service delivery process. To demonstrate the procedure, a modification to a hospital patient-treatment process is evaluated.     

基于多特征的PSO-MSVM动态过程质量异常模式识别

为了提高动态过程质量异常模式识别效率,将动态过程质量模式的均值特征与小波包分解特征作为分类特征,并构建两层多支持向量机识别模型进行分类.利用均值特征,在第一层MSVM中把动态过程变化趋势划分为正常与周期、上升与向上阶跃、下降与向下阶跃三大类别;采用小波包分解特征,在第二层MSVM中对这三大类别进行再分类.仿真结果表明提出的识别模型的识别精度相比采用单一特征的识别模型有明显提高.     

Global optimization of tool path for five-axis flank milling with a conical cutter

In this paper, optimum positioning of the conical cutter for five-axis flank milling of slender surfaces is addressed from the perspective of approximating the tool envelope surface to the data points on the design surface following the minimum zone criterion recommended by ANSI and ISO standards for tolerance evaluation. Based on the observation that a conical surface can be treated as a canal surface, i.e. envelope surface of one-parameter family of spheres, the swept envelope of a conical cutter is represented as a sphere-swept surface. Then, an approach is presented to efficiently compute the signed distance between a point in space and the swept surface without constructing the swept surface itself. The first order differential increment of the signed point-to-surface distance with respect to the differential deformation of the tool axis trajectory surface is derived. By using the distance function, tool path optimizations for semi-finish and finish millings are formulated as two constrained optimization problems in a unified framework, and a sequential approximation algorithm along with a hierarchical algorithmic structure is developed for the optimization. Numerical examples are given to confirm the validity and efficiency of the proposed approach. Comparing with the existing approaches, the present one improves the machining accuracy greatly. The rationale developed applies to general rotary cutters.     

基于动态数据流的密码函数加解密过程分析

在密码函数识别的基础上,采用九元组的形式定义了加解密过程依赖图,提出了基于动态数据流分析的函数依赖图构建框架,并设计了构建算法;采用垃圾调用删除、循环归约的方式对依赖图进行化简;基于标准密码算法依赖图知识库,设计了相似性判别算法对依赖图集合进行判别,测试结果验证了方法的可靠性与高效性。     

A multi-server queueing model with retrial connection arrivals as a model for optimisation of the traffic control

We consider a multi-server queueing model with a finite buffer and requests arriving in connections. The number of requests in a connection is random and unknown at the connection initiation instant. Requests, which belong to the connection, arrive in accordance with a Poisson process. Admission of connections to the system is regulated by means of so-called tokens. The pool of tokens is finite. If a connection arrives and there are no tokens available, it leaves the system forever or joins the orbit and retries for access later on. The steady-state distribution of the system is analysed. The problem of the throughput maximisation under the constraint that the request loss probability does not exceed a predefined value is numerically solved. The effect of the retrial intensity, correlation and variation in the arrival process and the probability to leave the system if tokens are not available is numerically highlighted.     

一种反馈过程神经元网络模型及在动态信号分类中的应用*

针对动态信号模式分类问题,提出了一种反馈过程神经元网络模型和基于该模型的分类方法。这种网络的输入可直接为时变函数,网络的信息传输既有与前馈神经元网络一样的前向流,也有后面各层节点到前层节点的反馈,且可对节点自身反馈输出信息,能直接用于动态信号的模式分类。由于反馈过程神经元网络在对输入样本的学习中增加了神经元输出信息的反馈,可提高网络的学习效率和稳定性。给出了具体学习算法,以时变函数样本集的分类问题为例,实验结果验证了模型和算法的有效性。     

Identification of the Tennessee Eastman challenge process with subspace methods

The Tennessee Eastman challenge process is a realistic simulation of a chemical process that has been widely used in process control studies. In this case study, several identification methods are examined and used to develop MIMO models that contain seven inputs and ten outputs. ARX and finite impulse response models are identified using reduced-rank regression techniques (PLS and CCR) and state-space models identified with prediction error methods and subspace algorithms. For a variety of reasons, the only successful models are the state-space models produced by two popular subspace algorithms, N4SID and canonical variate analysis (CVA). The CVA model is the most accurate. Important issues for identifying the Tennessee Eastman challenge process and comparisons between the subspace algorithms are also discussed.     

Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

Helical milling is a hole-making process which has been applied in hardened materials. Due to the difficulties on achieving high-quality boreholes in these materials, the influence of noise factors, and multi-quality performance outcomes, this work aims the multi-objective robust design of hole quality on AISI H13 hardened steel. Experiments were carried out through a central composite design considering process and noise factors. The process factors were the axial and tangential feed per tooth of the helix, and the cutting velocity. The noise factors considered were the tool overhang length, the material hardness and the borehole height of measurement. Response models were obtained through response surface methodology for roughness and roundness outcomes. The models presented good explanation of data variability and good prediction capability. Mean and variance models were derived through robust parameter design for all responses. Similarity analysis through cluster analysis was performed, and average surface roughness and total roundness were selected to multi-objective optimization. Mean square error optimization was performed to achieve bias and variance minimization. Multi-objective optimization through normalized normal constraint was performed to achieve a robust Pareto set for the hole quality outcomes. The normalized normal constraint optimization results outperformed the results of other methods in terms of evenness of the Pareto solutions and number of Pareto optimal solutions. The most compromise solution was selected considering the lowest Euclidian distance to the utopia point in the normalized space. Individual and moving range control charts were used to confirm the robustness achievement with regard to noise factors in the most compromise Pareto optimal solution. The methodology applied for robust modelling and optimization of helical milling of AISI H13 hardened steel was confirmed and may be applied to other manufacturing processes.     

自适应递推核学习及在橡胶混炼过程在线质量预报的工业应用

实时测取混炼胶门尼粘度是橡胶和轮胎厂十分关心和亟待解决的问题. 采用两阶段递推核学习建模方法, 按配方快速建立橡胶混炼过程门尼粘度的预报模型, 并对模型进行递推更新以适应过程的快速变化. 结合混炼过程的特点, 提出一种适合门尼粘度的性能指标, 并推导了采用快速留一交叉验证法对核学习模型参数进行自适应选择, 避免人为选取参数的片面性. 所研发的先进密炼信息集成与控制系统已在国内多家大型橡胶和轮胎厂上线应用. 门尼粘度实时预报的工业应用结果表明了其实用和有效性, 对橡胶混炼过程具有重要的现实和经济意义.     

基于基函数展开的双隐层过程神经元网络及其应用

提出一类基于基函数展开的双隐层过程神经元网络模型．过程神经元隐层完成对输入信息过程模式特征的提取和对时间的聚合运算，非时变一般神经元隐层用于提高网络对系统输入输出之间复杂关系的映射能力．在输入空问中引入一组函数正交基，将输入函数和网络权函数表示为该组正交基的展开形式，利用基函数的正交性简化过程神经元聚合运算．以旋转机械故障诊断和油藏开发过程采收率的模拟为例，验证了模型和算法的有效性。     

基于一种新形核函数高斯过程的双频微带天线设计

针对采用高斯过程进行建模时,不同核函数形式有着不同学习效果的问题。提出了一种自定义的平方指数形式的核函数,并基于多项式函数拟合对这种新形的核函数进行了数值仿真。仿真结果表明,该核函数不但可以提高模型的精确度和有效性,而且可以提高模型的学习能力和泛化能力。最后,将基于该核函数的高斯过程建模方法用于矩形双频微带天线优化设计和WLAN双频单极子天线优化设计,进一步证明了这种方法是可行的和有效的。     

Prioritised best effort routing with four quality of service metrics applying the concept of the analytic hierarchy process

In this paper, a new approach that applies the concept of the Analytic Hierarchy Process (AHP) in the area of routing in communication networks is proposed. AHP is a well-known model in the area of decision making with multiple objectives. In addition, a new algorithm called Enhanced Best Effort Quality of Service Routing (QoS) with Multiple Prioritised Metrics is proposed for connection-oriented point-to-point communications. Four QoS metrics have been considered: delay, bandwidth, security and loss probability. The results presented and discussed in this paper are focussed on demonstrating the effects of metric prioritisation on the routing decisions. It is found that changing priority of a metric from 0 (the lowest priority) to 1 (the highest priority) applying the proposed algorithm improves the value of that metric by an average of (20–60)% for 90% of utilisation range.