[show abstract][hide abstract] ABSTRACT: Manufacturing that minimises the exhaustion of natural resources, energy used and deleterious environmental impact is increasingly demanded by societies that seek to protect global environments as much as possible. To achieve this, life-cycle design (LCD) is an essential component of product design scenarios; however, LCD approaches have not been well integrated in optimal design methods that support quantitative decision-making. This study presents a method that yields quantitative solutions through optimisation analysis of a basic product design incorporating life-cycle considerations. We consider two types of optimisation approaches that have different aims, namely, (1) to reduce the use of raw materials and energy consumption and (2) to facilitate the reuse of the product or its parts when it reaches the end of its useful life. We also focus on how the optimisation results differ according to the approach used, from the viewpoint of the 3R concept (Reduce, Reuse and Recycling). Our method obtains optimum solutions by evaluating objectives fitted to each of these two optimisation approaches with respect to the product's life-cycle stages, which are manufacturing, use, maintenance, disposal, reuse and recycling. As an applied example, a simple linear robot model is presented, and Pareto optimum solutions are obtained for the multiobjective optimisation problem whose evaluated objectives are the operating accuracy of the robot and the different life-cycle costs for the two approaches. The characteristics of the evaluated objectives and design variables, as well as the effects of using material characteristics as design parameters, are also examined.
International Journal of Sustainable Engineering 06/2010; 3(2):81-94.
[show abstract][hide abstract] ABSTRACT: The shortening of product delivery lead-times can usually be achieved by keeping high-level components in inventory, however in small-volume production systems, maintaining such inventories is often a costly as well as a risky business strategy. If the risk of maintaining unsold inventory can be decreased, even small-volume manufacturers may be able to justify holding more significant quantities of versatile inventory. This paper discusses a component commonality effect to breakthrough the trade-off relationship between inventory levels and delivery lead-times for such small-volume production systems. By using the same component in different products, inventory maintenance costs can be dramatically reduced, but component commonality design problems are inherently complex, since excessive module commonality may lead to lower product performances, and there are trade-off relationships between product performance and cost reductions obtained through component commonality. In this paper, such a design problem is formulated as a multiobjective component commonality design optimisation problem considering inventory level, delivery lead-time and product performance, and the optimal solutions are obtained as a Pareto optimal solution set. Detailed procedures concerning the proposed design method, including inventory simulation, are discussed and developed for a switchgear design problem. Finally, an example switchgear design problem is solved to illustrate that optimal use of component commonalities across different modules can significantly reduce inventory costs, while also shortening product delivery lead-times.
International Journal of Production Research 05/2010; 48(10):2821-2840. · 1.46 Impact Factor
[show abstract][hide abstract] ABSTRACT: The SLSV (single-loop-single-vector) method is modified for the reliability-based optimization problem with multiple reliability constraints. The design problem is formulated to minimize the structural volume of frame structure in terms of cross-sectional area of each frame element subjected to the two mode reliability constraints. The two mode reliability criteria consist of the mean compliance and mean eigenfrequency. The limit state functions are formulated as normalized form to achieve numerical stability of the SLSV method, because the functions are directly adopted as constraint conditions. That is a large difference from the conventional double-loop method, where the limit state functions do not appear in the optimization loop. Through numerical examples of 2-D and 3-D frame design problems, higher computational efficiency and sufficient reliability approximation accuracy by the SLSV method are demonstrated in comparison with the conventional double loop method that the mode reliabilities are evaluated by the first order reliability method (FORM) in each optimization step. Additionally, the importance of normalization of the limit state functions in the SLSV method is also demonstrated.
Journal of Computational Science and Technology 01/2010; 4(3):172-184.
[show abstract][hide abstract] ABSTRACT: This paper proposes an optimum system design method that especially considers product lifecycles and aims to help designers make effective decisions during the product design phase. By considering and estimating all lifecycle factors of cost and environmental impact in addition to the product performance, this method facilitates development of optimum design solutions that incorporate requirements pertaining to the product's entire lifecycle. Furthermore, quantitative estimation of lifecycle factors enables the numerical expression of optimum solutions, rather than depending primarily on experiment and designer intuition. To demonstrate the effectiveness of the proposed method, this paper develops an optimum system design method for a milling machine as an example of a machine product designed for long term use. The lifecycle cost and the lifecycle environmental impact are generally expressed as the summation of each value during manufacturing phase, usage phase, disposal phase and recycling phase. In this example model, Eco-indicator 99 is used to evaluate environmental impact. In the proposed lifecycle design optimisation method, the relationships among the product performance, the lifecycle cost and the lifecycle environmental impact are evaluated as a multi-objective optimisation problem. Analysis of the obtained Pareto optimum solution sets subsequently enables designers to pursue breakthrough product design solutions.
International Journal of Sustainable Engineering 09/2009; 2(3):171-183.
[show abstract][hide abstract] ABSTRACT: Electromagnetic waveguides effectively conduct electromagnetic microwaves using resonance phenomena in RF-ranges, and are widely used in high-frequency electronic devices and equipment. The waveguide guiding characteristics related to eigen-frequencies and eigen-modes are critical factors determining the design performances pertaining to the bandwidth of appropriate response frequencies, and high performance electromagnetic waveguides can be obtained by designing cross-sections of waveguides that appropriately control such guiding characteristics at the conceptual design phase. This paper proposes a new application of a topology optimization method for the design of inhomogeneous electromagnetic waveguide cross-sections composed of dielectric material and air, with the resulting configurations performing according to specified guiding characteristics. First, the concept of topology optimization and a way to apply it to electromagnetic wave problems are explained. Next, design requirements for the design of waveguide cross-sections are clarified and corresponding objective functions and the optimization problem are formulated. A new multi-objective function is formulated to reduce grayscales since using a penalization parameter for physical property interpolation is ineffective in electromagnetic problems. The optimization algorithm is constructed based on these formulations, Sequential Linear Programming and the finite element method, where hybrid edge/nodal elements are used. Finally, several design examples of waveguide cross-sections are presented to confirm the usefulness of the proposed method.
[show abstract][hide abstract] ABSTRACT: In structural designs considering thermal loading, in addition to heat conduction within the structure, the heat convection upon the structure’s surface can significantly influence optimal design configurations. In this paper, we focus on the influence of design-dependent effects upon heat convection and internal heat generation for optimal designs developed using a topology optimization scheme. The method for extracting the structural boundaries for heat convection loads is constructed using a Hat function, and heat convection shape dependencies are taken into account in the heat transfer coefficient using a surrogate model. Several numerical examples are presented to confirm the usefulness of the proposed method.
International Journal of Heat and Mass Transfer. 01/2009;
[show abstract][hide abstract] ABSTRACT: In optimization problems that aim to minimize sound pressure levels, for simplicity, rather than calculating sound pressure directly, elastic structures have been designed so that fundamental eigen-frequencies rigorously depart from excitation frequencies, or so that radiation efficiency is reduced within target frequency ranges. In this paper, we propose a new topology optimization method for the design of soundproof structures consisting of a poroelastic material and an elastic material, which directly minimizes sound pressure levels inside an acoustic cavity by applying damping material to the system. Biot’s theory is incorporated into the optimization method to deal with the poroelastic material. The elastic material and the air medium surrounding a soundproof structure are equivalently represented in expressions in agreement with Biot’s theory. In this method, a new material interpolation scheme for poroelastic materials based on the density approach is also proposed. Several two-dimensional design problems are presented to demonstrate that the proposed method can provide clear configurations for soundproof structures that reduce sound pressure levels within specified frequency ranges.
Computer Methods in Applied Mechanics and Engineering 01/2009; · 2.62 Impact Factor
[show abstract][hide abstract] ABSTRACT: This paper proposes an innovative, integrated design method for the design of practical and sophisticated compliant mechanisms. The approach consists of two optimisation methods, topology and shape optimisation, plus a scheme to implement designer input of ideas. In the first step, a designer explores the most fruitful design concepts for mechanisms that achieve the design specifications, by combining compliant mechanisms created by the topology optimisation with additional mechanisms prepared by the designer. In this first step, a support method based on the visualisation of the designer's thinking processes assists the designer in his or her exploration of new ideas and design concepts. In the second step, the shape optimisation yields a detailed optimal shape based on the design concept. The combination of compliant mechanisms with the additional mechanisms enables the creation of devices having increased capability or higher performance than would be possible using a single compliant mechanism designed by topology optimisation alone. Executing the shape optimisation after initial design concepts have been explored facilitates the determination of a detailed optimal shape, and also enables to consider non-linear analysis and stress concentration and to make accurate quantitative performance evaluations, which topology optimisation cannot provide.
[show abstract][hide abstract] ABSTRACT: Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)—the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.
[show abstract][hide abstract] ABSTRACT: To achieve truly optimal system reliability, the design of a complex system must address multilevel reliability configuration concerns at the earliest possible design stage, to ensure that appropriate degrees of reliability are allocated to every unit at all levels. However, the current practice of allocating reliability at a single level leads to inferior optimal solutions, particularly in the class of multilevel redundancy allocation problems. Multilevel redundancy allocation optimization problems frequently occur in optimizing the system reliability of multilevel systems. It has been found that a modular scheme of redundancy allocation in multilevel systems not only enhances system reliability but also provides fault tolerance to the optimum design. Therefore, to increase the efficiency, reliability and maintainability of a multilevel reliability system, the design engineer has to shift away from the traditional focus on component redundancy, and deal more effectively with issues pertaining to modular redundancy. This paper proposes a method for optimizing modular redundancy allocation in two types of multilevel reliability configurations, series and series–parallel. A modular design variable is defined to handle modular redundancy in these two types of multilevel redundancy allocation problem. A customized genetic algorithm, namely, a hierarchical genetic algorithm (HGA), is applied to solve the modular redundancy allocation optimization problems, in which the design variables are coded as hierarchical genotypes. These hierarchical genotypes are represented by two nodal genotypes, ordinal and terminal. Using these two genotypes is extremely effective, since this allows representation of all possible modular configurations. The numerical examples solved in this paper demonstrate the efficacy of a customized HGA in optimizing the multilevel system reliability. Additionally, the results obtained in this paper indicate that achieving modular redundancy in series and series–parallel systems provides significant advantages when compared with component redundancy. The demonstrated methodology also indicates that future research may yield significantly better solutions to the technological challenges of designing more fault-tolerant systems that provide improved reliability and lower lifecycle cost.
[show abstract][hide abstract] ABSTRACT: Compliant mechanisms are a new type of mechanism, designed to be flexible in order to achieve a specified motion as a mechanism. Such mechanisms can function as compliant thermal actuators in Micro-Electro Mechanical Systems (MEMS) by intentionally designing configurations that exploit thermal expansion effects in elastic material when appropriate portions of the mechanism structure are heated. Compliant thermal actuators of this type have been designed using a trial and error approach, but creating high performance actuators this way is difficult. Topology optimization  is a highly flexible structural optimization method, allowing changes not only in shape but also in the topology of target structures, and it can yield high performance structural configurations. Sigmund  successfully used topology optimization in the design of compliant thermal actuators, however numerical problems such as grayscales and hinges ,  are often encountered.
European Congress on Computational Methods in Applied Sciences and Engineering. 07/2008;
[show abstract][hide abstract] ABSTRACT: Topology optimization  is considered the most flexible structural optimization method because it allows changes in topology as well as shape, and most studies focus on structural problems such as stiffness maximization. Thermal problems have mainly been discussed in terms of their application in the construction of a basic optimization theory using a homogenization method , due to their relatively simple constitutive equations. Topology optimization methods based on the SIMP method [3,4] have recently been proposed for actual heat transfer engineering problems, however due to the inabillity to precisely define structural boundaries in the fixed design domain, boundary conditons such as heat transfer boundry contitions, which should be set on the structual boundaries, can not be defined for the usual topology optimizaiton methods. To overcome the above isuees, Chen and Kikuchi, and Sigmund and Causen proposed a mixed displacement-pressure formulation for structural problems, but this has not been applied to thermal problems. Yoo et al., proposed the Element Connectivity Parameterization method , but this leads to theoretical inconsistencies with continuum mechanics. Bruns proposed a way to extract the structual boundaries for thermal problems, but this does not consider the shape dependencies with respect to heat transfer coeffients.
European Congress on Computational Methods in Applied Sciences and Engineering. 07/2008;
[show abstract][hide abstract] ABSTRACT: This article proposes a new multiobjective optimization method for structural problems based on multiobjective particle swarm optimization (MOPSO). A gradient-based optimization method is combined with MOPSO to alleviate constraint-handling difficulties. In this method, a group of particles is divided into two groups---a dominated solution group and a non-dominated solution group. The gradient-based method, utilizing a weighting coefficient method, is applied to the latter to conduct local searching that yields superior non-dominated solutions. In order to enhance the efficiency of exploration in a multiple objective function space, the weighting coefficients are adaptively assigned considering the distribution of non-dominated solutions. A linear optimization problem is solved to determine the optimal weighting coefficients for each non-dominated solution at each iteration. Finally, numerical and structural optimization problems are solved by the proposed method to verify the optimization efficiency.
[show abstract][hide abstract] ABSTRACT: In this study, a robust topology optimization method is proposed for compliant mechanisms, where the effect that variation of the input load direction has on the output displacement is considered. Variations are evaluated through a sensitivity-based robust optimization approach, with the variance evaluated using first-order derivatives. The robust objective function is defined as a combination of maximizing the output deformation under the mean input load and minimizing variation in the output deformation as the input load is varied, where variance due to changes in load can be obtained through mutual compliance and the presence of a pseudo load. For the topology optimization, a modified homogenization design method using the continuous approximation assumption of material distribution is adopted. The validity of the proposed method is confirmed with two compliant mechanism design problems. The effect that varying the input load direction has upon the obtained configurations is investigated by comparing these with deterministic optimum topology design results.
Journal of Advanced Mechanical Design Systems and Manufacturing 01/2008; 2(1):96-107. · 0.49 Impact Factor
[show abstract][hide abstract] ABSTRACT: This paper describes a new design method to optimize thickness distribution of a multilayered structure which is located on the coupling surface between a structure and an acoustic cavity. The design method is based on the concept of the density approach in topology optimization incorporating a transfer matrix for a multilayered structure that includes a poroelastic media layer. The one-dimensional transfer matrix adopted here is an approximate representation addressing vibro-acoustic effects inherent in a multilayered structure, and balances calculation resources and desired accuracy. Applying the transfer matrix representation as boundary conditions on the coupling surface between a structure and an acoustic cavity, the modified equilibrium equation of the vibro-acoustic system is derived which is approximately but efficiently solved by the modal approach. In this study, the problem of minimizing the acoustic pressure within the cavity over the prescribed frequency range is formulated under the volume constraint of the poroelastic media layer. The continuous approximation of thickness distribution is assumed, and the thickness of the poroelastic media layer at each nodal point is chosen as design variables. Numerical results show that an acoustic response is significantly reduced by the optimal thickness distribution having a total weight equal to or less than that in the initial uniform thickness. These demonstrate that the proposed method is effective to design the optimal thickness distribution of a multilayered structure.
[show abstract][hide abstract] ABSTRACT: In this research, we propose a new topology optimization method for the design of dielectric resonator antennas (DRAs) aiming to operate with enhanced bandwidths at multiple operational bands, using the finite difference-time domain (FDTD) method for electromagnetic analysis and the finite element method (FEM) for structural mechanics analysis. First, the concept of topology optimization is briefly discussed, and a way to integrate topology optimization with the FDTD method and the FEM is proposed. Next, a DRA design example is presented to confirm the usefulness of the proposed method.
Antenna Technology: Small and Smart Antennas Metamaterials and Applications, 2007. IWAT '07. International Workshop on; 04/2007
[show abstract][hide abstract] ABSTRACT: This paper proposes a method for modular redundancy optimization in a hierarchical series reliability system. A modular design variable is defined and modular redundancy is allocated to a different hierarchical level. An especially appropriate genetic algorithm, a hierarchical genetic algorithm (HGA), is used to solve the modular redundancy optimization. The results obtained indicate that modular redundancy provides significant advantages when compared with component redundancy. The methodology also indicates that future research may yield significantly superior solutions to technological challenges in designing more fault-tolerant systems that provide improved reliability and lower lifecycle cost.
Reliability and Maintainability Symposium, 2007. RAMS '07. Annual; 02/2007