An expert system for experimental design in off-line quality control

Abstract: Robust design is an efficient method for designing high quality products at low cost. The method examines the effect of a large number of design factors on the variability of a product's response due to various sources of disturbance. This effect can be observed efficiently by studying a large number of variables simultaneously through balanced, orthogonal array experiments, and by analyzing the resulting data using variance decomposition methods. In this paper we describe an expert system prototype for designing efficient experiments. Given the information on various parameters and their levels, the system designs an experiment using orthogonal arrays. This expert system is implemented in Prolog, which is a logic programming language for artificial intelligence research and expert systems development. The system was implemented under the P-Shell knowledge programming environment on UNIX.     

An automated method for the preparation of orthogonal arrays for use in Taguchi designed experiments

In the last several years, the use of designed experiments in manufacturing and engineering design environments has become increasingly popular through the introduction of the ideas of Dr. G. Taguchi. The Taguchi Method, a systematic technique for experimental design and analysis, employs team oriented solutions to analyze design and production problems and their causes. The Taguchi Method as provided a simplified approach to the design of statistically significant experiments. This has greatly increased the number of experimental design practitioners.

This paper presents a computer program that addresses the need for an automated system able to design the experimental matrices for the orthogonal arrays that are required by Taguchi's Method. The program was written tode sign simple arrays as well as complex multi-level arrays with two-way interactions.     

Optimum design of sensor arrays via simulation-based multivariate calibration

This paper is concerned with the optimum design of sensor arrays (i.e., electronic noses or tongues) using simulation experiments. The proposed design method considers multiple criteria simultaneously for the evaluation of sensor arrays, and a multiple objective tabu search algorithm was adapted to search for a number of Pareto optimum array designs in terms of those criteria. The evaluation of a candidate sensor array is based on its multivariate calibration model, which is efficiently estimated from well-designed simulation experiments. The method can be used to optimize the design of both linear and nonlinear sensor arrays.     

Efficient striping techniques for variable bit rate continuous media file servers

The performance of striped disk arrays is governed by two parameters: the stripe unit size and the degree of striping. In this paper, we describe techniques for determining the stripe unit size and degree of striping for disk arrays storing variable bit rate continuous media data. We present an analytical model to determine the optimal stripe unit size in redundant and non-redundant disk arrays. We then use the model to study the effect of various system parameters on the optimal stripe unit size. To determine the degree of striping, we first demonstrate that striping a continuous media stream across all disks in the array causes the number of clients supported to increase sub-linearly with increase in the number of disks. To overcome this limitation, we propose a technique that partitions a disk array and stripes each media stream across a single partition. We then propose an analytical model to determine the optimal partition size and maximize the number of clients supported by the array.     

基于改进遗传算法的圆阵稀布方法

由于圆形阵列所具有的特性,使其正得到日益广泛的应用,但是圆阵方向图却具有相对主瓣较高的旁瓣电平。为此,针对稀布圆形阵列的天线单元使旁瓣电平尽量降低的问题,应用改进的遗传算法,取角度差值为染色体的基因,进行阵列孔径、单元个数、最小间隔一定的稀布优化排列,减小了遗传算法的搜索空间,提高了搜索效率。仿真结果表明:该方法能有效提高收敛速度、降低圆阵的旁瓣电平。     

A Genetic Algorithm for Multiobjective Robust Design

The goal of robust design is to develop stable products that exhibit minimum sensitivity to uncontrollable variations. The main drawback of many quality engineering approaches, including Taguchi's ideology, is that they cannot efficiently handle presence of several often conflicting objectives and constraints that occur in various design environments.Classical vector optimization and multiobjective genetic algorithms offer numerous techniques for simultaneous optimization of multiple responses, but they have not addressed the central quality control activities of tolerance design and parameter optimization. Due to their ability to search populations of candidate designs in parallel without assumptions of continuity, unimodality or convexity of underlying objectives, genetic algorithms are an especially viable tool for off-line quality control.In this paper we introduce a new methodology which integrates key concepts from diverse fields of robust design, multiobjective optimization and genetic algorithms. The genetic algorithm developed in this work applies natural genetic operators of reproduction, crossover and mutation to evolve populations of hyper-rectangular design regions while simultaneously reducing the sensitivity of the generated designs to uncontrollable variations. The improvement in quality of successive generations of designs is achieved by conducting orthogonal array experiments as to increase the average signal-to-noise ratio of a pool of candidate designs from one generation to the next.     

Determination of an optimal configuration of operating policies for direct-input-output manufacturing systems using the Taguchi method

Some modern manufacturing systems have workstations directly integrated with a centralized storage and handling system for work-in-process. We consider a Direct-Inlet-Output manufacturing system(DIOMS) which has a number of machine centers placed along a built-in automated storagejretrieval system(AS/RS). The storagdretrievai(S/R) machine handles parts placed on pallets for the machine centers located at either one or both sides of the AS/RS.

This paper investigates the operational aspect of DIOMS by the Taguchi method. Four operating policies including input sequencing control. dispatching rule for the S/R machine, machine center-based part type selection rule, and storage assignment policy are treated as design factors. For the performance characteristics, man flow time and throughput are adopted. The number of machine centers, the number of part types, demand rate, processing time and the rate of each part type. vertical and horizontal speed of the SIR machM and the size of a local buffer in the machine centers are considered as noise factors in generating various DIOMS environments. A robust design experiment with inner and outer orthogonal arrays are conducted by computer simulation, and an optimal configuration of operating policies is presented which consists of a combination of the level of each design factor. The validity of the optimal configuration is investigated by comparing its SN ratios with those obtained by an experiment with fiill factorial designs.     

求解正交数组问题的拟物拟人算法

此工作是方开泰工作的继续，正交数组在制造业和高技术产业的试验中有着广泛的应用，目前正交数组构造的研究相当活跃，现有的许多构造方法很复杂且所能构造的类型有限。提出了一个构造正交数组简单而效的方法－拟物拟人算法，应用该算法已经独立地得到了一些历史上尚未发现的L27（3^13)的不同构数组，希望该算法经过进一步发展后将能设计出许多新的正交数组。     

覆盖表生成的可配置贪心算法优化

覆盖表生成是组合测试研究的关键问题之一,其中,贪心算法因为速度快、生成的覆盖表规模小而得到人们的青睐.人们提出了很多基于不同策略的贪心算法,其中,多数算法可以归结到一个统一的算法框架,即形成一个可配置贪心算法,从该框架又可以衍生出很多新的算法.如何科学地配置优化受多个因素影响的算法框架、有效生成覆盖表是一个新的挑战.针对具有6个决策点的贪心算法框架,设计了3条不同的实验路线,系统地探索各个决策点以及它们之间相互作用对生成覆盖表规模的不同影响,寻找最佳配置,从而可以有效地生成规模更小的覆盖表,为覆盖表生成的贪心算法的设计和优化提供理论和实践基础.     

Wafer-scale integration and two-level pipelined implementations of systolic arrays

Two important issues in systolic array designs are addressed: How is fault tolerance provided in systolic arrays to enhance the yield of wafer-scale integration implementations? And, how are efficient systolic arrays with two levels of pipelining designed? (The first level refers to the pipelined organization of the array at the cellular level, and the second refers to the pipelined functional units inside the cells.) The fault-tolerant scheme proposed replaces defective cells with clocked delays. This has the distinct characteristic that data can flow through the array with faulty cells at the original clock speed. It is shown that both the defective cells under this fault-tolerant scheme and the second-level pipeline stages can simply be modeled as additional delays in the data paths of “generic” systolic designs. The mathematical notion of a cut is introduced to solve the problem of how to allow for these extra delays while preserving the correctness of the original systolic array designs. The results obtained by applying these techniques are encouraging. When applied to systolic arrays without feedback cycles, the arrays can tolerate large numbers of failures (with the addition of very little hardware) while maintaining the original throughput. Furthermore, all of the pipeline stages in the cells can be kept fully utilized through the addition of a small number of delay registers. However, adding delays to systolic arrays with cycles typically induces a significant decrease in throughput. In response to this, a new class of systolic algorithms has been derived in which the data cycle around a ring of processing cells. The systolic ring architecture has the property that its performance degrades gracefully as cells fail. Use of the cut theory and ring architectures for arrays with feedback gives effective fault-tolerant and two-level pipelining schemes for most systolic arrays. As a side effect of developing the ring architecture approach, several new systolic algorithms have been derived. These algorithms generally require only one-third to one-half of the number of cells used in previous designs to achieve the same throughput. The new systolic algorithms include ones for LU-decomposition, QR-decomposition, and the solution of triangular linear systems.