An integrated joint optimization procedure for robust and tolerance design

Many manufacturers have discovered that optimizing design parameters is a costeffective means of improving product quality and being competitive in the world market. In this regard, the issues of robust design (RD) and tolerance design (TD) are clearly important, but there is significant room for improvement. The primary objective of this paper is to propose a set of enhanced optimization strategies by combining RD and TD. To be more specific, first, we consider an alternative experimental scheme using response surface methodology, while avoiding the use of controversial tools for RD such as orthogonal arrays and signal-to-noise ratios. Secondly, we discuss an enhanced optimization model by simultaneously considering both the process mean and variance, and then show that this model provides a better (or at least equal) solution in terms of the control factor settings. Thirdly, we show how the response functions for the process mean and variance, which are estimated by using an RD principle, are transmitted into the TD stage. Fourthly, we propose an optimization model for TD and present closed-form solutions for optimum tolerance limits. Finally, we study the possible effects of major cost components, and observe the behaviour of the optimum control parameter settings and the tolerance limits by carrying out sensitivity analysis.     

An integrated reliability-based design optimization of offshore towers

After recognizing the uncertainty in the parameters such as material, loading, geometry and so on in contrast with the conventional optimization, the reliability-based design optimization (RBDO) concept has become more meaningful to perform an economical design implementation, which includes a reliability analysis and an optimization algorithm. RBDO procedures include structural analysis, reliability analysis and sensitivity analysis both for optimization and for reliability. The efficiency of the RBDO system depends on the mentioned numerical algorithms. In this work, an integrated algorithms system is proposed to implement the RBDO of the offshore towers, which are subjected to the extreme wave loading. The numerical strategies interacting with each other to fulfill the RBDO of towers are as follows: (a) a structural analysis program, SAPOS, (b) an optimization program, SQP and (c) a reliability analysis program based on FORM. A demonstration of an example tripod tower under the reliability constraints based on limit states of the critical stress, buckling and the natural frequency is presented.     

A genetic algorithms-based approach for design of manufacturing systems: An industrial application

This paper presents a design methodology and a genetic algorithm-based approach for redesign of a manufacturing system for a small steel pre-fabricated building manufacturer. Through the application of celular manufacturing principles, we discuss the application of the design methodology that takes a topdown approach to determine system needs and a bottom-up integrated design approach to develop the configurations of the manufacturing system. The integrated design approach uses a genetic algorithm and an AutoCAD interface to minimize the inter and intra cell material movements during cell formation. A selected set of solutions obtained are further analysed using discrete event modelling and simulation. The final results presented indicate a substantial improvement in overall performance compared to the original layout. The company has implemented a modified version of the final solution and has achieved the significant improvements in material handling and overall productivity.     

结构-声场耦合系统声压响应优化设计研究

为了减小结构振动产生的噪声,基于结构-声场耦合有限元模型,对其在简谐力激励下的声响应进行了计算。在此基础上,以结构厚度为设计变量,保持结构重量相对不变并以设计变量的上、下限为约束,以设计域点在各频率响应声压平方和的平方根为目标函数,对其进行了优化设计研究。用软件N astran计算声响应及声敏度,基于iS IGHT对N astran的集成用可行方向法实施了优化。以一矩形板结构-立方体声场耦合系统为实例,得到了优化的结构厚度分布。优化后,设计域点的峰值声压级均有不同程度的降低,声压级降低最大值达32.8dB。结果表明声压响应优化设计,在保持结构重量相对不变的情况下,通过对结构重量的重新分布能达到较明显的降噪效果。     

An algorithm for engineering design optimization

In this paper a new concept for development of algorithms for optimal design of engineering systems is presented. The basic idea is to use upper and lower bounds on optimum cost to develop iterative search strategies. The main feature of the concept is that it does not rely on one-dimensional search to compute a step size at any design iteration. Implication of the feature is that the algorithms based on this concept require evaluation of constraint functions only once at any design iteration. This is highly desirable for optimal design of engineering systems because evaluation of functions for such systems is very expensive due to their implicit dependence on design variables. An algorithm based on the new concept is derived in the paper. Several new step sizes are introduced and their relation to proper reduced optimal design problems are presented. A new step size based on the constant cost requirement at some design iterations is introduced. Numerical aspects for the algorithm are also presented. Based on the new algorithm, a general-purpose computer code GRP2 is developed. The code is used to solve several problems to gain experience and insight for the algorithm. Numerical experience with examples is discussed. It is concluded that algorithms based on bounding optimum cost have substantial potential for applications in optimal design of engineering systems.     

An integrated sequential solver for large matrix equations

An integrated sequential computer programme for the solution of large linear algebraic systems encountered in the discrete analysis of complex structures using finite element idealization is described. The programme uses an algorithm based on Gauss elimination for solution and is independent of the possible symmetric nature of the system matrix thus enhancing the applicability of the programme for systems with unsymmetric coefficient matrices. The present programme can handle large band widths and the core memory is used efficiently for all feasible problem sizes. A FORTRAN print-out of the programme with relevant explanatory comments and a full notation list are appended.     

阻振质量-刚度-阻尼材料配置同步优化的基座声学设计

提出了一种通过配置阻振质量、优化构件尺寸和阻尼材料的基于声功率级约束的基座优化设计方法.不同于以往通过基座减振优化设计进而减小辐射噪声的方法,验证了基座声学优化设计对声隐身特性的直接效果.分别建立阻振质量单独优化、阻振质量-基座刚度同步优化、阻振质量-基座刚度-阻尼材料综合优化三种基座声学优化模型,比较了三种优化模型的...     

An efficient framework for the reliability-based design optimization of large-scale uncertain and stochastic linear systems

This paper is focused on the development of an efficient reliability-based design optimization algorithm for solving problems posed on uncertain linear dynamic systems characterized by large design variable vectors and driven by non-stationary stochastic excitation. The interest in such problems lies in the desire to define a new generation of tools that can efficiently solve practical problems, such as the design of high-rise buildings in seismic zones, characterized by numerous free parameters in a rigorously probabilistic setting. To this end a novel decoupling approach is developed based on defining and solving a limited sequence of deterministic optimization sub-problems. In particular, each sub-problem is formulated from information pertaining to a single simulation carried out exclusively in the current design point. This characteristic drastically limits the number of simulations necessary to find a solution to the original problem while making the proposed approach practically insensitive to the size of the design variable vector. To demonstrate the efficiency and strong convergence properties of the proposed approach, the structural system of a high-rise building defined by over three hundred free parameters is optimized under non-stationary stochastic earthquake excitation.     

Design optimization of industrial robots considering the working environment

Industrial robots are being used increasingly in complicated working environments where there are obstacles. Industrial robots most suitable for a given working environment should be designed such that they avoid obstacles while moving in the designated working space. In this paper, a design optimization method is proposed for two-degree-of-freedom rotary angular jointed robots for use in such an obstacle-inclusive working environment. In this method, the lengths of the arms and the directional orientation of the robot installation are theoretically determined. First, the algorithmic procedures of the optimization method are presented. Then analytical procedures for obtaining the feasible set of arm lengths are described. Finally, effectiveness of the method is demonstrated for designing a robot used in a given working environment.     

复杂系统的多学科设计优化综述

从设计和分析的本质出发,结合复杂系统的特点,通过分析传统设计优化流程在面对复杂系统时存在的困难和缺陷,指出多学科设计优化(multidisciplinary design optimization,MDO)方法是解决复杂系统设计优化问题的一种有效措施.在此基础上,介绍了多学科优化方法的基本思想,总结了子系统耦合方式及MDO在处理耦合时的基本方法,归纳了MDO的知识框架和主要研究内容.最后在现有研究成果的基础上,对MDO今后的研究提出了几点参考意见.     

An integrated framework for protective packaging design and manufacture

Computer-based techniques are becoming more widely used to solve design and manufacturing problems, but some firms remain sceptical as to its technical functionalities in providing realistic price/performance improvement and flexibility. The local protective packaging industry is one of those where computers are not widely used to automate the various stages of design and manufacture. A fundamental deficiency in the data integration, therefore, exists between these two processes. This paper describes an integrated technological approach to the design and manufacture of polyfoam protective products. The work will involve the use of knowledge-based techniques for protective packaging design, automated procedures for mould design, and an information communication link to the production of prototype samples and moulded products. Special emphasis would also be made as to the nature and integration of data between the various areas.     

多类型冰箱的集成式仿真设计平台

为了实现在同一平台下对常用的不同类型冰箱进行仿真设计,本文开发了多类型冰箱的集成式仿真设计平台。本文首先提出冰箱部件的通用计算模型,包括压缩机通用计算模型、换热器通用计算模型和箱体通用计算模型。然后,开发了多类型冰箱仿真平台的数据交互方法和系统控制策略的集成方法,从而建立了多类型冰箱的集成式仿真设计平台。实验验证结果表明,多类型冰箱的集成式仿真设计平台能够对常用类型的冰箱进行仿真计算,计算得出的冰箱耗电量和开机率的计算误差都在10%以内。     

An integrated framework for multi-scale materials simulation and design

In this paper, we describe initial results of an ongoing research activity involving materials scientists, computer scientists, mathematicians, and physicists from academia, industry and a national laboratory. The present work aims to develop a set of integrated computational tools to predict the relationships among chemistry, microstructure and mechanical properties of multicomponent materials systems. It contains a prototype grid-enabled package for multicomponent materials design with efficient information exchange between structure scales and effective algorithms and parallel computing schemes within individual simulation/modeling stages. As part of our multicomponent materials design framework, this paper reports the materials simulation segment in developing materials design knowledgebase, which involves four major computational steps: (1) Atomic-scale first-principles calculations to predict thermodynamic properties, lattice parameters, and kinetic data of unary, binary and ternary compounds and solutions phases; (2) CALPHAD data optimization approach to compute thermodynamic properties, lattice parameters, and kinetic data of multicomponent systems; (3) Multicomponent phase-field approach to predict the evolution of microstructures in one to three dimensions (1–3D); and (4) Finite element analysis to generate the mechanical response from the simulated microstructure. These four stages are to be integrated with advanced discretization and parallel algorithms and a software architecture for distributed computing systems.     

An integrated inventory optimization model for facility location-allocation problem

This paper presents an integrated inventory distribution optimisation model for multiple products in a multi-echelon supply chain environment. Inventory, transportation and location decisions are considered. The objective is to offer practical guideline to the steel retail supply chain practitioners in choosing the correct distribution centre, finding out inventory level at individual inventory keeping points (retailers and distribution centres) point thereby helping them in reducing overall distribution cost. The framework presented endorses systems approach and suggests near-optimal approach to calculating inventory for an individual distributor and his retailers. Two algorithms are used to solve this problem, a novel hybrid Multi-objective Self-learning particle swarm optimiser and Non-dominated sorting genetic algorithm-II. The model and solution methods are tested on real data-sets obtained from organisations in the steel retail environment. The actual data on inventory holding, ordering and transportation costs of distributors and retailers are used as inputs. The decisions like choosing correct set of Distribution centres, keeping optimal regular and safety stock inventory levels are arrived at by applying practical constraints in the supply chain. Model developed assists in effective and efficient distribution of the products manufactured from the optimal location at minimal cost.     

Using constraints and their value for optimization of large ODE systems

We provide analytical tools to facilitate a rigorous assessment of the quality and value of the fit of a complex model to data. We use this to provide approaches to model fitting, parameter estimation, the design of optimization functions and experimental optimization. This is in the context where multiple constraints are used to select or optimize a large model defined by differential equations. We illustrate the approach using models of circadian clocks and the NF-κB signalling system.     

An integrated approach to evaluating conceptual design alternatives in a new product development environment

As many companies have demonstrated over time, a conceptual design for a new product contributes greatly to an improvement in competitiveness, because it permits a reduction of costs, an increase in quality, and, often, a shortening of the time necessary to get the product on the market. That is why the evaluation of conceptual design alternatives created in a new product development (NPD) environment has long been very vital and a critical point for the future success of companies in fast-growing markets. These alternatives can be evaluated using the analytic hierarchy process (AHP), one of the most commonly used multiple criteria decision making (MCDM) techniques. This technique is used to reduce the number of conceptual design alternatives after ranking them using the scores obtained from the process. Furthermore, another technique, simulation analysis integrated with the AHP, is also used to help decision makers (product engineers or managers) perform economic analyses of the AHP's high-score alternatives using data from the generated simulation model of a real-life manufacturing system in which the final alternative is produced. In short, the objectives of this research are: first, to use the AHP technique to evaluate conceptual design alternatives in a NPD environment; second, to use a simulation generator integrated with this technique in order to perform economic analyses for the AHP's high-score alternatives. Finally, the results of both techniques, simulation and AHP, are used in a benefit/cost (B/C) analysis to reach a final decision on the conceptual design alternatives.     

Two‐scale topology optimization in computational material design: An integrated approach

In this work, a new strategy for solving multiscale topology optimization problems is presented. An alternate direction algorithm and a precomputed offline microstructure database (Computational Vademecum) are used to efficiently solve the problem. In addition, the influence of considering manufacturable constraints is examined. Then, the strategy is extended to solve the coupled problem of designing both the macroscopic and microscopic topologies. Full details of the algorithms and numerical examples to validate the methodology are provided.     

Chemometric methods applied to industrial optimization and materials optimal design

Based on the methods of multivariate data processing of the data records for complicated chemical reaction systems, computer software named `process analyzer' and `materials research advisor' has been built. The methods used include some new methods of pattern recognition, such as back-mapping methods, local-structure view and data transformation methods. These new computational techniques have been widely used in the chemical, petrochemical and metallurgical industries for industrial optimization and materials design with good results.     

An integrated approach to multi-criteria design and control of manufacturing systems using simulation and goal-regression

In this paper we discuss the issue of multi-criteria design and control of manufacturing systems. We also trace the development of domain-independent non-linear planners from the field of artificial intelligence. These planners automate the task of generating a sequence of actions to achieve a specified goal. The problem of conjunctive goal planning is addressed, and a parallel drawn with the design and control of manufacturing systems where multiple criteria are to be satisfied. The inability of existing approaches to facilitate optimization across multiple performance criteria is also highlighted. Finally, to ameliorate the problem an integrated approach based on goal-regression and simulation is proposed. To facilitate conflict-resolution across multiple goals, a new algorithm is developed. The approach is tested on different configurations of test systems and found to perform satisfactorily for manufacturing systems with fairly large sets of defining variables.