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An analytical method is studied for estimating coupling between arbitrarily directed multiple finite-length lines with different line lengths and heights. Coupling or crosstalk analysis is performed by developing an expanded circuit-concept approach based on modified telegrapher's equations of the Agrawal approach instead of the Taylor approach, providing some computational advantages. An electric image method using the quasi-static terms of the accurate Green's function is used to estimate the electromagnetic fields in an inhomogeneous medium such as a printed circuit board. The approach is applied to the analysis of parallel and nonparallel or bent microstrip models, and embedded-line models in which one line is embedded and the other is on the surface layer. To verify the proposed approach, we conducted some experiments and compared the results of our approach with the results of measurements and a commercial electromagnetic solver.

The advancement of computer networks and information technologies has been rapidly changing the manufacturing environment of the industrial age to that of the current information era. The engineering philosophy has been shifted from concurrent engineering to collaborative engineering among the respective areas of expertise in a design space. Handling uncertainties in an initial design process is of great importance, particularly for collaborative engineering. For collaborative engineering, designers having different preferences in the different disciplines need to represent their own possible design solutions or design solution spaces, and they also need to understand the other designers’ design solution spaces. We have proposed a preference set-based design method that enables a flexible and robust design under various sources of uncertainties, while capturing a designer’s preference. In this study, the proposed method was applied to a real industrial multi-objective design problem (i.e. an automotive front-side frame design). This study discusses the suitability of our proposed approach for obtaining the multi-objective satisfactory solutions that reflect the different design preferences of different designers in their design solutions for collaborative engineering.

Customer satisfaction is one of the critical success factors to many leading companies over the world. Quality function deployment (QFD) has gained extensive international support as one of the powerful techniques to increase the customer satisfaction. In the QFD, correctly rating the final importance of customer requirements (CRs) is a crucial and essential process since it largely affects the target value setting of design requirements. The final importance ratings of CRs are generally determined by combining relative importance ratings and competitive priority ratings. However, determining the final importance ratings is very difficult due to the typical uncertainty or imprecision of customer’s judgment (or perceptions). This paper proposes a novel approach to prioritize CRs in QFD process by developing two sets of new rating methods, called customer preference rating (CPR) method and customer satisfaction rating (CSR) method, for relative importance ratings and competitive priority ratings, respectively. The CPR method provides a simple and intuitive technique to capture the customers’ incomplete or uncertain perceptions on the relative importance of CRs based on their own preferences, allowing them to give a partial ordering of CRs. The CSR method constructs the customer satisfaction model based on the competitive benchmarking analysis and then evaluates the performance quality of company product using our satisfaction and uncertainty measure. Furthermore, the CSR method is integrated with the Kano’s model to capture the different impacts of CRs on customer satisfaction. Finally, the proposed approach is illustrated with a numerical example of car door design problem.

Various computer-based simulation tools such as 3D-CAD systems and CAE are widely used to design products at the early phase of design. Designers must search the optimal solution that satisfies a number of performance requirements by repeating analysis and modification of the CAD models. They need to confirm the results of CAE analysis until they can obtain a better design solution. These works impose a heavy burden on designers and analysts. Therefore, design works can be more efficient if we can automate these iterative processes. Moreover, the early phase of design contains multiple sources of uncertainty in describing design, and nevertheless the decision-making process at this phase exerts a critical effect upon drawing a successful design. Therefore, handling the uncertainties in the early phase of design has great importance especially for concurrent engineering (CE). The previous series of our studies have proposed a preference set-based design (PSD) method that enables the flexible and robust design while incorporating designer’s preference structure. In contrast to conventional optimization techniques, this method generates a ranged set of design solutions that satisfy sets of performance requirements. The combination of 3D-CAD and CAE with PSD method can be more powerful design support system. In this study, a system based on PSD method is implemented by combination of 3D-CAD and CAE, and a design example of a swing arm is demonstrated to show the effectiveness of the proposed system for obtaining the multi-objective satisfactory solutions reflecting the designers’ intentions.

So far, there has been an extraordinary development of computer-aided tools intended to generate, present or communicate 3D models. But there has not been a comparable progress in the development of 3D-CAD systems intended to assist designers in representing and manipulating both geometric and non-geometric design information based on solid models, thus facilitating concurrent engineering (CE). Design objects continue to be produced by traditional means using the computer as little more than a drafting tool. In addition, the state-of-the-art 3D-CAD systems are incapable of encoding engineering uncertainties since only precise single-valued assignments are allowed for their modeling operations. Recently, set-based CE (SBCE) has been attracting public attention as an emerging CE paradigm. Such a set-based design (SBD) approach presents many possibilities in handling the uncertainties that are intrinsic at the early phases of design. This paper addresses a novel concept – set-based parametric design (SBPD) – which combines the SBD practice with the parametric modeling technique widely used in most 3D-CAD systems. A preference set-based design (PSD) model and a design information solid (DIS) model are proposed to incorporate the SBPD concept into the current 3D-CAD systems. Finally, a prototype system is implemented to illustrate the potential to achieve a SBPD practice.

The early phase of design intrinsically contains multiple sources of uncertainties in describing the design, and nevertheless the decision-making process at this phase exerts a critical effect upon drawing a successful design. Recently, set-based concurrent engineering (SBCE) has been attracting public attention as an emerging CE paradigm. Representing and communicating set-valued information are useful in handling engineering uncertainties and efficient for the collaboration between designers in the CE environment. Even if we can readily know that SBCE is efficient and powerful enough for large-scale design and management, the existing literature does not give the details of methods to achieve SBCE principles. We have developed a computer-based framework, called ‘preference set-based design’ (PSD), for implementing SBCE principles, which consists of set representation, propagation, modification, narrowing, and aggregation methods. This article focuses on the set representation and aggregation methods that play an important role in the CE environment. This article proposes new engineering quantities that can capture the designer’s preference structure on both the continuous and the discrete sets. A new aggregation method is presented to aggregate the proposed engineering quantities. A comparative analysis with the existing representation and aggregation techniques is also provided.

Concurrent engineering (CE) has been widely accepted as an effective engineering practice for decreasing product development time, improving quality, decreasing manufacturing costs, and improving customer satisfaction. Since CE philosophy is intended to consider all elements of product life cycle from the outset, CE approach increases the complexity of design problem and makes it more difficult to manage. In addition, the advances in computer networks and information technology have brought engineering design into a new era. Although a considerable number of studies have been made on design decomposition (e.g., product and process (or perspective) decomposition) as a means to reduce the complexity of a large scale design problem, relatively little attention has been given to the computational framework for dynamic and systematic design integration in a computer network-oriented design environment. This paper describes an integrated product and process modeling (IPPM) framework for collaborative product design through the Internet. Here, the hierarchical and heterarchical dependencies between the decomposed smaller design problems are addressed. An agent-based approach is proposed for the computer support of hierarchical and heterarchical design topologies. In our framework, a smaller design problem is dynamically modeled in terms of interacting and pluggable design agents that represent a specific aspect of the design problem and provide the interoperability between heterogeneous design agents or software applications, and the results of these smaller problems are recursively integrated to formulate solutions to the larger problems in a systematic manner. Finally, the proposed framework forms a global design network through which a number of design possibilities are explored.