Modeling of machine failures in a flexible manufacturing cell with two machines served by a robot

In this study, a stochastic model is developed to analyze performance measures of a flexible manufacturing cell (FMC) under different operational conditions, including machine failures and repairs. The FMC consists of two machines served by a robot for loading and loading purposes, and a pallet handling system. The model is based on Markov processes and determines closed-form solutions for the probabilities of system states that are used to calculate system performance measures, such as production output rate and utilizations of system components under different parametric conditions and equipment failures and repairs.     

AutoCAD 中基于超图约束驱动参数化设计的实现

 使用超图表示约束模型,采用基于超图约束驱动的几何推理约束满足法进行参数化设计,几何实体的计算基于特征点。作者结合在ＡｕｔｏＣＡＤ上开发参数化设计模块的实践,得出该方法能处理多实体约束关系（如面积约束）,提高求解效率,降低时间复杂度。     

Developing a fuzzy proportional–derivative controller optimization engine for engineering design optimization problems

In real world engineering design problems, decisions for design modifications are often based on engineering heuristics and knowledge. However, when solving an engineering design optimization problem using a numerical optimization algorithm, the engineering problem is basically viewed as purely mathematical. Design modifications in the iterative optimization process rely on numerical information. Engineering heuristics and knowledge are not utilized at all. In this article, the optimization process is analogous to a closed-loop control system, and a fuzzy proportional–derivative (PD) controller optimization engine is developed for engineering design optimization problems with monotonicity and implicit constraints. Monotonicity between design variables and the objective and constraint functions prevails in engineering design optimization problems. In this research, monotonicity of the design variables and activities of the constraints determined by the theory of monotonicity analysis are modelled in the fuzzy PD controller optimization engine using generic fuzzy rules. The designer only needs to define the initial values and move limits of the design variables to determine the parameters in the fuzzy PD controller optimization engine. In the optimization process using the fuzzy PD controller optimization engine, the function value of each constraint is evaluated once in each iteration. No sensitivity information is required. The fuzzy PD controller optimization engine appears to be robust in the various design examples tested.     

设计的蝴蝶效应：当生活方式成为设计对象

目的提出生活方式从设计语境成为设计对象的学术观点;解析生活方式作为设计对象的本体属性;围绕生活方式作为设计对象的学术观点,探索相应的设计方法。方法通过文献综述寻找生活方式作为设计对象的理论依据;运用叙事探究、哲学抽象和案例分析的方法,解析生活方式本体属性,建构相应的设计方法。结论行为(Behavior)、环境(Environment)、价值观(Value)是生活方式作为设计对象的三个基本要素:行为是其中较为显性的维度,包括行为内容和行为习惯;环境既包括物理环境,也包括社会和制度环境;价值观一方面是行为决策和环境认知的内因,另一方面其自身也随着经历的成长发生着改变。体验(Experience)作为生活的整体表现或感受,渗透在生活的方方面面,共同构成了生活方式作为设计对象的BEV-E要素模型。生活方式的形成是一个在经历中不断反思、构想和行动的过程,生活方式设计IDR方法,即Initiating(启动)、Developing(养成)和Recognizing(确认),倡导关注过程中由于不确定因素带来的不可预期后果,通过设计引导、环境支持和个体主导的方式,构想和引导向健康生活方式的转型,产生良性蝴蝶效应。     

船舶运动模拟器ADRC控制系统的设计与仿真

针对并联式船舶运动模拟器具有多变量,强耦合,结构复杂,难以获得精确的数学模型等特点,给出了一种ADRC控制器设计及实现方案.使用参数化设计方法,在Simulink中构建了机械、液压、控制一体化多域仿真模型,分析了控制器的参数整定方法,仿真结果表明了仿真模型和ADRC控制器的有效性.     

Adaptive PID control based on explicit criterion minimization

Abstract

PID control has been widely used in industry for a long time. Under certain circumstances, it is necessary to retune the PID controller to obtain good performance. Recently, the developments in modern control theories and computing techniques have made automatic tuning of the PID controller feasible which provides better performance. In this paper, an adaptive PID controller based on explicit criterion minimization having the same structure as conventional PID controller is proposed. This new controller's design is based on the method of Ljung and Trulsson. Various properties of the method are described. Simulation studies using the new method show that the performance is satisfactory for control of minimum phase and nonminimum phase systems.     

An evaluation scheme for assessing the worth of automatically generated design alternatives

This paper introduces a tool called the designer preference modeler (DPM) that analyzes the designer’s decision making during concept evaluation, and constructs a designer preference model to be used for evaluation of automatically generated design alternatives. The method is based on establishing an interaction between a designer and a computational synthesis tool during conceptual design. The synthesis software generates design alternatives using a catalog of design knowledge formulated as grammar rules which describe how electromechanical designs are built. DPM carefully selects a set from these alternatives and presents it to the designer for evaluation. The designer’s evaluations are translated into a preference model that is subsequently used to search the solution space for best designs. Application of the method to the design of a consumer product shows DPM’s range of capabilities.     

Direct control algorithm for doubly fed induction generators in weak grids

An algorithm utilising direct feedbacks of torque and reactive power for the control of a doubly fed induction generator (DFIG) is proposed. Although the algorithm is based on field-oriented control, the algorithm calculates the feedback and feed-forward variables in the stator reference frame to reduce the number of coordinate transformations. Since the algorithm uses a single-loop approach instead of a cascaded loop design, the tuning of the controller is easier and the response time is faster when compared to those of most existing methods. The internal model control (IMC) design method is used in the proposed scheme to formulate the controller parameters. Measures on the possible voltage variations are included to increase the robustness of the system. Computer simulation and experimental implementation are reported. The results show that the algorithm can control the torque and reactive power independently. Harmonic distortions generated by the system are not noticeable because of the use of constant switching frequency.     

Multi-objective system reliability-based optimization method for design of a fully parametric concept car body

This article investigates multi-objective optimization under reliability constraints with applications in vehicle structural design. To improve computational efficiency, an improved multi-objective system reliability-based design optimization (MOSRBDO) method is developed, and used to explore the lightweight and high-performance design of a concept car body under uncertainty. A parametric model knowledge base is established, followed by the construction of a fully parametric concept car body of a multi-purpose vehicle (FPCCB-MPV) based on the knowledge base. The structural shape, gauge and topology optimization are then designed on the basis of FPCCB-MPV. The numerical implementation of MOSRBDO employs the double-loop method with design optimization in the outer loop and system reliability analysis in the inner loop. Multi-objective particle swarm optimization is used as the outer loop optimization solver. An improved multi-modal radial-based importance sampling (MRBIS) method is utilized as the system reliability solver for multi-constraint analysis in the inner loop. The accuracy and efficiency of the MRBIS method are demonstrated on three widely used test problems. In conclusion, MOSRBDO has been successfully applied for the design of a full parametric concept car body. The results show that the improved MOSRBDO method is more effective and efficient than the traditional MOSRBDO while achieving the same accuracy, and that the optimized body-in-white structure signifies a noticeable improvement from the baseline model.     

Non-Gaussian models for stochastic mechanics

Memoryless transformations of Gaussian processes and transformations with memory of the Brownian and Lévy processes are used to represent general non-Gaussian processes. The transformations with memory are solutions of stochastic differential equations driven by Gaussian and Lévy white noises. The processes obtained by these transformations are referred to as non-Gaussian models. Methods are developed for calibrating these models to records or partial probabilistic characteristics of non-Gaussian processes. The solution of the model calibration problem is not unique. There are different non-Gaussian models that are equivalent in the sense that they are consistent with the available information on a non-Gaussian process. The response analysis of linear and non-linear oscillators subjected to equivalent non-Gaussian models shows that some response statistics are sensitive to the particular equivalent non-Gaussian model used to represent the input. This observation is relevant for applications because the choice of a particular non-Gaussian input model can result in inaccurate predictions of system performance.     

Multivariate tolerance design using quality loss

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. We extend our prior research on tolerance allocation by developing both parametric and nonparametric methods for a multivariate set of performance measures that are functions of a common set of design parameters. The parametric method is novel and assumes full information about the probability distribution of design parameter processes. The proposed nonparametric method assumes that only partial information is available and significantly extends prior research by considering a more contemporary and realistic model for manufacturer costs. For both methods we derive economically based models that represent the costs, both internal (supplier) and external (manufacturer), of tolerance allocation under several different process scenarios. These scenarios are based on the manner of disposition of nonconforming product. For the parametric methods we derive tolerance allocation solutions that jointly minimize expected total cost of the supplier and manufacturer. For the nonparametric methods we derive solutions for tolerance allocation that jointly minimizes the maximum expected total cost. An example in the fabrication of a rubber tread compound is used to: (i) demonstrate the implementation of our proposed methodologies for tolerance allocation; (ii) illustrate and compare the nonparametric and parametric methods; land iii) assess the sensitivity of optimal tolerance allocations to changes in process model types, cost coefficient estimates, and manner of disposition of nonconforming product.     

曲线梁桥地震响应的简化分析方法

曲线梁桥的平面不规则性引起的弯扭耦合效应,导致了地震响应的复杂性。对弹性支座上的刚性桥面系统建立了具有刚度偏心的简单曲线梁桥模型,给出了自振特性和地震响应的简化计算方法。通过数值模拟比较,系统地分析了各种影响因素及其对曲线梁桥动力响应的影响规律和计算图表,可以在抗震初步设计中参考使用。     

设计建构论:数据智能时代的新兴设计认识论

目的 在数据智能时代提出了设计建构论的设计认识论。方法 从建构及建构主义的定义出发,明确设计具有的知识属性并以建构的视角思考创新设计发展,分析了设计认识论的研究进展和意义。结果 提出了设计建构论这一新兴设计认识论,明确了设计建构论的概念、特征、实践立场与理论价值,从本体建构论(求真)、行为建构论(向善)、价值建构论(尚美)三个层次对设计建构论进行了深入剖析,并对设计建构论的未来研究展开了思考。结论 设计建构论为如何解决复杂问题提供了全新的设计理论与方法体系,对建立中国产品自信、中国设计自信、中国文化自信具有重要的现实意义。     

Combinatorial process and plant design for agile manufacture

The concept of combinatorial process, equipment and plant design is introduced and developed for the specific examples of fluid separations and crystallisation. It is shown that traditional methods of process design may miss options that are identified using the combinatorial approach. New options may lead to novel types of processes and equipment. Application of this methodology is suggested in terms of scanning the multi-dimensional space describing the process, equipment and plant attributes. The new approach is particularly appropriate for the design of agile plants for families of products and where decisions have to be made as how best to re-configure an existing facility to manufacture a new product.     

Design optimization of a prescribed vibration system using conjoint value analysis

This article details a novel design optimization strategy for a prescribed vibration system (PVS) used to mechanically filter solids from fluids in oil and gas drilling operations. A dynamic model of the PVS is developed, and the effects of disturbance torques are detailed. This model is used to predict the effects of design parameters on system performance and efficiency, as quantified by system attributes. Conjoint value analysis, a statistical technique commonly used in marketing science, is utilized to incorporate designer preferences. This approach effectively quantifies and optimizes preference-based trade-offs in the design process. The effects of designer preferences on system performance and efficiency are simulated. This novel optimization strategy yields improvements in all system attributes across all simulated vibration profiles, and is applicable to other industrial electromechanical systems.     

基于结合分析的产品意象造型设计研究

为设计出符合消费者感性需求的产品,提出基于结合分析的产品意象造型设计方法。首先采用多元尺度法和聚类分析法选择典型样本,进而应用形态分析法确定产品的属性和各属性的水平。其次,利用因子分析法确定产品的感性意象,并用造型吸引力对其进行整合。在此基础上,使用对应分析法对感性意象和产品属性的关系进行探讨。最后,利用结合分析建立二者之间的数学模型。该文结合办公座椅进行研究,结果表明该方法是正确可行的。     

Solving and visualizing nonlinear parametric constraints in control based on quantifier elimination

We present a new method with a software tool for parametric robust control synthesis by symbolic-numeric computation. The method is a parameter space approach and it is especially effective for analysis and design of fixed-structure controllers of rational type, which encompass PI and PID controllers. The real quantifier elimination (QE), which is one of the recent progresses in the symbolic computation, plays a key role in our development. The QE-based approach can uniformly deal with a lot of important design specifications for robust control such as frequency restricted H _∞ norm constraints, stability (gain/phase) margin and stability radius specifications, and pole location requirement by reducing such specifications to a particular type of formulae called a “sign definite condition (SDC)”. This is also useful for improving the efficiency of QE computations since we can utilize an efficient QE algorithm specialized to the SDC using the Sturm-Habicht sequence. We have developed a MATLAB toolbox for robust parametric control based on a parameter space approach accomplished by QE. The QE-based parameter space approach and numerical simulation of performances for specific controller parameter values taken from a controller parameter space are integrated conveniently in our toolbox with the assistance of a graphical user interface (GUI). With our toolbox the feasible regions of controller parameters are visualized in a parameter space for the controllers with three or two parameters. This enables control engineers to achieve multi-objective robust controller synthesis smoothly. We also discuss how to merge the numerical computation and the symbolic operation to make our new design methods more efficient in practical control design.     

Evaluation of ductility requirements in current design guidelines for FRP strengthening

Advanced composites are widely used for the strengthening of existing concrete structures. Current design guidelines give basic requirements on how to model the enhancement of structural performance of concrete members using surface bonded FRP (fibre reinforced polymer) reinforcement. With respect to this, it is of interest to evaluate the ductility requirements which are explicitly or implicitly imposed by design guides. Based on an evaluation of four major design guidelines in Europe, Japan and North-America, and a small parametric study, the ductility aspect of the design of FRP strengthened concrete members is verified. It appears that the ductility of flexural members strengthened with FRP should be considered with care, as reduced deformability is obtained at ultimate, though generally a minimum deformability is implicitly obtained in a proper design. At the other hand, ductility enhancement by means of FRP confinement is explicitly considered in the design guidelines.