Abstract: The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of today’s engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper, we review several of these techniques, including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning and kriging. We survey their existing application in engineering design, and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations, and how common pitfalls can be avoided.

Abstract: In redesign and design for customization, products are changed. During this process a change to one part of the product will, in most cases, result in changes to other parts. The prediction of such change provides a significant challenge in the management of redesign and customization of complex products where many change propagation paths may be possible. This paper reports on an analysis of change behavior based on a case study in Westland Helicopters of rotorcraft design; the development of mathematical models to predict the risk of change propagation in terms of likelihood and impact of change; and the development of a prototype computer support tool to calculate such information for a specific product. With knowledge of likely change propagation paths and their impact on the delivery of the product, design effort can be directed towards avoiding change to "expensive" sub-systems and, where possible, allowing change where it is easier to implement while still achieving the overall changes required.

Abstract: Metamodeling techniques have been widely used in engineering design to improve efficiency in the simulation and optimization of design systems that involve computationally expensive simulation programs. Many existing applications are restricted to deterministic optimization. Very few studies have been conducted on studying the accuracy of using metamodels for optimization under uncertainty. In this paper, using a two-bar structure system design as an example, various metamodeling techniques are tested for different formulations of optimization under uncertainty. Observations are made on the applicability and accuracy of these techniques, the impact of sample size, and the optimization performance when different formulations are used to incorporate uncertainty. Some important issues for applying metamodels to optimization under uncertainty are discussed.

Abstract: Real world engineering design problems are usually characterized by the presence of many conflicting objectives. Therefore, it is natural to look at the engineering design problem as a multiobjective optimization problem. This report summarizes a survey of techniques to conduct multiobjective optimization in an engineering design context. The report starts with discussing some of the difficulties of expressing the value of a deign and how to characterize different design variables. Thereafter we look more closely on the design problem in order to reformulate the design problem as a multiobjective optimization problem. As engineering design problems often consist of a mixture of numerical simulations, analytical calculations and catalog selections, there is no easy way of calculating derivatives of the objectives function. Therefore, non-gradient optimization methods are better suited for these types of problems. Different types of non-gradient method are discussed in the report and different ways of developing hybrid methods are presented as well. As most optimization problems are multiobjective to there nature, there are many methods available to tackle these kind of problems. Generally, a multiobjective optimization problem can be handled in four different ways depending on when the decision-maker articulates his or her preference on the different objectives; never, before, during or after the actual optimization procedure. The most common way is to aggregate the different objectives to one figure of merit by using a weighted sum and the conduct the actual optimization. There is however an abundance of other ways in which multiobjective optimization can be conducted, some of them are presented in this report. A survey of multiobjective optimization methods in engineering design

Abstract: Target cascading in product development is a systematic effort to propagate the desired top-level system design targets to appropriate specifications for subsystems and components in a consistent and efficient manner. If analysis models are available to represent the consequences of the relevant design decisions, analytical target cascading can he formalized as a hierarchical multilevel optimization problem. The article demonstrates this complex modeling and solution process in the chassis design of a sport-utility vehicle. Ride quality and handling targets are cascaded down to systems and subsystems utilizing suspension, tire, and spring analysis models. Potential incompatibilities among targets and constraints Throughout the entire system can he uncovered and the trade-offs involved in achieving system targets under different design scenarios can he quantified.

Abstract: Introduction / Key Drivers in the Design Process Aerodynamic Considerations in Tactical Missile Design Propulsion Considerations in Tactical Missile Design Weight Considerations in Tactical Missile Design Flight Performance Considerations in Tactical Missile Design Measures of Merit and Launch Platform Integration Sizing Examples Development Process Summary and Lessons Learned References List of Acronyms/Symbols Conversion Factors Index

Abstract: As the integrated circuits (ICs) are scaled into nanometer dimensions and operate in gigahertz frequencies, interconnects have become critical in determining system performance and reliability. This paper presents the ongoing research effort at UCLA in developing an interconnect-centric design flow, including interconnect planning, interconnect synthesis, and interconnect layout, which allows interconnect design and optimization to be properly considered at every level of the design process. Efficient interconnecter performance estimation models and tools at various levels are also developed to support such an interconnect-centric design flow.

Abstract: The well-accepted basis for developing a mechatronic system is a synergetic concurrent design process that integrates different engineering disciplines. In this paper, a general model is derived to mathematically describe the concurrent design of a mechatronic system. Based on this model, a concurrent engineering approach, called design for control (DFC), is formally presented for mechatronic systems design. Compared to other mechatronic design methodologies, DFC emphasizes obtaining a simple dynamic model of the mechanical structure by a judicious structure design and a careful selection of mechanical parameters. Once the simple dynamic model is available, in spite of the complexity of the mechanical structure, the controller design can be facilitated and better control performance can be achieved. Four design scenarios in application of DFC are addressed. A case study is implemented to demonstrate the effectiveness of DFC through the design and control of a programmable four-bar linkage.

Abstract: This article presents an overview of the state-of-the art in modeling and simulation, and studies to which extent current simulation technologies can effectively support the design process. For simulation-based design, modeling languages and simulation environments must take into account the special characteristics of the design process. For instance, languages should allow models to be easily updated and extended to accommodate the various analyses performed throughout the design process. Furthermore, the simulation software should be well integrated with the design tools so that designers and analysts with expertise in different domains can effectively collaborate on the design of complex artifacts. This review focuses in particular on modeling for design of multi-disciplinary engineering systems that combine continuous time and discrete time phenomena.

Abstract: Data Mining for Design and Manufacturing: Methods and Applications is the first book that brings together research and applications of data mining within design and manufacturing. Book objectives are 1) to clarify the integration of data mining in engineering design and manufacturing, 2) to present a wide range of domains to which data mining can be applied, 3) to demonstrate the essential need for symbiotic collaboration of expertise in design and manufacturing, data mining and information technology, 4) to illustrate how to overcome central problems in design and manufacturing environments. The book also presents formal tools required to extract valuable information from design and manufacturing data and facilitates interdisciplinary problem solving for enhanced decision making.

Abstract: Decision based design shows great promise in improving the design process, but is not a panacea. The design problem of interest here is tradeoffs between conflicting objectives, particularly under uncertainty. The focus is on multiattribute utility theory. This paper describes several real limitations to utility analysis in the context of engineering design, and attempts to clear up several common misconceptions about it. The real limitations are in the initial configuration and analytic design phases, and in overcoming difficulties in group decision making. The major misconceptions relate to independence conditions, the functional form and assessment biases.

Abstract: We present MILAN, a model based extensible framework that facilitates rapid, multigranular performance evaluation of a large class of embedded systems, by seamlessly integrating different widely used simulators in to a unified environment. MILAN provides a formal paradigm for specification of structural and behavioral aspects of embedded systems, an integrated model-based approach, and a unified software environment for system design and simulation. This paper provides an overview of MILAN, discusses the Model Integrated Computing philosophy, and illustrates the high-level modeling concepts being developed in the MILAN project for embedded systems design and evaluation.

Abstract: The dimensionality and complexity of typical multidisciplinary systems hinders the use of formal optimization techniques in application to this class of problems. The use of approximations to represent the system design metrics and constraints has become vital for achieving good performance in many multidisciplinary design optimization (MDO) algorithms. This paper reports recent research efforts on the use of variable fidelity response surface approximations (RSA) to drive the convergence of MDO problems using a trust region model management algorithm. The present study focuses on a comparative study of different response sampling strategies based on design of experiment (DOE) approaches within the disciplines to generate the zero order data to build the RSAs. Two MDO test problems that have complex coupling between disciplines are used to benchmark the performance of each sampling strategy. The results show that these types of variable fidelity RSAs can be effectively managed by the trust region model management strategy to drive convergence of MDO problems. It is observed that the efficiency of the optimization algorithm depends on the sampling strategy used. A comparison of the DOE approaches with those obtained using a optimization based sampling strategy (i.e. concurrent subspace optimization --- CSSO) shows the DOE methodologies to be competitive with the CSSO based sampling methodology in some cases. However, the CSSO based sampling strategy was found to be, in general, more efficient in driving the optimization.

Abstract: This paper discusses the role that computational fluid dynamics plays in the design of aircraft. An overview of the design process is provided, covering some of the typical decisions that a design team addresses within a multi-disciplinary environment. On a very regular basis trade-offs between disciplines have to be made where a set of conflicting requirements exist. Within an aircraft development project, we focus on the aerodynamic design problem and review how this process has been advanced, first with the improving capabilities of traditional computational fluid dynamics analyses, and then with aerodynamic optimizations based on these increasingly accurate methods. The optimization method of the present work is based on the use of the adjoint of the flow equations to compute the gradient of the cost function. Then, we use this gradient to navigate the design space in an efficient manner to find a local minimum. The computational costs of the present method are compared with that of other approaches to aerodynamic optimization. A brief discussion regarding the formulation of a continuous adjoint, as opposed to a discrete one, is also included. Two case studies are provided which highlight the benefits of utilizing automatic aerodynamic shape optimization. The first case chronicles the application of such software during a complete aircraft design effort, while the second case shows to what extent the aerodynamic design cycle can be compressed. In both efforts, the optimizations were performed in design spaces with dimensions greater than 4, 000. Furthermore, they were conducted on very affordable computer equipment and turned around within a few hours of wall-clock time. ∗AIAA Fellow, T. V. Jones Prof. of Engineering †AIAA Associate Fellow, Boeing Technical Fellow Copyright c ©2001 by Jameson & Vassberg. Published by the AIAA with permission. The paper finishes with some visions for the future. Extrapolating the trends of computer weight and cost, it is interesting to speculate on how the aircraft design environment may evolve in the years to come.

Abstract: This paper presents an integrated approach that supports the topology optimization and CAD-based shape optimization. The main contribution of the paper is using the geometric reconstruction technique that is mathematically sound and error bounded for creating solid models of the topologically optimized structures with smooth geometric boundary. This geometric reconstruction method extends the integration to 3-D applications. In addition, commercial Computer-Aided Design (CAD), finite element analysis (FEA), optimization, and application software tools are incorporated to support the integrated optimization process. The integration is carried out by first converting the geometry of the topologically optimized structure into smooth and parametric B-spline curves and surfaces. The B-spline curves and surfaces are then imported into a parametric CAD environment to build solid models of the structure. The control point movements of the B-spline curves or surfaces are defined as design variables for shape optimization, in which CAD-based design velocity field computations, design sensitivity analysis (DSA), and nonlinear programming are performed. Both 2-D plane stress and 3-D solid examples are presented to demonstrate the proposed approach.

Abstract: A Corrigendum has been published for this article in Systems Engineering 4: 190–212, 2001. Practicing engineers often find the tools and techniques used for investigating alternative system designs to be cumbersome or complicated. This article will show that these systems engineering tools and techniques are in fact quite simple and can provide critical insight into how stakeholder requirements drive the engineering design process. This helps ensure that customer requirements are satisfied throughout the entire system lifecycle and aids in reducing expensive design iterations due to poorly understood or poorly documented requirements. These goals are achieved by deriving figures of merit and combining them using standard scoring functions to steer efforts towards fulfilling the customer's objectives early in the design process. Few papers in the literature capture the basic elements of tradeoff analyses in a way that entices the engineer to utilize the techniques. We have attempted to ameliorate this problem. Most of the practices presented in the literature are written from a decision analysis perspective. The success of such techniques is dependent on the expertise of the analyst in that several of the methods require considerable analyst experience for them to be employed effectively. This paper presents standardized methodologies for carrying out tradeoff analyses, which are applicable to a wide array of problems and also demonstrates that these techniques are relatively simple to use. © 2001 John Wiley & Sons, Inc. Syst Eng 4: 190–212, 2001

Abstract: This thesis focuses on how to improve design and development of complex engineering systems by employing simulation and optimization techniques. Within the thesis, methods are developed and applied ...

Abstract: This paper argues that it is possible to gain good design information from low-cost user trials of low-fidelity prototypes early in the design process, and that simple prototyping is a valuable tool in the user-centred design of new technology especially “smart” consumer products. The value of that design information depends on the stage of the design process at which user testing is carried out and the associated level of realism or fidelity of the prototype. The first stages involve testing simple prototypes which examine the cognitive, or information processing, needs of the user, followed by higher-fidelity prototypes which examine the physical (visual, auditory and tactile) needs of the user.The results of four studies are discussed to illustrate: the extent and nature of the design information gathered, the relative merits of varying the fidelity of the prototypes, and the benefits and costs associated with using different levels of fidelity of prototypes in a user-centred approach to design. Finally, and based on that discussion, an appropriate and practical design strategy is suggested.

Abstract: Dynamically reconfigurable architectures are emerging as a viable design alternative to implement a wide range of computationally intensive applications. At the same time, an urgent necessity has arisen for support tool development to automate the design process and achieve optimal exploitation of the architectural features of the system. Task scheduling and context (configuration) management become very critical issues in achieving the high performance that digital signal processing (DSP) and multimedia applications demand. This article proposes a strategy to automate the design process which considers all possible optimizations that can be carried out at compilation time, regarding context and data transfers. This strategy is general in nature and could be applied to different reconfigurable systems. We also discuss the key aspects of the scheduling problem in a reconfigurable architecture such as MorphoSys. In particular, we focus on a task scheduling methodology for DSP and multimedia applications, as well as the context management and scheduling optimizations.

Abstract: This paper presents an eco-innovative design method based on the TRIZ method. The proposed method can solve eco-innovation design problems by using TRIZ inventive principles without requiring contradiction analysis. This new method can be used as a supporting tool for designers to invent novel, useful, and environmentally friendly products or processes. Several eco-innovative design examples are demonstrated to illustrate the capabilities of the proposed method.

Abstract: Power-efficient design requires reducing power dissipation in all parts of the design and during all stages of the design process subject to constraints on the system performance and quality of service (QoS). Power-aware high-level language compilers, dynamic power management policies, memory management schemes, bus encoding techniques, and hardware design tools are needed to meet these often-conflicting design requirements. This paper reviews techniques and tools for power-efficient embedded system design, considering the hardware platform, the application software, and the system software. Design examples from an Intel StrongARM based system are provided to illustrate the concepts and the techniques. This paper is not intended as a comprehensive review, rather as a starting point for understanding power-aware design methodologies and techniques targeted toward embedded systems.

Abstract: Conceptual design, along with need identification and analysis, make up the initial stage of the design process. Need analysis transforms the often vague statement of a design task into a set of design requirements. Conceptual design encompasses the generation of concepts and integration into system-level solutions, leading to a relatively detailed design. This 2001 book is devoted to the crucial initial stage of engineering design. In particular, it focuses on parameter analysis, a methodology that leads the user through the design process, helping to identify critical issues (parameters) of the design and propose configuration-specific solutions. To illustrate the principles discussed, the authors present numerous examples and a variety of real-world case studies. The emphasis throughout is on innovation. This useful text will appeal to advanced undergraduate and graduate students, as well as practising engineers, architects, and product development managers.

Abstract: List of Figures. List of Tables. Introduction. The Design Process. Requirements Analysis. System Design. Managing the Design Process. Detailed Design, Testing, and Design Management. Appendix A: Case Study. Appendix B: System Design Exercise.Bibliography. Index.

Abstract: The effectiveness of manufacturing enterprises that compete with product families can be leveraged through an appropriate standardization of components. In this paper we examine how a robust standardization of components can be implemented in the early stages of design with an explicit evaluation of the production system. The approach is based on (1) a mathematical formulation of design decisions using the Compromise Decision Support Problem (DSP), which includes robustness considerations, and (2) modeling production systems as networks of response surfaces. This modeling method facilitates evaluation of the impact of product design changes on the performance of the production system, thus enabling concurrent product-process design exploration. We demonstrate the approach with a case study, namely, the design of an absorber-evaporator module for a family of absorption chillers.

Abstract: For typical optimization problems, the design space of interest is well defined: It is a subset of Rn, where n is the number of (continuous) variables. Constraints are often introduced to eliminate infeasible regions of this space from consideration. Many engineering design problems can be formulated as search in such a design space. For configuration design problems, however, the design space is much more difficult to define precisely, particularly when constraints are present. Configuration design spaces are discrete and combinatorial in nature, but not necessarily purely combinatorial, as certain combinations represent infeasible designs. One of our primary design objectives is to drastically reduce the effort to explore large combinatorial design spaces. We believe it is imperative to develop methods for mathematically defining design spaces for configuration design. The purpose of this paper is to outline our approach to defining configuration design spaces for engineering design, with an emphasis on the mathematics of the spaces and their combinations into larger spaces that more completely capture design requirements. Specifically, we introduce design spaces that model physical connectivity, functionality, and assemblability considerations for a representative product family, a class of coffeemakers. Then, we show how these spaces can be combined into a “common” product variety design space. We demonstrate how constraints can be defined and applied to these spaces so that feasible design regions can be directly modeled. Additionally, we explore the topological and combinatorial properties of these spaces. The application of this design space modeling methodology is illustrated using the coffeemaker product family.