基于模拟试验法的离散公差稳健设计

 在分析计算机辅助公差设计技术的研究现状的基础上,提出了基于模拟试验法的离散公差稳健设计方法．在该方法中将加工成本与质量损失作为两个独立的目标函数,从而建立离散公差优化设计模型,采用试验设计法和CP方法相结合的技术实现公差的稳健设计,最后用实例证明该方法的可行性．     

A methodology for planning experiments in robust product and process design

Robust design is an important method for improving product manufacturability and life, and for increasing manufacturing process stability and yield. In 1980 Genichi Taguchi introduced his approach to using statistically planned experiments in robust product and process design to U.S. industry. Since then, the robust design problem and Taguchi's approach to solving it has received much attention from product designers, manufacturers, statisticians and quality professionals. Although most agree on the importance of the robust design problem, controversy over some of the specific methods used to solve the problem has made this an active research area. Although the answers are not all in yet, the importance of the problem has led to development of a four-step methodology for implementing robust design. The steps are (1) formulate the problem by stating objectives and then listing and classifying product or process variables, (2) plan an experiment to study these variables, (3) identify improved settings of controllable variables from the experiment's results and (4) confirm the improvement in a small follow-up experiment. This paper presents a methodology for the problem formulation and experiment planning steps. We give practical guidelines for making key decisions in these two steps, including choice of response characteristics, and specification of interactions and test levels for variables. We describe how orthogonal arrays and interaction graphs can be used to simplify the process of planning an experiment. We also compare the experiment planning strategies we are recommending to those of Taguchi and to more traditional approaches.     

Robust optimal design using a second-order tolerance model

In this paper we present a general, quantitative method for developing designs that are robust to variation in design variables and parameters. Variation is defined in terms of tolerances which bracket the expected deviation of uncertain quantities about nominal values. We specifically address the case where input variations are assumed to be random variables that are normally distributed. The method incorporates a second-order tolerance model as part of a nonlinear optimization process. The second-order tolerance model makes it possible to estimate the skewness of function distributions, which are modeled with a three-parameter gamma distribution. We apply the method to determine robust designs for 11 test cases that span a variety of problems; robustness is verified with Monte Carlo simulation. The method enables a designer to understand and account for the effects of tolerances, making it possible to build robustness into an engineering design.     

Optimization of product and process design for quality and cost

Robust product and process design is an important technique for achieving high quality at low cost. It involves making the product's function much less sensitive to various sources of noise such as manufacturing variation, environmental variation and deterioration. This is a problem in optimization involving minimization of the mean square loss resulting from the deviation of the product's function from its target. Here we show that the optimization can be carried out in two steps: first maximize a quantity called signal-to-noise ratio (S/N) and then bring the performance on target by special adjustment parameters. The two-step procedure works for a wide variety of product functions and makes the optimization process more efficient and practical compared to the direct minimization of the quadratic loss function.     

Optimization strategies in robust engineering design and computer-aided design

This paper reviews the fundamental ideas involved in robust engineering design (RED), and how they relate to computer-aided design. There are several areas of RED that may be successfully resolved by the use of statistical methods or ideas. This paper gives a general overview of several popular statistical strategies in RED and discusses how these strategies approach the statistical problems involved.     

Robust design via simulation experiments: a modified dual response surface approach

The existing procedures for robust design, devised for physical experiments, may be too limiting when the system can be simulated by a computer model. In this paper we introduce a modification of the dual response surface modelling, which incorporates the option of stochastically simulating some of the noise factors when their probabilistic behaviour is known. Our method generalizes both the crossed and the combined array approaches and finds a natural application to integrated parameter and tolerance design. The method appears suitable for designing complex measurement systems and in this paper is applied to the design of a high‐precision optical profilometer. Copyright © 2008 John Wiley & Sons, Ltd.     

微机电器件的稳健设计

微机电系统（MEMS）是一个新兴的跨学科研究领域,成本和可靠性是MEMS商品化的关键。与传统的机械加工和IC加工相比,MEMS加工的尺寸偏差比较大,而且很难控制,因此需要在设计过程中充分考虑加工的不确定性。稳健设计可以在不提高制造成本的前提下提高设计方案的稳健性。稳健优化设计方法主要包括 Taguchi方法和基于容差模型的方法,后者特别适合于处理带约束的优化设计问题。以微加速度计和微阀为例给出了稳健设计在MEMS设计中的应用,验证了稳健设计可以显著提高MEMS器件的信噪比。     

方差分析法在鲁棒公差设计中的应用

目前公差优化设计主要在于降低加工成本,而很少考虑公差对制造加工的敏感度问题。为此,在公差设计中采用了方差分析法,通过对加工模拟所产生的一系列数据的分析,找出对封闭环有显著影响的设计变量,并提高该设计变量的公差要求,从而减小封闭环对加工变动的敏感度,实现面向质量的鲁棒公差设计。     

Mixed resolution designs as alternatives to Taguchi inner/outer array designs for robust design problems

There has been considerable debate over the contributions made by Genichi Taguchi to robust process and product design. As a result of the numerous debates, there have been many alternative approaches presented that are better suited to the robust design problem. In this paper a combined array design is presented as an alternative to a standard Taguchi design. The mixed resolution design is illustrated in an example involving control and noise variables. Two new variance properties of experimental designs are also presented. Copyright © 2000 John Wiley & Sons, Ltd.     

Economic tolerance design for quality

This paper provides a few general mathematical models for determining product tolerances which minimize the combined manufacturing costs and quality loss. The models contain quality cost with a quadratic loss function and represent manufacturing costs with geometrical decay functions. The models are also formulated with multiple variables which represent the set of characteristics in a part. Applications of these models include minimizing the total cost with effective tolerance allocation in product design.     

Product Robust Design and Process Robust Design: Are They the Same? (No.)

Taguchi's ideas of robust parameter design motivated the development of the dual-response approach, where both the mean and the variance of the quality response are modeled in terms of the design parameters and noise factors. These are then used to identify optimal settings that achieve the dual objective of optimizing the signal (the mean) and minimizing variation. While much research has been published recently with regard to how to solve the dual-response problem (DRP), relatively little attention has been given to the unique characteristics of process robust design, like the existence of systematic variation or intercorrelations among the process “controllable” variables. These properties indeed put process robust design in a category of its own (separate from product robust design). In this paper, we first expound these unique properties and develop a general formulation of the DRP as it applies to process robust design. We then report on an implementation to an industrial process in a high-tech corporation.     

Robust design for multiple dynamic quality characteristics using data envelopment analysis

The Taguchi method is extensively adopted in various industries to continuously improve product design in response to customer requirements. The dynamic system of the Taguchi method is frequently implemented to design products with flexible applications. However, Taguchi's dynamic system can be employed only for individual quality characteristic, and the relationship between the quality characteristic and the signal factor is assumed to be linear. Because of these restrictions, Taguchi's dynamic system is ineffective for multiple quality characteristics or when the quality characteristic has a nonlinear relationship with the signal factor. This study describes a novel procedure for optimizing a dynamic system based on data envelopment analysis. The proposed procedure overcomes the limitations of Taguchi's dynamic system. Two cases are analyzed to demonstrate the effectiveness of the proposed procedure. The results show that the proposed procedure can enhance multiple dynamic quality characteristics. Copyright © 2008 John Wiley & Sons, Ltd.     

Nonlinear Elastic Wave Spectroscopy (NEWS) Techniques to Discern Material Damage,Part I: Nonlinear Wave Modulation Spectroscopy (NWMS)

Abstract

The level of nonlinearity in the elastic response of materials containing structural damage is far greater than in materials with no structural damage. This is the basis for nonlinear wave diagnostics of damage, methods which are remarkably sensitive to the detection and progression of damage in materials. Nonlinear wave modulation spectroscopy (NWMS) is one exemplary method in this class of dynamic nondestructive evaluation techniques. The method focuses on the application of harmonics and sum and difference frequency to discern damage in materials. It consists of exciting a sample with continuous waves of two separate frequencies simultaneously, and inspecting the harmonics of the two waves, and their sum and difference frequencies (sidebands). Undamaged materials are essentially linear in their response to the two waves, while the same material, when damaged, becomes highly nonlinear, manifested by harmonics and sideband generation. We illustrate the method by experiments on uncracked and cracked Plexiglas and sandstone samples, and by applying it to intact and damaged engine components.     

Japanese Manufacturing Techniques: Nine Hidden Lessons in Simplicity

Compound orthogonal arrays (COAs) and single arrays are alternatives to the inner–outer arrays advocated by Taguchi for robust parameter design experiments. A criterion based on the word type pattern and strength of COAs is proposed to select optimal COAs. Single arrays are classified into prodigal single arrays (PSAs) and economical single arrays (ESAs) according to their relative estimation capacities, and various optimality criteria, again based on the word type pattern, are proposed for selecting optimal single arrays. Useful optimal COAs, PSAs, and ESAs are constructed and tabulated as convenient references for experimenters in practice.     

Development of a sequential optimization procedure for robust design and tolerance design within a bi-objective paradigm

Many practitioners and researchers have implemented robust design and tolerance design as quality improvement and process optimization tools for more than two decades. Robust design is an enhanced process/product design methodology for determining the best settings of control factors while minimizing process bias and variability. Tolerance design is aimed at determining the best tolerance limits for minimizing the total cost incurred by both the customer and manufacturer by balancing quality loss due to variations in product performance and the cost of controlling these variations. Although robust design and tolerance design have received much attention from researchers and practitioners, there is ample room for improvement. First, most researchers consider robust design and tolerance design as separate research fields. Second, most research work is based on a single quality characteristic. The primary goal of this paper is to integrate a sequential robust design–tolerance design optimization procedure within a bi-objective paradigm, which, the authors believe, is the first attempt in the robust design and tolerance design literature. Models are proposed and numerical examples along with sensitivity analysis are performed for verification purposes.     

Continuous Taguchi—a model-based approach to Taguchi's ‘quality by design’ with arbitrary distributions

Statistical experimental design has been used in ‘off-line’ quality control to determine the optimal settings for a system even when the mathematical model is known. Taguchi demonstrated how signal-to-noise ratios could be used to improve the performance of a system through variance minimization. However, these statistical methods often do not use the full distribution information that may be available. Proposed in this paper is an extension and complement to Taguchi's use of experimental design and signal-to-noise ratios for known system models. The use of a probability transformation method with the mathematical system model will allow designers to perform parameter and tolerance design simultaneously using a method of ‘fast integration’. The result is a new method in the field of ‘quality by design’, which we call continuous Taguchi, that can handle both linear and non-linear systems, with components of any distribution type, with or without correlation of the variables. In addition, an interpretation of Taguchi's classification of factors is given in the context of our full distribution method. © 1998 John Wiley & Sons, Ltd.     

Robust design of an interior hard trim to improve occupant safety in a vehicle crash

Head injury ranks among the top contributors in automobile accidents. Consequently, although styling is treated important, safety of occupants in a crash receives preemptive priority in the design of automotive interior components. Additionally, the Federal Motor Vehicle Safety Standard (FMVSS) 201 has laid down certain requirements to be fulfilled by automobile manufacturers for producing a safe vehicle. One of the requirements stipulate dummy equivalent of the Head Injury Criteria, i.e. HIC(d) value for the interior components of a vehicle to be below 1000 under certain stated conditions. In this paper, we provide a robust design approach to achieve the requirements for one such interior component, viz. an interior hard trim that covers the pillar closest to the driver's head on the left-hand side of the vehicle.     

Robust design using a hybrid-cellular-evolutionary and interval-arithmetic approach: a reliability application

Sensitivity analysis is a technique by which one can determine, with good approximation, whether a system will work within the specification limits when the input vary between their limits.Although this type of analysis, from input to output, can provide useful information to the decision-maker, we present an approach based on the use of Cellular Evolutionary Strategies and Interval Arithmetic in which the inverse problem can be solved. That is, we move from output to input: starting with output range specifications, we infer the maximum uncertainty or variability that can be exhibited by the input parameters. The approach used is an indirect method based on optimisation instead of a direct method based on mapping from the output into the input space. The proposed approach is illustrated by computational examples applied to a reliability complex system. Results are compared with those obtained using a general non-linear optimisation package.     

Robust design of a polysilicon deposition process using split-plot analysis

The technique used for the analysis of experimental data must be appropriate for the design and treatment structures of the experiment; failure to take this into account can produce misleading results. This paper illustrates how split-plot designs can be used for the analysis of robust design experiments. In particular, the polysilicon deposition process data presented by Phadke¹ is analysed, and comparisons are made between the split-plot analysis of the raw data and the analysis conducted using signal-to-noise ratios. In addition, we demonstrate how the split-plot analysis provides information about interactions between control and noise factors, and how interaction plots can be used to assess the performance of the control factors across the levels of the noise factors. This information is particularly important to select the settings of the control factors that minimize the variation in the response induced by the noise factors.     

基于田口方法的柔性铰链柔度稳健优化设计

柔顺机构柔度稳健性是柔性机构在微机电系统与精密工程等领域广泛应用的前提和基础,但在实际工程中传统设计方法未充分考虑其稳健性.引入田口稳健优化设计方法,选取柔性铰链各结构参数为可控因素,工作载荷为噪声因子,通过正交试验数据分析得出各个可控因素的信噪比和贡献率,进而选出最佳的参数水平组合,并对柔度综合稳健性能的最优方案进行了验证.算例表明,采用田口稳健优化设计的柔性铰链柔度稳健性比传统方法信噪比水平提高了4.68dB,降低了其质量损失,实现了柔性铰链柔度稳定性优化.田口稳健优化设计方法具有普适性,在实际工程应用中具有较高参考价值.