基于实例推理的小型液压机参数化

结合小型液压机企业的实际需求,充分利用现有资源,基于实例推理的思想,引入参数化理论和有限元技术,采用vc++对SolidWorks进行二次开发,开发了一个由参数化CAD模块、数据库模块和有限元分析与优化模块构成的小型液压机参数化CAD系统.使用结果表明该系统大大提高了设计效率.     

面向可适应性的产品平台设计参数规划方法

 在分析已有产品平台特点的基础上,将模块化和参数化产品平台统一表示为基于“设计参数”的产品平台,提出了面向可适应性的产品平台设计参数规划方法．引入可适应设计理念,分析了产品平台结构及变型方式;以公理设计理论为指导,进行产品功能要求 设计参数的映射,建立公理设计矩阵;分析各设计参数之间及其与功能要求之间的敏感性,构建设计关联矩阵并对其进行关联度分析;然后通过变型产品关于设计参数的差异度计算,合理识别平台参数和变型参数,确定设计参数在产品平台中的共享策略．通过桥式起重机产品族的柔性配置实例,证明了该方法的可行性和实用性．     

串联生产系统智能维护调度实验平台研究

结合工业工程专业学习需求,设计了考虑有限缓存的串联生产系统维护调度实验平台。实验平台由维护调度计算模块和维护调度演示模块组成。维护调度计算模块基于Matlab,在考虑有限缓存的串联生产系统维护调度模型的基础上,提供3种不同的策略对维护进行调度;维护调度演示模块基于Flexsim。基于该平台,可完成维护调度参数分析、维护调度策略分析、维护调度仿真等实验,并可在此平台基础上建立维护调度相关参数优化模型。     

基于ANSYS的产品缓冲包装的分析与设计

以被包装产品的计算机模型为研究对象,以有限元分析软件ANSYS为平台,通过对产品的静态和动态的仿真分析来确定产品的脆值、固有频率等缓冲包装设计的重要参数,并以此为设计依据,来设计产品的缓冲包装衬垫和外包装箱.在设计产品缓冲包装的同时,可以通过ANSYS的优化分析模块对缓冲包装进行优化分析,以避免过度包装并节省包装成本.该研究可以大大缩短并简化缓冲包装的设计流程,其结果也更为科学可靠.     

汽车车身包边工艺及表面质量分析

在汽车车身的制造过程中,很多部件是将内板和外板通过包边合成的,在车门、车厢和发动机罩的制作中需要运用到包边工艺。完成汽车的包边工艺需要采用简易的胎具对包边工艺支持,然后用木榔头把车身的每一个部位敲砸,采用这种工艺可以节省资金,而且工艺比较简单,但是这种工艺的效率特别低,需要耗费大量的人力,产品的质量比较低,形成废品比重大,在施工过程中要耗费很多木榔头,与汽车生产的规模不能协调。汽车车身的包边技术主要是分为手工包边、压力机模具包边和液压包边,文章重点分析汽车车身的包边技术。     

可空投系留平台空投跌落冲击响应研究

目的实现可空投系留平台软着陆,为优化可空投系留平台的隔振缓冲设计提供理论参考。方法将可空投系留平台等效为二自由度非线性隔振缓冲系统,在Matlab环境中,采用四阶龙格-库塔方法,对可空投系留平台跌落冲击响应进行数值仿真,并分析系统参数对系留平台中继模块空投跌落冲击响应的影响。结果得到动态响应数据和曲线,避免了大量破坏性试验,得到不同参数条件下的跌落冲击仿真结果。结论根据隔振缓冲仿真系统的动态响应规律,可对隔振缓冲包装的安全性进行评估,实时修改设计参数,有效地提高隔振缓冲包装设计的精确性和经济性。     

基于参数化设计的现代汽车车身设计方法研究

研究汽车车身的参数化设计方法,通过参数化设计采用几何约束控制产品形状的几何特点,改变约束可迅速获得不同的设计结果,提高设计效率,有助于减轻设计人员的工作强度。并针对目前计算机辅助系统在平台交互性,构造虚拟现实方面的不足,展望了未来汽车车身设计方法的发展方向。     

通用电机产品族协同设计的模糊优化

产品族设计是大规模定制中的核心内容,许多文献在假定产品特征确定情况下,采用平台参数和非平台参数,提出了大规模定制下的产品族设计优化方法。基于产品族设计理念,针对含有不确定特征的产品族设计中的一种基本类型——产品参数与产品功能之间的映射含有模糊系数的情形,建立一种对平台参数和非平台参数进行协同优化的模糊双层线性规划模型,利用有关模糊算法对模糊条件下的通用电机产品族协同设计进行优化。     

汽车门盖胶泡问题研究

该文针对汽车门盖经涂装涂胶烘烤后产生PVC胶泡的问题,分析了胶泡产生的原理,根据查理定律、水蒸气温度与压力的关系得知在体积不变的情况下,空气和水蒸汽的压力相比于常温情况下会明显上升,压力上升导致胶泡的产生。通过对门盖包边工艺中折边胶涂胶位置优化、涂胶直径优化、包边参数优化以及涂装烘烤温度参数的控制,避免空腔的形成、提升门盖的干燥度的关键要素着手,减少胶泡产生的概率,提高过程稳定性与产品质量。     

采用SolidWorks API的离心式叶轮参数化建模

离心式叶轮是离心压缩机产品的核心零件,结构形状复杂,对其开展参数化建模研究可提升设计质量和效率.分析了三维CAD平台下离心式叶轮三维建模的一般步骤,构建了采用SolidWorks API的参数化建模方案.分别讨论了叶片、轮盘和轮盖的参数化建模实现原理.以Visual Basic为开发工具,在SolidWorks环境下实现了离心式叶轮的参数化自动建模.应用实例表明,在该软件支持下可高效地进行离心式叶轮的参数化设计与优化.     

Product platform design through clustering analysis and information theoretical approach

An effectively designed product platform is vital to the final product family derived from it. A product platform design consists of platform configuration to decide which variables to make common across the product family and to determining the optimal values for platform and scaling variables for all product variants. Many existing product family design methods assume a given platform configuration, i.e. the platform variables are specified a priori by designers. However, selecting the right combination of common and scaling variables is not trivial. Most approaches are single-platform methods, in which design variables are either shared across all product variants or not at all. While in multiple-platform design, platform variables can have special value with regard to a subset of product variants within the product family, offering opportunities for superior overall design. This paper proposes a quantitative method for scale-based multiple-platform design using clustering analysis and Shannon's Entropy theory. Optimization methods are used to design the product family by holding the values of platform variables constant and to find the best values of the scaling variables. An information theoretical approach is used to help select platform variables based on the clustering analysis of individually designed products. Validity analysis is performed to determine the optimal settings for platform variables. Local clustering is further performed on each platform variable, to establish subsets of variants such that variants within a subset are more similar to each other than they are to variants in other subsets and a common value is used to represent the various values of variants in each subset. A case study is used to illustrate the process of the proposed method, and the design solutions are compared with that found by other methods given in previous literature. The comparison results verified that the multiple-platform design can lead to superior solutions of product family.     

基于优化的产品平台参数规划方法

 为满足客户化和全球竞争的需求,企业要实现大规模定制(mass customization,MC).基于公共产品平台的产品族设计是实现大规模定制的一种有效方式,而平台规划是面向产品族设计方法学的核心内容,也是目前研究中的一个热点问题.基于模型参数的平台设计是其方法之一.针对基于一系列标准可变参数的产品平台,用优化方法对产品平台参数进行规划,以满足各种客户需求.该规划方法无需事先人为指定,而是在满足客户需求的前提下,尽可能提高产品族中设计变量的共性,从而确定最好的产品平台的公共参数及其最优值,以及个性参数及其变化值,并以带式输送机为例验证了该方法.     

产品可适应设计评价的信息熵方法

随着用户对产品的功能、质量、成本、个性化以及环境友好性等方面的需求日益提升,制造企业必须更加即时、高效地响应不断变化的市场需求.可适应设计作为一种新型的设计范式,可通过设计过程的综合优化来满足产品生命周期内用户、制造企业和社会的需求,以提升经济效益和环境效益等.为了提高产品设计的可适应性,需对可适应性进行量化的科学表达...     

A Variation-Based Method for Product Family Design

Product family design entails all of the challenges of product design while adding the complexity of coordinating the design of multiple products in an effort to maximize commonality across a set of products without compromising their individual performance. This paper presents the Variation-Based Platform Design Method (VBPDM) for product family design, which aims to satisfy a range of performance requirements using the smallest variation of the product designs in the family. In the first stage of the VBPDM, the product platform around which the product family is to be developed is identified. The product platform is common to all of the products in the family and represents the maximum standardization possible considering the variety of performance requirements that must be satisfied. To satisfy the range of performance requirements for the product family, a ranged set of solutions is found using variation-based modeling. A compromise Decision Support Problem (DSP) is formulated to solve the tradeoff between satisfying the variety requirement and maximizing platform commonality. Platform commonality is achieved by introducing a commonality goal that seeks to minimize the deviation of the input design variables while satisfying the range of performance requirements. Those design variables that show small deviations are held constant to form the product platform. In the second stage of the VBPDM, each individual product is designed around the common platform such that the functional requirements for each product in the family are best satisfied. As an example, the proposed method is used to develop a family of universal electric motors designed to meet a range of torque requirements. The results are compared against previous work on the same example.     

Optimal platform design using non-dominated sorting genetic algorithm II and technique for order of preference by similarity to ideal solution; application to automotive suspension system

Unlike conventional approaches where optimization is performed on a unique component of a specific product, optimum design of a set of components for employing in a product family can cause significant reduction in costs. Increasing commonality and performance of the product platform simultaneously is a multi-objective optimization problem (MOP). Several optimization methods are reported to solve these MOPs. However, what is less discussed is how to find the trade-off points among the obtained non-dominated optimum points. This article investigates the optimal design of a product family using non-dominated sorting genetic algorithm II (NSGA-II) and proposes the employment of technique for order of preference by similarity to ideal solution (TOPSIS) method to find the trade-off points among the obtained non-dominated results while compromising all objective functions together. A case study for a family of suspension systems is presented, considering performance and commonality. The results indicate the effectiveness of the proposed method to obtain the trade-off points with the best possible performance while maximizing the common parts.     

Effective Product Family Design Using Physical Programming

In response to today's highly competitive global marketplace, many companies are utilizing product families - groups of related products derived from a product platform - to maintain economies of scale while satisfying a variety of customer requirements. This paper focuses on scale-based product families and presents a new single-stage approach for simultaneously optimizing a product platform and the resulting family of products based on one or more scaling variables - variables that are used to instantiate the product platform by "stretching" or "shrinking" it in one or more dimensions to satisfy a variety of customer requirements. The proposed approach is also unique in that it employs the Physical Programming method, enabling designers to formulate the product family optimization problem in terms of physically meaningful terms and parameters. The design of a family of ten universal electric motors is used as an example to benchmark the effectiveness of the proposed approach against previous results. While the emphasis in this paper is on the design method rather than the results per se , performance gains are achieved in the motor family by using the proposed single-stage approach and Physical Programming.     

机械产品可适应性度量方法及应用

基于信息论中信息熵的概念,用构成产品的模块集合来描述产品的当前状态,提出用可适应信息熵函数来表征产品设计的复杂性和不确定性,在此基础上提出了新的基于可适应信息熵的产品可适应度的计算公式.提出了2种可适应度计算方法,即基于结构配置图的可适应度计算和基于功能结构图的可适应度计算.实例研究表明,该可适应度具有很好的可操作性和实用性,能够应用于产品的开发和设计实践.     

Modularity analysis and commonality design: a framework for the top-down platform and product family design

With a highly fragmented market and increased competition, platform-based product family design is recognised as an effective method for constructing a product line that satisfies diverse customer demand while keeping design and production cost- and time-effective. Recognising the need for modularity and commonality in platform development, this paper presents a systematic framework to assist in implementing top-down platform and product family design, which aims to achieve system-level modularity for variety generation, and rationalise the commonality configuration for module instantiation. In the first phase of platform development, a robust and flexible product family architecture is constructed to accommodate variations by analysing the external varieties of the generic product architecture, and provide a modularity design space, wherein the design tasks are further decomposed into module instantiation. The second phase of detailed platform development aims to enhance commonality in terms of engineering efficiency by coordinating with the back-end product realisation stage. A tractable optimisation method is used to capture and resolve the trade-off between commonality configuration and individual product performance. A family of power tool designs is used to demonstrate the potential and feasibility of the proposed framework at the system level and detailed design stages.     

Media milling process optimization for manufacture of drug nanoparticles using design of experiments (DOE)

Design of experiments (DOE), a component of Quality by Design (QbD), is systematic and simultaneous evaluation of process variables to develop a product with predetermined quality attributes. This article presents a case study to understand the effects of process variables in a bead milling process used for manufacture of drug nanoparticles. Experiments were designed and results were computed according to a 3-factor, 3-level face-centered central composite design (CCD). The factors investigated were motor speed, pump speed and bead volume. Responses analyzed for evaluating these effects and interactions were milling time, particle size and process yield. Process validation batches were executed using the optimum process conditions obtained from software Design-Expert® to evaluate both the repeatability and reproducibility of bead milling technique. Milling time was optimized to <5?h to obtain the desired particle size (d90?相似文献