快速响应制造系统产品开发过程时间估计与优化
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摘要
为缩短产品开发和生产周期,在尽可能短的时问内满足客户需求,提出基于“快速响应”原理的快速响应制造系统。进行产品开发过程时间分析对于保障系统的快速响应能力,提高进度控制和管理能力具有重要意义,本文针对快速响应制造系统的产品开发过程开展了时间估计与优化研究。
首先,介绍产品开发过程中的一些基本概念,对快速响应制造系统产品开发过程任务及存在的设计迭代进行分析描述,提出了基于元模型方法的快速响应制造系统产品开发过程时间分析流程。对作为重要特征的设计迭代进行重点分析,特别对基于DSM的迭代描述做了详细介绍;为能够更加科学合理的对产品开发过程时间进行估计,引入计算机仿真领域的元模型方法,针对设计活动时间估计问题的特点给出了元模型建模步骤,指出元模型拟合方法和训练数据选取方法是研究的重点。
其次,针对元模型拟合方法开展研究,提出了基于高斯过程元模型的产品设计活动时间估计方法。将常用的元模型方法分为参数方法和非参数方法进行了介绍,指出非参数方法的弊端以及高斯过程元模型在理论上可以取代几种常见的非参数方法;介绍了高斯过程元模型的建模原理,并对协方差函数的设定以及超参数优化方法进行了相应的说明,由于训练数据存在语言型变量是设计活动时间估计问题的自身特点之一,为此引入模糊距离的概念,将语言型变量模糊化后根据其模糊距离对协方差函数进行计算,并针对该问题提出了具体建模步骤;通过实例说明了高斯过程元模型方法在解决设计活动时间估计问题中的良好特性。
第三,针对训练数据选取问题,提出一种基于最优化拉丁超立方设计的数据选取方法。训练数据的选取在很大程度上影响着元模型的预测精度和效率,为配合元模型方法在产品开发过程时间估计中的应用,引入试验设计的概念,以最优化拉丁超立方设计来指导历史数据的选取;考虑正交属性、? p准则以及Kullback–Leibler准则对拉丁超立方设计进行多目标优化;为构造目标函数,找出了Kullback–Leibler准则的理论上下限;在以上研究基础上提出一种改进的ILS算法对LHD进行多目标优化,并将其应用于数据选取中。
第四,针对重叠模式下快速响应制造系统产品开发过程时间评估与优化开展研究。为针对重叠模式下产品开发过程进行建模,在分析已有研究的基础上提出了一种上下游设计活动之间的信息交互策略,提出了适用于该模式的信息交互策略以及各类迭代参数表示方法;假设设计活动时间为常数构建重叠模式下的一般模型,在此基础上考虑时间不确定性再次构建时间分析模型;提出一种基于蚁群算法的优化方法对各设计活动的开始时间进行规划,通过重新安排各设计活动开始时间可有效减少产品开发过程总时间。
Quick Response Manufacturing System (QRMS) based on Quick Response theory is raised to shorten the circle of product development and manufacturing, and met the customers’requirement as quickly as possible. The time analysis of product development process is of great significance for maintaining the system’s quick response capability and promoting progress control and management ability. The thesis focuses on the research of time estimation and optimization for product development process in QRMS.
First, some basic concepts of product development process are introduced. The task of product development process of QRMS and the design iteration problem exists in it are described, and based on meta-model approach, a time estimate program of product development process in QRMS is proposed. The analysis is mainly focused on the problem of design iteration,which is as the important feature…. Especially, depict the iteration description based on DSM in detail. In order to evaluate the time of product development process more scientifically and reasonable, the meta-model approach in computer simulation area is introduced. Meta-modeling procedures are proposed in line with the characteristics of problem of design activity time estimation, and meta-model fitting method and training data selection method are the points that focuses on.
Secondly, in the light of meta-model fitting method, the product design activity time estimation method based on Gaussian Process meta-model is put forward. Divide the common meta-model approaches into parametric method and nonparametric method, and introduce them respectively., present the defects of nonparametric method and Gaussian Process meta-model can replaces several common nonparametric methods theoretically. Introduce the modeling principles of Gaussian Process meta-model and illustrate the covariance function setting and hyper-parameter optimization methods. Since it is one of the properties of design activity time estimation that the training data have linguistic variables, the concept of fuzzy distance is introduced. After linguistic variables fuzzed, covariance function is computed according to its fuzzy distance, and the modeling procedures are proposed. Case study shows the advantages of Gaussian Process meta-model approach in solving design activity time estimation problems.
Thirdly, a data selection method based on optimal Latin Hypercube design is proposed for the problem of training data selection. The estimation accuracy and efficiency are greatly affected by training data selection, therefore, in order to cooperate with the application of meta-model approach in time estimation of product development process, the concept of experiment design is employed and optimal Latin Hypercube design is adopted for guiding the selection of historical data selection; Consider orthographic attributes, ? p criterion and Kullback-Leibler criterion; The theoretical high and low limits of Kullback-Leibler criterion are identified to construct objective function. The improvement is made on ILS algorithm for multi-objective optimization of LHD,
Fourthly, the study is on time estimation and optimization of QRMS product development process in overlapping mode. To build the model for product development process in overlapping mode, the thesis suggested an information interactive strategy between upper and lower design activity based on the existing research along with the information interactive strategy and representation of every kind of iteration parameters appropriate for this mode. Assuming design activity time as the constant to construct the general model in overlapping mode, the time analysis model is reconstructed taking time uncertainty into account. An optimization method based on ant colony optimization is brought forward for setting the starting time of every design activity, and the reschedule of starting time can effectively reduce the overall time of product development process.
首先,介绍产品开发过程中的一些基本概念,对快速响应制造系统产品开发过程任务及存在的设计迭代进行分析描述,提出了基于元模型方法的快速响应制造系统产品开发过程时间分析流程。对作为重要特征的设计迭代进行重点分析,特别对基于DSM的迭代描述做了详细介绍;为能够更加科学合理的对产品开发过程时间进行估计,引入计算机仿真领域的元模型方法,针对设计活动时间估计问题的特点给出了元模型建模步骤,指出元模型拟合方法和训练数据选取方法是研究的重点。
其次,针对元模型拟合方法开展研究,提出了基于高斯过程元模型的产品设计活动时间估计方法。将常用的元模型方法分为参数方法和非参数方法进行了介绍,指出非参数方法的弊端以及高斯过程元模型在理论上可以取代几种常见的非参数方法;介绍了高斯过程元模型的建模原理,并对协方差函数的设定以及超参数优化方法进行了相应的说明,由于训练数据存在语言型变量是设计活动时间估计问题的自身特点之一,为此引入模糊距离的概念,将语言型变量模糊化后根据其模糊距离对协方差函数进行计算,并针对该问题提出了具体建模步骤;通过实例说明了高斯过程元模型方法在解决设计活动时间估计问题中的良好特性。
第三,针对训练数据选取问题,提出一种基于最优化拉丁超立方设计的数据选取方法。训练数据的选取在很大程度上影响着元模型的预测精度和效率,为配合元模型方法在产品开发过程时间估计中的应用,引入试验设计的概念,以最优化拉丁超立方设计来指导历史数据的选取;考虑正交属性、? p准则以及Kullback–Leibler准则对拉丁超立方设计进行多目标优化;为构造目标函数,找出了Kullback–Leibler准则的理论上下限;在以上研究基础上提出一种改进的ILS算法对LHD进行多目标优化,并将其应用于数据选取中。
第四,针对重叠模式下快速响应制造系统产品开发过程时间评估与优化开展研究。为针对重叠模式下产品开发过程进行建模,在分析已有研究的基础上提出了一种上下游设计活动之间的信息交互策略,提出了适用于该模式的信息交互策略以及各类迭代参数表示方法;假设设计活动时间为常数构建重叠模式下的一般模型,在此基础上考虑时间不确定性再次构建时间分析模型;提出一种基于蚁群算法的优化方法对各设计活动的开始时间进行规划,通过重新安排各设计活动开始时间可有效减少产品开发过程总时间。
Quick Response Manufacturing System (QRMS) based on Quick Response theory is raised to shorten the circle of product development and manufacturing, and met the customers’requirement as quickly as possible. The time analysis of product development process is of great significance for maintaining the system’s quick response capability and promoting progress control and management ability. The thesis focuses on the research of time estimation and optimization for product development process in QRMS.
First, some basic concepts of product development process are introduced. The task of product development process of QRMS and the design iteration problem exists in it are described, and based on meta-model approach, a time estimate program of product development process in QRMS is proposed. The analysis is mainly focused on the problem of design iteration,which is as the important feature…. Especially, depict the iteration description based on DSM in detail. In order to evaluate the time of product development process more scientifically and reasonable, the meta-model approach in computer simulation area is introduced. Meta-modeling procedures are proposed in line with the characteristics of problem of design activity time estimation, and meta-model fitting method and training data selection method are the points that focuses on.
Secondly, in the light of meta-model fitting method, the product design activity time estimation method based on Gaussian Process meta-model is put forward. Divide the common meta-model approaches into parametric method and nonparametric method, and introduce them respectively., present the defects of nonparametric method and Gaussian Process meta-model can replaces several common nonparametric methods theoretically. Introduce the modeling principles of Gaussian Process meta-model and illustrate the covariance function setting and hyper-parameter optimization methods. Since it is one of the properties of design activity time estimation that the training data have linguistic variables, the concept of fuzzy distance is introduced. After linguistic variables fuzzed, covariance function is computed according to its fuzzy distance, and the modeling procedures are proposed. Case study shows the advantages of Gaussian Process meta-model approach in solving design activity time estimation problems.
Thirdly, a data selection method based on optimal Latin Hypercube design is proposed for the problem of training data selection. The estimation accuracy and efficiency are greatly affected by training data selection, therefore, in order to cooperate with the application of meta-model approach in time estimation of product development process, the concept of experiment design is employed and optimal Latin Hypercube design is adopted for guiding the selection of historical data selection; Consider orthographic attributes, ? p criterion and Kullback-Leibler criterion; The theoretical high and low limits of Kullback-Leibler criterion are identified to construct objective function. The improvement is made on ILS algorithm for multi-objective optimization of LHD,
Fourthly, the study is on time estimation and optimization of QRMS product development process in overlapping mode. To build the model for product development process in overlapping mode, the thesis suggested an information interactive strategy between upper and lower design activity based on the existing research along with the information interactive strategy and representation of every kind of iteration parameters appropriate for this mode. Assuming design activity time as the constant to construct the general model in overlapping mode, the time analysis model is reconstructed taking time uncertainty into account. An optimization method based on ant colony optimization is brought forward for setting the starting time of every design activity, and the reschedule of starting time can effectively reduce the overall time of product development process.
引文
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