Multiobjective Optimization Method for Lifecycle Design of Machine Products

Author(s):  
Kenji Doi ◽  
Masataka Yoshimura ◽  
Shinji Nishiwaki ◽  
Kazuhiro Izui

Manufacturing that minimizes 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, lifecycle 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 optimization analysis of a conceptual product design incorporating lifecycle considerations. We consider two types of optimization 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 optimization results differ according to the approach used, from the view point of the 3R concept (Reduce, Reuse and Recycling). Our method obtains optimum solutions by evaluating objectives fitted to each of these two optimization approaches with respect to the product’s lifecycle 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 optimization problem whose evaluated objectives are the operating accuracy and the different lifecycle costs for the two approaches. The characteristics of the evaluated objectives and design variables, as well as the effects of using material properties as design parameters, are also examined.

Author(s):  
Lifang Zeng ◽  
Dingyi Pan ◽  
Shangjun Ye ◽  
Xueming Shao

A fast multiobjective optimization method for S-duct scoop inlets considering both inflow and outflow is developed and validated. To reduce computation consumption of optimization, a simplified efficient model is proposed, in which only inflow region is simulated. Inlet pressure boundary condition of the efficient model is specified by solving an integral model with both inflow and outflow. An automated optimization system integrating the computational fluid dynamics analysis, nonuniform rational B-spline geometric representation technique, and nondominated sorting genetic algorithm II is developed to minimize the total pressure loss and distortion at the exit of diffuser. Flow field is numerically simulated by solving the Reynolds-averaged Navier–Stokes equation coupled with k–ω shear stress transport turbulence model, and results are validated to agree well with previous experiment. S-duct centreline shape and cross-sectional area distribution are parameterized as the design variables. By analyzing the results of a suggested optimal inlet chosen from the obtained Pareto front, total pressure recovery has increased from 97% to 97.4%, and total pressure distortion DC60 has decreased by 0.0477 (21.7% of the origin) at designed Mach number 0.7. The simplified efficient model has been validated to be reliable, and by which the time cost for the optimization project has been reduced by 70%.


2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.


Author(s):  
Ethan Boroson ◽  
Samy Missoum

Nonlinear energy sinks (NESs) are promising devices for achieving passive vibration mitigation. Unlike traditional tuned mass dampers (TMDs), NESs, characterized by nonlinear stiffness properties, are not tuned to specific frequencies and absorb energy over a wider range of frequencies. NES efficiency is achieved through time-limited resonances, leading to the capture and dissipation of energy. However, the efficiency with which a NES dissipates energy is highly dependent on design parameters and loading conditions. In fact, it has been shown that a NES can exhibit a near-discontinuous efficiency. Thus, NES optimal design must account for uncertainty. The premise of the stochastic optimization method proposed is the segregation of efficiency regions separated by discontinuities in potentially high dimensional space. Clustering, support vector machine classification, and dedicated adaptive sampling constitute the basic techniques for maximizing the expected value of NES efficiency. Previous works depended solely on the ratio of energy dissipated by the NES for clustering. This work also includes information about the type of m:p resonances present. Three examples of optimization for the maximization of the expected value of efficiency for NESs subjected to transient loading are presented. The optimization accounts for both design variables with uncertainty and aleatory variables to characterize loading.


2005 ◽  
Vol 11 (1) ◽  
pp. 103-120 ◽  
Author(s):  
K. R. Asfar ◽  
S. N. Akour

We present a numerical study for the suppression of self-excited vibrations represented by a Rayleigh oscillator using an impact viscous damper. A systematic approach based on a univariate search optimization method is used to determine the best design parameters for suppressing self-excited vibrations. The suggested system is found to be effective in suppressing this type of vibration. Optimum parameters for complete quenching of such vibrations are obtained. We investigate quasi-static as well as dynamic variations of the bifurcation parameter for both supercritical and subcritical Hopf bifurcation.


2021 ◽  
Vol 2137 (1) ◽  
pp. 012075
Author(s):  
Xi Feng ◽  
Yafeng Zhang

Abstract An improved immune genetic algorithm is used to design and optimize the wing structure parameters of a competition aircraft. According to the requirements of aircraft design, multi-objective optimization index is established. On this basis, the basic steps of using immune algorithm to optimize the main design parameters of aircraft wing structure are proposed, and the optimization of the wing parameters of a competition aircraft is used as an example for simulation calculation. The design variables in the optimization are the size of the wing components, and the optimization goal is to minimize the weight of the wing and the maximum deformation of the wing structure. Research shows that compared with traditional optimization methods; the improved immune genetic algorithm is a very effective optimization method. At the same time, a prototype is made to check the validity and feasibility of the design. Flight test results show that the optimization method is very effective. Although the method is proposed for competition aircraft, it is also applicable to other types of aircraft.


2021 ◽  
Vol 20 (2) ◽  
pp. 136
Author(s):  
Sugoro Bhakti Sutono

This paper presents a multi-response optimization method that uses the grey-based Taguchi method as the integrative product form design optimization method, and it serves as a tool for product form design to determine the optimal combination of design parameters in Kansei engineering (KE). This method is unique in that it combines the Taguchi method (TM) and grey relational analysis (GRA), allowing it to take advantage of the benefits of both methods. The TM is used to design experiments and generate combinative product form design samples which can be used to improve product quality. The GRA is applied to multi-response optimization problems. Factor effect analysis and analysis of variance (ANOVA) are used to determine which combinations of design parameters will result in the optimal product design. To demonstrate the applicability of the grey-based TM, a case study of a car form design is presented, and a confirmation test is performed to verify the performance of the optimal product design. The results show that the grey-based TM can deal with optimization problems with multiple Kansei responses and determine an optimal car form design that is representative of the consumers' perception in a systematic manner. The confirmation test results also show that the optimal product design generated by the grey-based TM can be used to improve the overall quality of a product form.


2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Rui Meng ◽  
Nenggang Xie ◽  
Lu Wang

Based on the similarity between the game theory and the multiobjective design, the bionic mapping and the space mapping are established between the multiobjective optimization model and game model. Then, the multiobjective optimization method based on self-adaptive space division of design variables is proposed. The design variables are divided into multiple strategy subspaces and are assigned to corresponding game players by calculating impact factors,K-means clustering, and correlation analysis. Strategy subspaces of game players are dynamically adjusted in the iteration process. In their own strategy subspaces, each game player takes their payoff function (the mapping of objective function) as monoobjective optimization. It gives the best strategy upon other players. And the best strategies of all players are combined into the group strategy in this game round. Triobjective optimization is carried out for vehicle suspension in this method and it is compared with the traditional game method. The results show that this method has better calculating automaticity and can effectively promote generalization of multiobjective game method and improve the computational efficiency and precision.


2013 ◽  
Vol 365-366 ◽  
pp. 77-81
Author(s):  
Zhi Wei Feng ◽  
Qian Gang Tang ◽  
Qing Bin Zhang

A multiobjective optimization based vibration isolator design for space application is described. It is common to use passive isolator and isolate the platform noise in space applications. The design of a passive isolator involves a trade-off between the resonant peak reduction and the high frequency attenuation. The equation of motion and transfer function model for single-stage and two-stage connector model is derived by using basic principle. The multiobjective optimization model is proposed, where the design variables are the damping coefficients and stiffness coefficients, the objective functions are the resonant peak reduction and the high frequency attenuation, and the constraints are the natural frequency of the connector. The multiobjective optimization problems for the design of the passive isolator are solved by using the multiobjective evolutionary algorithm based on decomposition (MOEA/D). The Pareto front obtained can provide multiple candidate solutions for the designer. The method is effective for the design process of the passive isolator.


2011 ◽  
Vol 50-51 ◽  
pp. 135-139
Author(s):  
Tie Yi Zhong ◽  
Chao Yi Xia ◽  
Feng Li Yang

Based on optimization theories, considering soil-structure interaction and running safety, the optimal design model of the seismic isolation system with lead-rubber bearings (LRB) for a simply supported railway beam bridge is established by using the first order optimization method in ANSYS, which the parameters of the isolation bearing are taken as design variables and the maximum moments at the bottom of bridge piers are taken as objective functions. The optimal calculations are carried out under the excitation of three practical earthquake waves respectively. The research results show that the ratio of the stiffness after yielding to the stiffness before yielding has important effect on the structural seismic responses. Through the optimal analysis of isolated bridge system, the optimal design parameters of isolation bearing can be determined properly, and the seismic forces can be reduced maximally as meeting with the limits of relative displacement between pier top and beam, which provides efficient paths and beneficial references for dynamic optimization design of seismic isolated bridges.


2021 ◽  
Author(s):  
Wenjie Wang ◽  
Qifan Deng ◽  
Ji Pei ◽  
Jinwei Chen ◽  
Xingcheng Gan

Abstract Pressure fluctuation due to the rotor-stator interaction in turbomachinery is unavoidable, inducing strong vibration and even shortening the lifecycle. The investigation on optimization method of an industrial centrifugal pump was carried out to reduce the pressure fluctuation intensity. Considering the time-consuming transient calculation of unsteady pressure, a novel optimization strategy was proposed by discretizing design variables and genetic algorithm. Four highly related design parameters were chosen, and 40 transient sample cases were generated and simulated using an automatic simulation program. Furthermore, a modified discrete genetic algorithm (MDGA) was proposed to reduce the optimization cost by unsteady simulation. For the benchmark test, the proposed MDGA showed a great advantage over the original genetic algorithm in terms of searching speed and could deal with the discrete variables effectively. After optimization, an improvement in terms of the performance and stability of the inline pump was achieved.


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