Development of a machine tool selection system using AHP

The selection of appropriate machines is one of the most critical decisions in the design and development of an efficient production environment. In this study, we propose a decision support system for machine tool selection using an effective algorithm, the analytic hierarchy process. In the selection process, we first consider qualitative decision criteria that are related to the machine properties. Reliability and precision analyses may be included in the detailed evaluation procedure. Furthermore, the decision-maker may take into account the economical considerations through cost analysis. In addition, the robustness of the selection procedure may be evaluated using sensitivity analysis. An illustrative example of machine tool selection using the proposed methodology and the software implementation are provided.     

Behavioural modelling for design decomposition and design equations derivation

Analysis of system performance is necessary at various stages of the design process. For this purpose, design equations should be identified or derived, which establish the links between the required performance and the physical structure of the designed system and system inputs/outputs. There has been no generic methodology for the derivation of design equations at the early design stage. In this paper, we present a behavioural modelling methodology to address the problem. It is achieved by modelling the system behaviours as one or more behavioural processes, and deriving design equations from each individual behaviour of the process. To simplify the task as well as those subsequent design tasks, we also discuss the issue of performance analysis oriented design decomposition. This is achieved by developing two design hierarchies with established links between them. An algorithm for automatic design decomposition is subsequently proposed. This algorithm is applicable both before and after the derivation of design equations. Finally, a design case is also studied to illustrate and demonstrate the proposed methodologies.     

汽车覆盖件成形性集成分析技术研究

提出在汽车覆盖件早期设计阶段将基于成形工艺知识的定性分析与基于一步模拟法的定量分析相结合进行覆盖件特征模型的成形性分析。在基于知识的覆盖件成形性定性分析中提出一种自动识别与交互定义相结合的覆盖件形状特征识别方法 ,提出汽车覆盖件集成信息模型和CBR/RBR集成的推理方法。在此基础上提出基于知识的汽车覆盖件冲压工艺设计系统的总体结构和系统的冲压工艺设计流程     

汽车乘员舱安全性与舒适性多学科设计优化

概念设计阶段汽车乘员舱的安全性和舒适性设计是关键任务,两者具有耦合效应,将多学科设计优化运用到乘员舱的设计中实现两个学科的并行设计。针对某款车的乘员舱布置,在该车100%正面碰撞试验基础上,通过乘员损伤分析软件建立该车的正面碰撞乘员约束系统模型并对模型进行验证用于评估其安全性;同时也基于关节强度的概念建立乘员舒适性模型。将多学科设计优化运用到乘员舱的设计中,避免了传统设计方法对安全性和舒适性的单独优化,实现了两个学科的并行设计,缩短了开发周期,最大化了乘员舱的整体性能。为提高计算效率,通过试验设计构建乘员约束系统的Kriging近似模型用于代替仿真模型。结果表明,该方法在较好地满足乘员安全性的同时提高了乘员的乘坐舒适性,在乘员舱布置方面具有较强的工程实用性。     

Method of Constructing a 3D Friction Map for a Rubber Tire Tread Sliding Over a Rough Surface

An experimental methodology for constructing a 3D friction map, which depends on normal pressure, sliding velocity, and temperature, for tire tread rubber has been presented. The methodology of constructing a 3D friction map is based on the principle of temperature–velocity superposition, which makes it possible to combine the obtained experimental data into one sculpted surface. Two types of the tread rubbers were investigated that are used in summer passenger tires and heavy-loaded all-metal tires. The results of analyzing the obtained 3D friction maps have been presented. The influence of normal pressure and sliding velocity to the amount and position of the values of coefficient of friction of the rubber sliding over the sandpaper surface with the specified abrasive grit has been considered.     

Solving multiple response optimisation problems using adaptive neural networks

This paper describes an integrated methodology using experimental designs and neural networks technologies for solving multiple response problems. This new methodology consists of an experiment reference template for designing and collecting training data samples and a parallel distributed computational adaptive neural network system to provide a powerful tool for data modelling, guiding experimentation and empirical investigations. While the experiment reference template is for determining the measurements to adopt in order to extract maximum information within minimum experimental efforts, the adaptive neural network provides a nonlinear multivariate data-fitting algorithm for analysing the results of the experimental design and providing decision support. This integrated methodology is used to model and optimise a multiple response metal inert gas (MIG) welding process. The neural network is trained with optimum welding experimental data, tested and compared in an actual welding environment in terms of weld quality. The relevant data is established using experimental design methods and is highlighted in the case study. The implementation for this case study was carried out using a semi-automatic welding facility, to mass weld a 20 in.×0.438 in. pin/box onto a 20 in.×0.5 in.×37 ft pipe (tubular drilling products), in an actual workshop which makes oilfield equipment. The entire range of welding combination that the process might be subject to during actual welding operations is included to study the weld quality.     

电缆压接性能测试系统设计及实验

为了推进电缆中间接头压接制作工艺的规范化,提出并设计了一套电缆压接性能测试系统及其实验方案。该平台结合了设计加压单元,以及实验测试机械装置及传感器系统,并且设计有配套的软件系统,进行电缆中间接头压接实验。通过实验测试方案,可以获得电缆压接制作过程中的实时实验数据,以及电缆机械性能及电气性能衡量数据,为电缆中间接头的性能机理分析提供数据依据。该系统及实验为电缆中间接头的压接制作工艺过程提供参考,并为自动压接设备的设计提供了实验依据。     

A hybrid root transformation and decision on belief approach to monitor multiattribute Poisson processes

Most of industrial applications of statistical process control involve more than one quality characteristics to be monitored. These characteristics are usually correlated, causing challenges for the monitoring methods. These challenges are resolved using multivariate quality control charts that have been widely developed in recent years. Nonetheless, multivariate process monitoring methods encounter a problem when the quality characteristics are of the attribute type and follow nonnormal distributions such as multivariate binomial or multivariate Poisson. Since the data analysis in the latter case is not as easy as the normal case, more complexities are involved to monitor multiattribute processes. In this paper, a hybrid procedure is developed to monitor multiattribute correlated processes, in which number of defects in each characteristic is important. Two phases are proposed to design the monitoring scheme. In the first phase, the inherent skewness of multiattribute Poisson data is almost removed using a root transformation technique. In the second phase, a method based on the decision on belief concept is employed. The transformed data obtained from the first phase are implemented on the decision on belief (DOB) method. Finally, some simulation experiments are performed to compare the performances of the proposed methodology with the ones obtained using the Hotelling T ² and the MEWMA charts in terms of in-control and out-of-control average run length criteria. The simulation results show that the proposed methodology outperforms the other two methods.     

Development of a hydroforming setup for deep drawing of square cups with variable blank holding force technique

Sheet hydroforming is a process that uses fluid pressure for deformation of a blank into a die cavity of desired shape. This process has high potential to manufacture complex auto body and other sheet metal parts. Successful production of parts using hydroforming mainly depends on design aspects of tooling as well as control of important process parameters such as closing force or blank holding force (BHF) and variation of fluid pressure with time. An experimental setup has been designed and developed for hydroforming of square cups from thin sheet materials. Square cups have been deep drawn using constant and variable BHF techniques. A methodology has been established to determine the variable BHF path for successful hydroforming of the cups with the assistance of programmable logic controller and data acquisition system. Finite element (FE) simulations have also been carried out to predict formability with both of these techniques. It has been found that it is possible to achieve better formability in terms of minimum corner radius and thinning in the case of variable BHF technique than in the case of constant BHF technique (constant force during forming and calibration). The results of FE analysis have been found to be in good agreement with experimental data.     

Interactive robust optimal design of plastic injection products with minimum weldlines

A new robust optimal design methodology has been developed and applied to the design of plastic injection molding products. Taguchi’s robust design method and an optimal design search algorithm are integrated with a commercial CAE simulation tool. A direct search-based optimization procedure is implemented with the considerations of process variations as well as uncontrollable noise variables. The Interactive Design Space Reduction Method (IDSRM) based on orthogonal arrays for design of experiments is developed as a general optimization tool. Using the system, designers can interactively adjust the design space during the searching process for the optimal solution based on the outcomes of the experiments. The developed methodology is applied to an industrial application: a molding process design of an automobile front bumper to minimize the weldline, a form defect of plastic parts. Compared with the initial design solution, the optimized design aided by the proposed methodology shows a more efficient and better result in terms of design robustness against process variations.     

Development of Expert System for Concurrent Product Design and Planning for Assembly

This paper addresses the development of an expert system for concurrent product design and assembly planning (CDAPFAES) including conceptual design, detailed design, assemblability analysis and design for assembly, assembly system design, assembly process planning and stimulation, and technical–economics justification. This approach is implemented through an agent-based framework with concurrent integration of multiple cooperative knowledge sources and software. This intelligent system can offer systematic assistance for assembly design and planning in the early stage of product development and facilitate, as far as possible, the use of flexible assembly equipment, including robots. Finally, this new design methodology is illustrated with a successful implementation of a switch product design.     

Dominant root locus in state estimator design for material flow processes: A case study of hot strip rolling

The purpose of the paper is to achieve a constrained estimation of process state variables using the anisochronic state observer tuned by the dominant root locus technique. The anisochronic state observer is based on the state-space time delay model of the process. Moreover the process model is identified not only as delayed but also as non-linear. This model is developed to describe a material flow process. The root locus technique combined with the magnitude optimum method is utilized to investigate the estimation process. Resulting dominant roots location serves as a measure of estimation process performance. The higher the dominant (natural) frequency in the leftmost position of the complex plane the more enhanced performance with good robustness is achieved. Also the model based observer control methodology for material flow processes is provided by means of the separation principle. For demonstration purposes, the computer-based anisochronic state observer is applied to the strip temperatures estimation in the hot strip finishing mill composed of seven stands. This application was the original motivation to the presented research.     

改进MSPCA的研究与应用

针对PCA方法单尺度建模的局限性,将小波分析和主元分析综合起来,引入了主元子空间之间的差别的概念,提出了新的检测工具改进MSPCA.与MSPCA方法相比,改进MSPCA方法降低了随机误差对测量数据的影响,提高了过程性能监视和故障诊断的准确性.仿真实例验证了该方法的有效性.     

Simulation modeling of nuclear steam generator water level process--a case study

Simulation modeling of the nuclear steam generator (SG) water level process in Qinshan Nuclear Power Plant (QNPP) is described in this paper. A practical methodology was adopted so that the model is both simple and accurate for control engineering implementation. The structure of the model is in the form of a transfer function, which was determined based on first-principles analysis and expert experience. The parameters of the model were obtained by taking advantage of the recorded historical response curves under the existing closed-loop control system. The results of process dimensional data verification and experimental tests demonstrate that the simulation model depicts the main dynamic characteristics of the SG water level process and is in accordance with the field recorded response curves. The model has been successfully applied to the design and test of an advanced digital feedwater control system in QNPP.     

基于ICA的气体模式识别方法研究

文中提出一种基于独立成分分析的非监督气体模式识别方法,用多元统计理论中的独立成分分析(independent component analysis-ICA)来分析金属氧化物半导体气体传感器阵列响应数据,进而实现对不同种类气体的分类.对所设计的电子鼻实验系统测量得到的气体传感器阵列稳态响应数据进行了白化和快速定点独立成分分析(FastICA)处理.实验结果表明该方法对区分一氧化碳(CO)、甲烷(CH_4)和氢气(H_2)3种气体有很高的识别率.     

Applying a software framework for supervisory control of a PLC-based flexible manufacturing systems

In this paper, a software framework for a distributed flexible manufacturing system is presented where, as a main design goal, we consider that the functionalities are offered to other components with no effects on the robustness of the system and where security specifications are tackled without the flexibility losses. In this way, the use of the supervisory control theory (SCT) is considered. Also, a methodology that makes it easier to implement these functionalities at a PLC-based system is presented. A real application of the developed framework is presented, and the implementation is done over an industrial-size device, so the technical feasibility of the methodology is proved. As the framework considers the services offered by the device, it can be used at different manufacturing tasks, so the approach can be applied to any kind of industrial process unit.     

Analysis of shrinkage and warpage in an injection-molded part with a thin shell feature using the response surface methodology

This paper presents a systematic methodology to analyze the shrinkage and warpage in an injection-molded part with a thin shell feature during the injection molding process. The systematic experimental design based on the response surface methodology (RSM) is applied to identify the effects of machining parameters on the performance of shrinkage and warpage. The experiment plan adopts the centered central composite design (CCD). The quadratic model of RSM associated sequential approximation optimization (SAO) method is used to find the optimum value of machining parameters. One real case study in the injection molding process of polycarbonate/acrylonitrile butadiene styrene (PC/ABS) cell phone shell has been performed to verify the proposed optimum procedure. The mold temperature (M _T), packing time (P _t), packing pressure (P _P) and cooling time (C _t) in the packing stage are considered as machining parameters. The results of analysis of variance (ANOVA) and conducting confirmation experiments demonstrate that the quadratic models of the shrinkage and warpage are fairly well fitted with the experimental values. The individual influences of all machining parameters on the shrinkage and warpage have been analyzed and predicted by the obtained mathematical models. For the manufacture of PC/ABS cell phone shell, the values of shrinkage and warpage present the reduction of 37.8 and 53.9%, respectively, using this optimal procedure.     

Optimized robust control for industrial unstable process via the mirror-mapping method

In this work, a novel optimized robust control algorithm, based on the mirror-mapping method, is proposed for a class of industrial unstable process with time delay. The optimizing criterion is to minimize the sensitivity function to enhance its robustness. The controllers are designed based on the Padé approximated mirror-mapping process with a stable form, other than the original unstable system. The developed algorithm could release the internal stability constraints to the unstable plant. By using the graphical stability criterion, a systematic methodology is derived to obtain the exact stabilizing region, where the sole design parameter is related to the stability degree of the closed-loop system. The proposed algorithm is with characteristics of concise and efficient design. Three experiments has been employed to illustrate that the control effects can achieve the satisfied performance in aspects of disturbance rejection and robustness.     

A study of advanced die-casting technology integrating CAD/RP/FEA for Zn castings

By means of computer aided engineering (CAE) is developed an integrate CAD/RP/FEA system to assist reducing the lead-time of die-castings design and upgrade the die-casting manufacturing technology parameters for zinc castings. The rapid die-casting methodology developed integrates: conceptual design; virtual prototyping (VP), rapid prototyping (RP), P-Q² technique, finite element analysis (FEA) to improve die-casting process and numerical control (NC) to upgrade die-casting manufacturing parameters. Thermal fluid flow and heat transfer modelling are performed to simulate die-casting manufacture technology to predict defects, increase yield and to improve the manufacturing process. An improved die-casting manufacturing process supported via CAD/RP/FEA technologies and NC control are demonstrated through a die-casting case study to manufacture sound zinc die-castings and conclusions are presented.