A methodology of integrating affective design with defining engineering specifications for product design

Affective design and the determination of engineering specifications are commonly conducted separately in early product design stage. Generally, designers and engineers are required to determine the settings of design attributes (for affective design) and engineering requirements (for engineering design), respectively, for new products. Some design attributes and some engineering requirements could be common. However, the settings of the design attributes and engineering requirements could be different because of the separation of the two processes. In previous studies, a methodology that considers the determination of the settings of the design attributes and engineering requirements simultaneously was not found. To bridge this gap, a methodology for considering affective design and the determination of engineering specifications of a new product simultaneously is proposed. The proposed methodology mainly involves generation of customer satisfaction models, formulation of a multi-objective optimisation model and its solving using a chaos-based NSGA-II. To illustrate and validate the proposed methodology, a case study of mobile phone design was conducted. A validation test was conducted and the test results showed that the customer satisfaction values obtained based on the proposed methodology were higher than those obtained based on the combined standalone quality function deployment and standalone affective design approach.     

面向人机交互的轨道维护工程机械内室设计研究

目的 轨道维护工程机械是典型的复杂产品,根据用途需要自行研发制造,致使内室人机交互成为设计研究的难点。方法 根据轨道维护工程机械运动行驶、静态作业和移动作业三种形式,以及作业人员组和作业机械组两部分结合的行业现状,从界面、通道和用户三个方面,分析轨道维护工程机械的多类型界面组合、多通道信息传递和多用户行为协同的人机交互特点。依据开发过程的系统特性,界定轨道维护工程机械内室人机交互的概念,构建设计原则,并提出内室人机交互设计模型。结论 轨道维护工程机械内室设计以作业工况为核心,具有轨道交通和工程机械双重属性。内室人机交互既要符合轨道行业标准,也要顺应作业规范要求,结合工业设计与人机工程满足人机交互的作业工况。最后对磁浮轨道维护车内室人机交互进行设计应用,为理论与实践研究提供参考。     

用户感性认知与产品感性设计方法及应用

目的梳理用户感性认知测量及其设计应用,提出人工智能驱动的产品感性设计方法,并以验光仪设计验证其有效性。方法分析国内外文献,归纳总结用户感性认知测量及应用方法,通过验光仪设计验证所提出的产品感性设计方法。结果人工智能驱动的产品感性设计方法能提升设计效率,更好地满足用户感性需求。结论用户感性认知测量能转化为设计规范,并能为产品设计提供有效指导。随着计算机科学的发展,针对传统用户感性认知测量中样本采集量较少、测量不够全面等问题,提出了人工智能驱动的产品感性设计方法,并以验光仪的设计验证了其有效性。研究结果表明,通过文本挖掘提取用户感性认知能引导设计师更加全面地了解用户感性需求,从而使设计出的产品更贴近用户的预期满意度。人工智能与人类智慧相结合的感性设计方法是一种能提高用户对产品的心理接受度,从而提升产品竞争力的设计方法。     

Parameter tolerance design for electrical circuits

Realistic circuit design requires that unavoidable tolerances on component parameters be taken into account, particularly in situations where a circuit is to be mass-produced. Since specifications are normally imposed on circuit performance, parameter tolerances can have the undesirable effect of reducing manufacturing yield (i.e. the percentage of circuits which meet specifications) to values below unity, thereby effectively increasing circuit cost. Approaches have been developed to electrical circuit design which incorporate aspects of parameter tolerance variations at the various stages of design, thus enabling tolerance effects to be assessed and minimized. There are two principal approaches: statistical and deterministic. The first uses probabilistic techniques to predict variations in circuit performance, whereas the second uses deterministic (i.e. non-stochastic) methods. Within each group, three types of problems are important: first, the maximization of yield, secondly, the minimization of circuit unit cost and, thirdly, the minimization of performance variability. This paper discusses some important advances in the statistical approach to tolerance design. Monte Carlo analysis is almost invariably an important component of the procedure: random fluctuations in parameter values are simulated according to some probability density function and inserted into a computer circuit simulation program which computes corresponding circuit performance variations. The procedure — also referred to as tolerance analysis — not only allows the designer to predict expected performance fluctuations but also presents him with information regarding the relative location of acceptable and non-acceptable circuits in component parameter space. The Monte Carlo method can handle without difficult any number of component parameters and performance functions; moreover, statistical dependence among parameters is readily handled. The algorithm presented here is experimentally validated through successful design of practical circuits and is applicable to both discrete and integrated circuits. Strategies which ensure computational efficiency of the methods are discussed and a cost/benefit analysis carried out for a typical circuit.     

Robust optimization based on the Propagation of Variance method for analytic design models

The robust optimisation is performed in the preliminary design phase dealing with analytic models. The analytic models come either from the finite element models or from the physical laws approximation. The variability on the design parameters is defined using random variables identified by their first two Moments, the Mean and the Standard deviation. A robust design approach is proposed that determines whether a robust design solution exists or not to the given design problem. This approach combines a reformulation of the analytic model with the new design specifications. It integrates the parameter uncertainties (Mean and Standard deviation) and a deterministic optimisation algorithm (SQP algorithm). The Means and the Standard deviation are computed using the Propagation of Variance method. The engineering application of an electrical actuator design is introduced and used to show the implementation and the effectiveness of the proposed robust approach.     

Optimized sampling design and rationale for verification and validation

An optimized sampling design that meets customer, design, or process requirements, while balancing technology limitations, is still a common challenge to engineering communities. This is especially true in the medical device industry. Acceptance sampling plans for manufacturing are widely available, but the appropriate sampling plans for verification and validation (V&V) are less well known. This paper applies established statistical theory to derive sampling plans appropriate for estimating product reliability during V&V, where reliability must exceed an established threshold with an appropriate margin of statistical confidence. The paper provides insight on how to estimate parameters of interest and interpret acceptance criteria. Operating characteristic curves are used to examine if a design or process is capable of producing future product that meets design specifications and/or customer requirements in terms of confidence and reliability. The methodology is applied to both attribute and variable sampling plans, including examples showing how to achieve a high probability of passing the acceptance criteria. Formulas, sample size tables, and operating characteristic curves are provided for engineering practitioners to use. The paper aims at providing a practical quantitative approach and a valid statistical rationale to assess overall product quality during V&V.     

A Dominance-based Design Metric in Multiattribute Robust Design

This paper outlines the development of an effective and consistent ‘designing-in-quality’ strategy that can be used to deal with concepts of uncertainty, quality and robustness in engineering design. Specifically, this paper presents a decision analysis-based robust design metric that seamlessly integrates objective evaluations on the goodness of a design alternative with the designer’s intent and preferences. This is achieved through the development of a set of performance-reflecting dominance indices for the attributes and their utilization in a preference-influenced multiattribute utility formulation. Such a knowledge feedback-based decision model development will be particularly useful when dealing with complex iteration-based engineering design process where little information on the expected outcomes may be known a priori, or where product performance is computationally expensive to evaluate. Application of this robust design metric in a multi-stage experimentation and modeling design process is presented. The characteristics of the proposed design metric and the effectiveness of the overall design procedure in dealing with constrained engineering design problems are examined with the aid of demonstrative case studies and the results are discussed.     

Hierarchical and interactive decision refinement methodology for engineering design

This paper presents the Hierarchical and Interactive Decision Refinement (HIDER) methodology for engineering design. This methodology hierarchically refines (or reduces) a large initial design space through a series of multiple-objective optimizations, until a fully specified design is obtained. This contrasts with the traditional approach to design optimization which involves picking a fully specified design from the space of possible designs and then iteratively modifying its specifications to maximize the performance. The HIDER methodology uses an adaptive modeling approach that combines machine learning and statistical techniques for developing fast empirical models with different levels of detail and evaluation speeds. These models are used for multiple-objective optimization at different stages of the design. The use of layered models enables HIDER methodology to be used at different stages of parametric design, including early stages when design specifications are not complete. This methodology also supports multiple perspectives in concurrent design because it provides means for transforming models from these different perspectives into a uniform representation, as well as facilitating decision-making with respect to multiple competing objectives. This paper presents the HIDER methodology with an example in the parametric design of a diesel engine.     

大尺寸立方体开槽超声塑料焊接工具头的优化设计

谐振频率、频率间隔性、振幅均匀度是大尺寸超声塑料焊接工具头设计中的几个主要指标。基于工程实际,以工具头纵向长度、槽宽度及槽长度为设计变量,纵向谐振频率和频率间隔值为状态变量,振幅均匀度为目标函数,利用有限元软件ANSYS的参数化分析技术,对大尺寸立方体超声塑焊开槽工具头进行了优化设计。结果表明,该优化方法能很好地解决大尺寸超声塑焊工具头的设计问题,既提高了设计效率,也降低了设计成本。     

Analysis-of-Marginal-Tail-Means (ATM): A Robust Method for Discrete Black-Box Optimization

Abstract

We present a new method, called analysis-of-marginal-tail-means (ATM), for effective robust optimization of discrete black-box problems. ATM has important applications in many real-world engineering problems (e.g., manufacturing optimization, product design, and molecular engineering), where the objective to optimize is black-box and expensive, and the design space is inherently discrete. One weakness of existing methods is that they are not robust: these methods perform well under certain assumptions, but yield poor results when such assumptions (which are difficult to verify in black-box problems) are violated. ATM addresses this by combining both rank- and model-based optimization, via the use of marginal tail means. The trade-off between rank- and model-based optimization is tuned by first identifying important main effects and interactions from data, then finding a good compromise which best exploits additive structure. ATM provides improved robust optimization over existing methods, particularly in problems with (i) a large number of factors, (ii) unordered factors, or (iii) experimental noise. We demonstrate the effectiveness of ATM in simulations and in two real-world engineering problems: the first on robust parameter design of a circular piston, and the second on product family design of a thermistor network.     

西南山区机场高填方边坡反压护道优化设计

针对西南山区机场高填方地基存在有限深度相对软弱土层的工程地质情况,提出单级反压护道的优化设计方法及优化设计中所涉及到的各类典型滑移面稳定安全系数的简化计算方法,并对其进行了证明及验证,分析了所提方法计算结果与强度折减有限元法的差别大小及方法的适用性。验证结果表明:所提方法计算的安全系数与有限元计算结果的相对误差均不超过12%;计算的反压护道断面尺寸相对误差不超过20%;应用于有硬壳层的工程地质条件或有反压护道的典型滑移面时,误差更小。     

A co-operation framework for product–process integration in engineering design

Many different studies have stressed the importance of co-operation in engineering design. This paper is based on an empirical study carried out over 18 months and based on fieldwork where the researcher worked in a design team as a mechanical engineer. The question of product–process integration is particularly critical in mechanical engineering and requires the development of specific co-operative procedures. Our results stress the importance of artefacts as intermediary objects in the design process and more specifically in the development of co-operative processes. We developed a framework centred on three conceptual levels:

• At product level, where we developed specific artefacts within a CAD environment, referred to herein as co-operating features,

• At organisation level, where we stress the importance of developing organisational learning and a new interface role,

• At actor level, where we stress the importance of developing reflective practices.

This conceptual framework aims to provide a foundation to develop instrumental settings for design co-operation.     

Function-based cost estimating

Communication between cost estimators with commercial (CE-C) and engineering (CE-E) backgrounds is essential for good internal practice. This paper presents a function-based cost estimating (FUCE) framework to link the commercial and engineering communities through a structured approach at the conceptual design stage. The objective of FUCE is to translate the un-quantified terminology and the requests associated with the product specifications used by CE-C into a medium that CE-E can process using their resources, and creates estimates that are based on a standardized approach. The FUCE approach starts with functional decomposition, and then identifies product parameters that are related to a top level function and finally associate product costs to the function using past knowledge and data. FUCE is developed using a detailed case study on an automotive exhaust system. The methodology is then validated on two case studies from the automotive and aerospace industries.     

Expert systems and the emergence of teledesign

This paper considers the extent to which the amateur use of expert systems for home design challenges traditional views of the design process. The issues are examined in the context of competing definitions of design. The emergence of a design process characterised as ‘teledesign’ is then considered, wherein retailers provide a CAD/CAM service to consumers, allowing the latter to use expert systems to modify template designs and get products fabricated to their own specifications. Such a system may be seen to empower consumers as designers, rather than just selectors of products, and would differ considerably from established paradigms of design, manufacture and consumption, such as that given by Baudrillard.     

面向自理老人的适老家具设计研究

目的老龄化社会是新的社会形态,这种形态下多种形式的养老模式开始发展起来。就适老家具设计这一领域,我国在理论研究和设计实践方面也都处在起步阶段,除了需要学习国外经验之外,还要结合我国老年人的实际情况,设计以老年人为本的人性化家具。方法通过对老年家具的市场调研和对自理老人的问卷调查及用户访谈,总结自理型老人适老家具智能化设计的原则。通过对国内外的适老家具设计理论研究,得出适老家具行业急需较为全面且严谨的理论、标准和规范来指导设计。现阶段适老家具智能化设计可以从智能识别、智能健康提示和智能调节等方面深入研究实践。结论探索出符合我国国情的自理型老人的适老家具智能化设计的原则和理念,为国内家具企业进行适老家具产品的设计开发提供一定的设计理论和设计标准,对适老家具行业的发展有一定的促进作用。     

A Qualitative Study of a Course Trilogy in Biosystems Engineering Design

Engineering design encompasses professional competencies that complement a solid understanding of engineering science fundamentals, theories, and methods. Engineering schools are increasing their efforts to integrate design into the curriculum, and this paper critically analyses one initiative at a research‐intensive Canadian university, where a three‐course sequence (Design Trilogy) forms the design education backbone in the undergraduate Biosystems Engineering program. Data collection consisted of focus groups with students and one‐on‐one interviews with instructors and industry cooperators. The findings yielded authentic understandings of teaching and learning engineering design, many areas of common perceptions between participant groups, congruence with design concepts in the literature, and areas where students' perceptions and experiences did not correspond to instructors' intentions. Teaching implications include the importance of instructors' transparency and integration in teaching and the need to explicitly prepare students for a different kind of learning experience in the Design Trilogy.     

Power of experimental design studies for the validation of pharmaceutical processes: case study of a multilayer tablet manufacturing process

Experimental design studies (EDS) are already widely used in the pharmaceutical industry for drug formulation or process optimization. Rare are the situations in which this methodology is applied for validation purposes. The power of this statistical tool, key element of a global validation strategy, is demonstrated for a multilayer tablet manufacturing process. Applied to the Geomatrix® system generally composed of one compression and three granulation processes, time and strictness gains are non-negligible. Experimental design studies are not used in this work for modeling. Introduced at each important step of the process development, they allow for the evaluation of process ruggedness at pilot scale and specifications for full production. A demonstration of the complete control of key process parameters is given, identified throughout preliminary studies.     

Impact of response delay and training on user performance with text-based and graphical user interfaces for engineering design

With recent computer advances, visualization techniques are becoming more prevalently used as decision support tools for parametric design and engineering optimization. Despite the apparent advantages of visualization techniques, we have found little evidence in the engineering design literature that assesses the impact of fast graphical design interfaces on the efficiency and effectiveness of engineering design decisions. In this paper, we present experimental results from an I-beam design problem where the importance of rapid feedback is investigated by incorporating time delays in the software response to “mimic” computationally expensive design analyses. Design efficiency is measured by recording the completion time for solving the design problem, and design effectiveness is measured by calculating the error between a submitted design and the known optimum. The impact of graphical feedback is examined by comparing user performance on three different design interfaces to determine if their functionality and graphical capabilities mediate the impact of response delays in the software or the amount of training needed. Experimental results indicate that, on average, error increased by 280% and completion time increased by 33% when a delay of 1.5 s was present, and the perceived workload significantly increased as well. Meanwhile, user performance improved and perceived workload decreased as the “richness” of the design interface increased. The combination of a rich interface with a fast response time, therefore, will lead to the “best” interface as one might surmise, but our work provides the first empirical evidence of the effect of response delay on user performance within a realistic engineering design setting. Implications for interface development for engineering design are explored within the context of our findings, as are suggestions for future work.     

A MODIFIED PATTERN SEARCH METHOD WITH RELAXED LEXICOGRAPHIC MINIMIZATION FOR ENGINEERING DESIGN

In engineering design, many design problems have multiple constraints and objectives, which may be non-differentiable. For this problem type, only zero-order solution methods are applicable. In this paper, a relaxed lexicographic pattern search method is presented for solving this design problem type, where the objectives are preferenced in either an Archimedean or preemptive formulation. The Hooke-Jeeves (HJ) pattern search method is the basis of this method, which is implemented as the MORPS (Multi-Objective Randomized Pattern Search) algorithm. The HJ pattern search method is used because it requires only function values and has an intuitive graphical interpretation through which to gain insight into the nature of complex design spaces. A relatively new class of simultaneous product/process design problem utilizing virtual prototypes to support design for disassembly is introduced to motivate the need for the MORPS algorithm. An example, based on the design of an automotive center console for disassembly, illustrates the application of the MORPS algorithm.     

The development of a robust design methodology for time‐oriented dynamic quality characteristics with a target profile

Innovative engineering techniques are often sought within the manufacturing environment to improve product quality and promote more cost‐effective strategies. Robust design methods are frequently used to serve this purpose, with the objective of minimizing the variability inherent within a particular process or system. A review of the literature suggests that most robust design research involves the study of static quality characteristics, given a pre‐defined specification interval or region and target value. In addition to proposing a methodology for working with dynamic quality characteristics where the specifications and target value may change over time, this paper offers two other distinct contributions. First, those researchers who have examined dynamic systems traditionally consider the effects of a signal factor on a response variable on the identification of optimal factor settings. In contrast, this paper will consider the effects of a quality characteristic changing over time, thus removing the need to confine the problem to signal–response systems. Furthermore, most researchers consider the optimization of the process mean according to the costs of non‐conforming to an established specification interval or region. This paper, however, utilizes a methodology involving the simultaneous optimization of the process mean and variance while expanding the problem to consider a loss in quality attributed to deviation from a target value over time. Copyright © 2010 John Wiley & Sons, Ltd.