A cost estimation model to support automation decision in assembly systems design

Cost analysis is crucial in the design of assembly systems and the decision on their level of automation (LoA). This paper presents a cost estimation model of assembly system that is used to decide their LoA during the early phase of projects. Based on an extensive literature review, a complete cost model integrating multiple cost drivers is proposed. This model is then exploited to create the objective function of an integer linear programme model utilised to solve the LoA decision problem. The work provides a way to perform cost estimation of assembly systems alternatives and to decide the most appropriate LoA in assembly. The cost estimation model is built with a parametric approach allowing the definition of various optimisation objectives. The proposed integer programme, complement this approach by proposing the suitable constraints set, that describes the LoA decision problem.     

成本动因法与神经网络在生产成本预测中的应用

成本预测是企业成本控制的重要环节,有效的预测方法是进行成本控制的前提。在认真分析企业成本环境的基础上,提出了一种基于成本动因理论,应用人工神经网络进行成本预测的方法。这种方法较好地描述出成本的状况和结构,为工业制造成本的预测提供了决策支持。     

热压釜成型复合材料波纹梁工艺工时估算

成本估算是目前复合材料领域开发研究的关键问题之一,而工艺工时估算又是制造成本估算的核心。本文中建立复合材料制造工艺工时估算模型,以热压釜成型复合材料波纹梁为研究对象进行理论分析和实验研究,给出此估算模型中估算变量和方程参数的确定方法并应用最小二乘法将所得数据进行拟合,其结果与实验结果基本一致。介绍了估算模型中参数随制件曲度变化的修正方法,为实现不同结构设计的工时估算提供指导。     

复合材料结构面向成本的设计方法(DFC)

在DFC概念模型的基础上,将面向成本的设计引入复合材料结构设计当中,建立复合材料结构的面向成本设计的理论框架;在对成本估算模型分类的基础上,针对复合材料面向成本设计过程中各个阶段的特点,选择其相应的成本估算方法。     

A hybrid artificial neural network method with uniform design for structural optimization

This paper presents a new hybrid artificial neural network (ANN) method for structural optimization. The method involves the selection of training datasets for establishing an ANN model by uniform design method, approximation of the objective or constraint functions by the trained ANN model and yields solutions of structural optimization problems using the sequential quadratic programming method (SQP). In the proposed method, the use of the uniform design method can improve the quality of the selected training datasets, leading to a better performance of the ANN model. As a result, the ANN dramatically reduces the number of required trained datasets, and shows a good ability to approximate the objective or constraint functions and then provides an accurate estimation of the optimum solution. It is shown through three numerical examples that the proposed method provides accurate and computationally efficient estimates of the solutions of structural optimization problems.     

发动机装配线关键工位物料动态配送方法

目的 为降低装配车间线边物料配送及库存管理成本,提高配送环节对生产节拍变动的适应性,设计一种针对关键工位重点物料的动态配送方法.方法 首先,采用K-means算法考虑物料价值、包装体积、通用性进行初步分类,结合需求变异系数确定出关键工位重点物料;其次,结合发动机装配线生产特点,设计基于动态配送时间和数量的物料配送方法,并建立包括运输成本和线边库存成本的配送总成本模型;最后,通过Flexsim软件搭建生产物流仿真模型,分别模拟Z车间现有配送方法和所设计方法进行对比验证.结果 实行动态配送后,重点物料的平均库存容量和持有库存成本均得到有效降低,最大降幅分别为23.91％和23.96％.结论 结果表明所提方法能够提高车间物料管理的针对性,降低总配送成本,提升配送系统的柔性化.     

先进复合材料可制造性中的成本估算理论框架

飞行器复合材料构件的可制造性评价是其结构制造工艺方案决策的重要依据,成本是评价体系中的一个重要指标。本文概述了先进复合材料可制造性中的成本概念及组成,应用过程估算方法建立了成本指标的估算理论框架及初步模型。通过对工时估算理论的分析,提出了适合于过程估算方法的工时概念关系式。应用本文所提出的先进复合材料可制造性成本估算理论,能够有效地建立较为实用的可制造性成本评价估算模型。     

基于盲数理论的工程全寿命周期成本估算

借鉴盲数理论,以公路工程为例,研究如何更加精确地估算工程全寿命周期成本。结果表明：基于盲数理论的工程全寿命周期成本估算法全面真实地反映专家估算的区间和可信度,充分地显示了其简洁性和准确性。把参数作为盲数处理,不必关心随机变量的分布问题,匹配了专家判断回答模式的本质特点,包容了未来的不可确知因素,使得准确性得到有效的提高。不足之处是盲数的四则运算阶数增加很快,必须借助计算机程序解决。     

A new artificial neural network-based response surface method for structural reliability analysis

This paper presents a new artificial neural network-(ANN)based response surface method in conjunction with the uniform design method for predicting failure probability of structures. The method involves the selection of training datasets for establishing an ANN model by the uniform design method, approximation of the limit state function by the trained ANN model and estimation of the failure probability using first-order reliability method (FORM). In the proposed method, the use of the uniform design method can improve the quality of the selected training datasets, leading to a better performance of the ANN model. As a result, the ANN dramatically reduces the number of required trained datasets, and shows a good ability to approximate the limit state function and then provides a less rigorous formulation in the context of FORM. Results of three numerical examples involving both structural and non-structural problems indicate that the proposed method provides accurate and computationally efficient estimates of the probability of failure. Compared with the conventional ANN-based response surface method, the proposed method is much more economical to achieve reasonable accuracy when dealing with problems where closed-form failure functions are not available or the estimated failure probability is extremely small. Finally, several important parameters in the proposed method are discussed.     

Parametric cost analysis for web-based e-commerce of layer manufactured objects

Web-based e-commerce of rapid prototyping services is going to be a widely diffused methodology used to compete in a global market. A competitive market imposes a very accurate estimation of prototyping price. Prototype costs depend on many factors, some of which may be easily deduced, while some others consist in a complex function of the geometric model properties and of the specific technology employed to build a physical model. Build time, which affects some components of the prototype's build cost, is a critical factor to deduce. Build time depends not only on the prototype dimensions but also on the complexity of the shape that, in turn, affects the movement of the tool to form the object. A parametric approach to build cost estimation, suited for web-based e-commerce, is presented in this paper. Significant cost driving factors of layer manufactured objects are identified and instruments to evaluate them are proposed. Special attention has been paid to define a parametric approach to build time estimation. The proposed parametric approach analyses the geometrical features, which typically affect the build time of the main layer manufacturing technologies. The method is verified in some test cases related to FDM technology.     

Minimisation of inspection and rework cost in a BLU factory considering imperfect inspection

We address an optimisation problem for minimising the cost of both the inspection and the rework incurred throughout an interconnected inspection–rework system. In order to formulate the relevant cost objective function, assuming imperfect inspection, we make a time-based flow analysis between nodes (or shops), and derive the limiting sizes of flows between nodes and the limiting fraction defective by solving a set of nonlinear balance equations. We provide an enumeration method for determining the optimal frequency of inspection cycles at the end of assembly lines which minimises the relevant cost of inspection and rework.     

基于实例推理的产品包装成本估算研究

快速、有效地估算产品包装成本,可及时响应顾客对产品包装的询价、报价等方面的需求,也可为产品包装设计方案的技术经济评价、成本的降低提供支持。给出了针对产品包装特点的实例检索过程,采用分层实例推理的思路,以及知识引导策略和最相邻近策略相结合的检索方法,提出了利用相似实例的成本估算方法。以汽机旁路产品的包装成本估算为例,验证了方法的可行性及有效性。     

Estimating Military Aircraft Cost Using Least Squares Support Vector Machines

A multi-layer adaptive optimizing parameters algorithm is developed for improving least squares support vector machines (LS-SVM), and a military aircraft life-cycle-cost (LCC) intelligent estimation model is proposed based on the improved LS-SVM. The intelligent cost estimation process is divided into three steps in the model. In the first step, a cost-drive-factor needs to be selected, which is significant for cost estimation. In the second step, military aircraft training samples within costs and cost-drive-factor set are obtained by the LS-SVM. Then the model can be used for new type aircraft cost estimation. Chinese military aircraft costs are estimated in the paper. The results show that the estimuted costs by the new model are closer to the true costs than that of the traditionally used methods.     

Aircraft Combat Survivability Estimation and Synthetic Tradeoff Methods

A new concept is proposed that susceptibility, vulnerability, reliability, maintainability and supportability should be essential factors of aircraft combat survivability. A weight coefficient method and a synthetic method are proposed to estimate aircraft combat survivability based on the essential factors. Considering that it takes cost to enhance aircraft combat survivability, a synthetic tradeoff model between aircraft combat survivability and life cycle cost is built. The aircraft combat survivability estimation methods and synthetic tradeoff with a life cycle cost model will be helpful for aircraft combat survivability design and enhancement.     

不确定环境下复杂机械装配系统设备维修方法

为保障不确定环境下复杂机械装配系统的连续性并降低其维修成本,提出一种以马尔可夫决策理论为基础的设备维修策略动态选择方法。在综合考虑系统运行成本、缓冲库存成本、设备维修成本及停机损失成本的基础上,构建了装配系统可靠性成本模型。该模型以带有中间缓冲区的二级装配系统为研究对象,以设备状态和缓冲库存量为自变量,以可靠性成本为目标函数。分析了装配系统的不同运行状态,利用模拟退火算法和模糊非线性混合整数目标规划对可靠性成本模型求解,制定装配系统最优维修方法。该方法降低了装配系统停机时间,减少了设备维修次数,可为生产线设计和维修计划的制定提供依据。最后,通过算例分析验证了模型的有效性和可行性。     

Research on Affordability Modeling of Aircraft Based on Effectiveness Indexes

With the cost estimation of military aircraft as the research object,this paper aims to study the contradiction between the choice of explanatory variables in index modeling and the maintaining of model validity.It analyzes and establishes a cost estimation modeling concept based on an Effectiveness Index and studies the way to construct Effectiveness Indexes for the sake of cost estimation modeling.Based on a case study,the paper establishes and analyzes the Effectiveness Index-based cost estimation models and DAPCA(Development And Procurement Costs of Aircraft)models developed by the RAND Corparation.The comparison of these models shows that the Effectiveness Index-based cost parameter models not only comprehensively consider the obvious driving parameter indexes of the cost,but reduces the variables of regressive analysis,hence giving the model a higher reliability.     

复合材料结构制造成本估算模型及软件开发

基于制造工艺过程的成本估算模型,采用Delphi 可视化编程语言和SQL server数据库开发工具,开发了复合材料制造成本评估软件。介绍了基于制造工艺过程的成本估算模型的基本特点,重点讨论了工艺时间模型并分析了构件复杂程度对工艺时间的影响。此外,通过引入曲率熵的概念,对前人提出的构件复杂性因子进行了改进,以便更合理地描述构件的复杂度。提出了成本估算软件的总体方案,确定了软件实现流程,并建立了成本数据库管理系统。列举了用该软件对一种复合材料单曲率板的制造成本进行估算的过程。应用所开发的软件对某型飞机的复合材料副翼和金属副翼的制造成本进行了估算,估算结果表明,复合材料副翼由于采用了低成本工艺与整体化的设计理念,其制造成本低于金属副翼。      

工程项目管理中的人工神经网络方法及其应用

概括了神经网络在工程项目管理中的应用,包括风险预测评估、费用估计、绩效预测、项目组织有效性预测、工程事故诊断、索赔争议分析、投标决策、进度费用优化、资源平衡等,总结分析了应用中存在的问题,并对如何开展神经网络方法在我国项目管理中的应用,提出了一些意见和建议.     

快速产品成本评估方法研究

提出了一种快速产品成本评估方法。与目前的基于产品规格与成本间数学关系的成本评估方法不同，这种方法应用基于案例的推理(case-based reasoning，CBR)来对产品配置、资源需求和成本之间的成本评估关系进行建模。这种方法既可以应用数字参数又可以应用非数字参数，另外这种方法不需要大量的历史数据就能很好地被应用。这种快速产品成本评估方法以较少的时间和成本有效地支持企业对顾客的快速反应，从而提高了企业获得顾客订单的能力。     

Quantification of ternary mixtures of heavy metal cations from metallochromic absorbance spectra using neural network inversion

A new method based on artificial neural networks (ANN) for the processing of spectrophotometric data is proposed and illustrated on the example of the simultaneous quantification of ternary mixtures of zinc, cadmium, and mercury cations in aqueous solutions. Three types of commercially available metallochromic indicators were used as a simple model setup to create spectral data analogous to those normally received from an optical sensor array. In conventional ANN training methods for chemical sensors based on spectrophotometric data, a calibration is established by mathematically correlating the measured optical signal as network input with the concentration of the calibration sample as network output. In several situations, however, especially when dealing with mixed sample solutions, the relationship between a measured absorption spectrum and the corresponding ion concentrations is ambiguous, resulting in an "ill-posed problem". On the other hand, if the training direction is reversed by correlating known sample concentrations with measured optical signals, the relationship becomes reasonable for the ANN to obtain its structure. The proposed model illustrated in this paper is based on a more reasonable direct mapping and estimation by artificial neural network inversion (ANNI). In the training step, sample mixtures of known concentrations are optically measured to construct networks correlating the input data (ion concentrations) and the output data (absorption spectra). In the estimation step, the ion concentrations of unknown samples are estimated using the constructed ANN. The measured spectra of the unknown samples are fed to the output layer, and the appropriate input concentrations are determined by ANNI. When training the ANN system with 143 ternary mixtures of Zn2+, Cd2+, and Hg2+ in a concentration range from 1 to 100 microM, root-mean-square errors of prediction (RMSEP) of 0.45 (Zn2+), 0.96 (Cd2+), and 0.32 microM (Hg2+) were observed for the estimation of concentrations in 30 test samples, using the ANNI procedure. This newly proposed model, which involves the construction of an ANN based on direct mapping and estimation by ANNI, opens up one way to overcome the limitations of nonselective sensors, allowing the use of more easily accessible semiselective receptors to realize smart chemical sensing systems.