改进灰色关联分析在铸造型砂品质评价中的应用

提出了铸造型砂性能评价的灰色关联分析模型。针对传统灰色关联分析模型权重分配和确定存在的问题,采用加权灰色关联度方法加以改进,用权重的形式体现各评价指标对评价目标的影响程度,采用距离分析法确定权重的大小,避免主观确定方法带来的影响和干扰,使评价更符合实际,结果更加客观、科学。     

产品修改方案评价方法研究及应用

针对产品修改方案的多样性,提出一种基于熵权和层次分析法的指标权重确定方法,用熵权确定指标的客观权重,用层次分析法计算指标的主观权重,从而使评价指标权重度的确定更加可靠、合理。应用多属性关联函数对评价指标进行分类量化,根据关联函数的关联度评价修改方案的优劣。通过在某企业缝制设备新产品修改方案中的应用,验证了所提方法的有效性。     

基于灰色关联度分析的动态性能递阶综合评价

针对机床可靠性评价较多依赖主观判断的问题,文章提出了一种基于灰色关联度分析的动态递阶评价综合模型的评价方法,从精度、效率、可靠性和能耗4个方面建立数控机床关键性能指标体系。该方法以关联系数表征各时期指标与最优指标之间的关联度,集成关联度和权重信息以反映被评价对象与理想对象的接近程度。最后对数控机床性能测试历史数据进行实例分析。分析结果表明,基于灰色关联度分析的动态性能递阶综合评价方法可以有效的对机床综合性能做出科学的评价,对于其它相似产品的性能评价具有一定的指导意义。     

基于灰色关联度分析的数控机床性能模糊综合评判

如何从众多的数控机床供应商中选择适合自己企业的数控机床已成为广大企业或工厂关注的焦点。以数控机床的选择为研究对象,提出一种基于灰色关联度分析的数控机床选择的性能指标评价方案,从数控机床的精度指标、加工性能指标、可靠性指标等5个方面建立数控机床性能指标评价体系,利用改进的灰色关联分析法确定各性能指标的权重,采用模糊综合评判法对数控机床的性能进行评价并得出性能评估结果,以某供应商提供的某种型号的数控机床为例进行计算,其结果可以为企业或者工厂选择适合的的数控机床提供一套可行性参考方案,也可为机床性能的改进或提高提供可靠依据。     

基于R-KANO与G-TOPSIS法的产品设计方案多目标决策方法

针对产品设计方案多目标决策过程中存在的主观性与模糊性问题,进一步提高用户对企业产品的综合满意度,提出一种结合粗糙集与卡诺模型(R-KANO)、灰色关联分析与逼近理想解排序法(G-TOPSIS)的产品设计方案决策方法。首先,通过专家及用户问卷调查确定产品初始评价指标,运用公信度评测对初始指标进行筛选,确定最终评价指标集;然后,应用粗糙集理论计算评价指标初始权重,考虑用户需求偏好采用KANO模型对评价指标权重进行修正;最后,通过灰色关联分析法对设计方案与目标需求之间的形状关联度进行分析,采用TOPSIS法对设计方案与目标需求之间的位置匹配度进行分析,通过融入上述指标权重并计算重构的相对贴近度实现多目标决策要求下产品创新设计方案的优选。以某新型装备产品评价设计为例,验证了方法的有效性。研究结果表明,该方法能有效提高设计方案优选的客观性,具有一定指导作用。     

基于灰色多层次关联度的智慧型制造系统绩效动态评价

针对智慧型制造系统绩效评价问题,研究基于灰色关联度的动态评价模型和方法。首先,以分析智能制造过程动态因素为切入点,研究制造过程影响要素间的复杂性关系,确立了智慧型制造系统绩效评价指标体系,建立了基于灰色多层次关联法(Gray Multi-hierarchal Correlation Degree,GMCD)的制造系统绩效综合动态评价模型,在评价模型中采用基于层次分析法-熵权法(AHP-Entroy)的综合赋权法确定最优指标权重,并将其应用于智慧型制造系统绩效的动态评价研究中。研究表明,基于GMCD的智慧型制造系统绩效动态评价方法具有更高的准确性和实用性。     

基于典型相关分析和灰色关联分析的电火花小孔加工参数优化

为改善电火花小孔加工效果，采用典型相关分析法分析相关性和利用灰色关联理论优化参数组合的方法，选取直径0.7 mm的黄铜电极丝对304不锈钢板进行打孔实验。基于正交试验数据，分析了不同参数组合与工艺指标之间的相关性，确定了放电脉冲、放电休止、电流峰值、基准电压和极间电容等参数与加工时间、电极损耗、孔径三个工艺指标之间的关系以及各工艺指标的权重。采用灰色关联度值表示综合质量评价标准，运用均值分析法确定了最佳工艺参数组合。结果表明：相较于优化前，电极损耗减少23.10%，加工时间缩短37.50%，孔径减小1.10%。     

基于灰色加权关联度的航空运输企业能效评价

对航空运输企业进行能效分析与评价,挖掘节能潜力和机会,是保障航空运输企业开展节能优化、提高能源效率有效性的关键内容。通过对航空运输企业能源效率测度指标及影响因素的分析,采取定性评价与定量分析相结合的原则,从节能管理、能源系统及环境系统3个方面建立了航空运输企业能效综合评价指标体系。采取层次分析法与熵值法相结合的方式,确定各指标组合权重,建立基于灰色加权关联度的综合评价方法,以量化的方法分析和评价航空运输企业能源效率发展趋势。实例分析表明:对航空运输企业能效的综合评价较为客观的反映了企业能效发展的真实状况,基于灰色加权关联度的综合评价方法对于多目标决问题具有简单、科学、实用性强的特点。     

基于灰色加权关联度的航空运输企业能效评价（英文）

对航空运输企业进行能效分析与评价,挖掘节能潜力和机会,是保障航空运输企业开展节能优化、提高能源效率有效性的关键内容。通过对航空运输企业能源效率测度指标及影响因素的分析,采取定性评价与定量分析相结合的原则,从节能管理、能源系统及环境系统3个方面建立了航空运输企业能效综合评价指标体系。采取层次分析法与熵值法相结合的方式,确定各指标组合权重,建立基于灰色加权关联度的综合评价方法,以量化的方法分析和评价航空运输企业能源效率发展趋势。实例分析表明:对航空运输企业能效的综合评价较为客观的反映了企业能效发展的真实状况,基于灰色加权关联度的综合评价方法对于多目标决问题具有简单、科学、实用性强的特点。     

基于灰色关联分析的GH2132线材高精度切削参数优化

目的 通过无心车床车削去除GH2132线材的表面缺陷,分析无心车床加工参数对线材表面粗糙度、尺寸误差和表面显微硬度的响应关系,并建立GH2132线材表面灰色关联度多目标优化模型,确定可行工艺参数域。方法 采用响应曲面中心复合设计,测量车削后GH2132线材的表面粗糙度、尺寸误差和表面显微硬度;利用响应曲面法(Response Surface Method,RSM)分别建立表面粗糙度、尺寸误差和表面显微硬度的单目标预测模型,确定单目标优化最优工艺参数组;基于灰色关联分析(Grey Correlation Analysis,GRA)理论,以表面粗糙度、尺寸误差和表面显微硬度为优化指标进行降维处理,构建车削工艺参数与灰色关联度的二阶回归预测模型;绘制车削工艺参数与灰色关联度值的等值线图,确定可行工艺参数域。结果 对建立的表面粗糙度、尺寸误差和表面显微硬度的单目标预测模型进行方差分析,显著度均小于0.000 1。得到了最小表面粗糙度工艺参数组,切削速度n=373.919 r/min,进给速度vf =0.475 m/min。得到了最小尺寸误差工艺参数组,n=375.636 r/min,vf =0.596 m/min。得到了最大表面显微硬度工艺参数组,n=337 r/min,vf = 0.903 m/min。对于灰色关联度多目标预测模型,误差范围为0.13%~9.4%,确定的可行工艺参数域对应的最小灰色关联度值为0.544 37。结论 基于灰色关联分析的多目标预测模型的准确度较高,主轴转速n对多目标的响应程度大于进给速度vf。通过确定可行工艺参数域,为GH2132线材去除表面缺陷提供工程参考。     

The use of the orthogonal array with grey relational analysis to optimize the electrical discharge machining process with multiple performance characteristics

In this paper a new approach for the optimization of the electrical discharge machining (EDM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. A grey relational grade obtained from the grey relational analysis is used to solve the EDM process with the multiple performance characteristics. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters, namely workpiece polarity, pulse on time, duty factor, open discharge voltage, discharge current, and dielectric fluid are optimized with considerations of multiple performance characteristics including material removal rate, surface roughness, and electrode wear ratio. Experimental results have shown that machining performance in the EDM process can be improved effectively through this approach.     

Optimization of green sand mould system using Taguchi based grey relational analysis

The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting defects. In the present research work, the effect of process parameters such as AFS grain fineness number, water, molasses, bentonite, fly ash, and ramming, and their levels on the resultant mould properties were investigated and optimized using Taguchi based grey relational analysis. The Taguchi L18 orthogonal array and analysis of variance(ANOVA) were used. The quality characteristics viz., green compression strength, permeability, bulk density, mould hardness and shatter index of green sand mould were optimized using grey relational grade, based on the experiments designed using Taguchi's Design of Experiments. ANOVA analysis indicated that water content is the most influential parameter followed by bentonite, and degree of ramming that contributes to the quality characteristics. The results are confirmed by calculating confidence intervals, which lies within the interval limits. Finally, microstructure observations and X-ray diffraction analysis have been performed for the optimal sand parametric combination. Results show that presence of maximum amount of SiO_2, which might be the reason for enhancement of the physical properties of the sand.     

Optimization of back bead geometry in the PMAG-TIG twin arc hybrid root welding process using grey based Taguchi method

This study investigated multi-response optimization of the pulse metal active gas-tungsten inert gas( PMAG-TIG) twin arc hybrid root welding process for an optimal parametric combination to yield favorable back bead geometry of welded joints using grey relational analysis and Taguchi method.Eighteen experimental runs based on an orthogonal array following the Taguchi method were performed to derive objective functions to be optimized within the experimental domain.The objective functions were selected in relation to parameters of PMAG-TIG twin arc root welding back bead geometry: back bead width to root reinforcement ratio and deposited metal height.The Taguchi approach was followed by grey relational analysis to solve the multi-response optimization problem.The significance of factors on overall quality characteristics of the weld joint was also evaluated quantitatively using analysis of variance.Optimal results were verified through additional experiments,and showed to feasibility of applying grey relation analysis in combination with Taguchi technique for continuous improvement of product quality in the manufacturing industry.     

Optimising multiple qualities of Nd:YAG laser welding onto magnesium alloy via grey relational analysis

Abstract

This work evaluates multiple quality optimisation of Nd:YAG laser welding onto magnesium alloy via grey relational analysis. The effectiveness of the grey relational grade lies in quantifying and judging the performance obtained using various combinations of laser welding parameters. The parameters are shielding gas, laser energy, travelling speed of workpiece, point at which the laser is focused, pulse frequency, and pulse shape in this work. Moreover, 18 combinations of these six essential welding parameters were set following Taguchi's method to evaluate the integrated performance. The welding parameters that govern the laser beam in thin plate butt welding were evaluated by measuring the ultimate tension stress, and both the depth and the width along the welding path. This integrated performance was then quantified and judged via grey relational analysis to obtain an optimised set-up for laser welding. The verifying test was proved to optimise the ultimate tension stress, depth and width along the welding path from 67·0 MPa, 0·50 mm and 0·77 mm to 142·3 MPa, 0·79 mm and 0·79 mm, respectively.     

工业水腐蚀因素的灰关联分析方法

应用灰关联分析原理及方法讨论了工业水质与腐蚀性之间的关系.根据灰关联度的计算,找出工业水中影响腐蚀的主要因素,并据此提出防腐措施,分析结果与实际情况较为吻合     

基于正交试验和灰色系统理论的拼焊板前纵梁成形优化

影响拼焊板冲压成形的工艺参数较多,难以精确建立工艺参数与成形质量之间的关系。以压边力、拉延筋高度、凸筋圆角半径、凹筋圆角半径为自变量,进行四因素四水平正交试验,模拟拼焊板前纵梁拉延成形过程,获得最大减薄率和最大焊缝移动量的数据。利用灰色系统理论,分别计算成形工艺参数对单目标函数的关联系数和多目标函数的关联度,将多目标转换为以关联度为目标的单目标。进一步计算各成形工艺参数的平均关联度,将优化的压边力、拉延筋截面几何参数进行有限元模拟验证,指导设计、试模,成形的质量得到明显提高。     

大型灰铸铁皮带轮铸造工艺设计

介绍了大型灰铸铁皮带轮的铸造工艺设计.铸件质量约1.82 t,材料牌号为HT250,为了利用石墨化膨胀的自补缩作用,铸件采用刚度较高的呋喃树脂砂型生产.长期生产实践表明,工艺出品率达到90％,铸件质量符合要求.     

金属材料腐蚀形貌图像与实海挂片数据的相关性研究

采用图像扫描方法获取碳钢、低合金钢实海挂片的腐蚀形貌图像并进行图像分析;用灰色关联及典型相关技术分析了试片扫描灰度值分布与单位平均腐蚀失重及局部腐蚀平均深度的关系;用神经网络理论建立了扫描灰度值分布与试片局部腐蚀平均深度间的关系模型以及扫描灰度值典型加权与试片单位面积平均腐蚀失重间的关系模型。     

基于灰关联分析的热误差测点优化

针对影响机床热误差建模的机床温度场分布问题,提出了优化热关键点的新方法.借助于灰色系统理论的关联度分析方法,根据现场测得的统计数据序列,建立了灰关联分析模型,通过计算布置于机床上各个温度布点的温度传感器的温度采样序列值同机床定位误差之间的绝对灰色关联度值,最终从32个温度测点当中选择了4个点用于建立热误差补偿模型.最后基于四个测温关键点建模对Z轴的定位误差进行了补偿实验,结果证明补偿效果较好,所提出的热误差测点优化研究可以有效提高热误差模型的鲁棒性.     

Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling

This paper investigates optimization design of the cutting parameters for rough cutting processes in high-speed end milling on SKD61 tool steel. The major characteristics indexes for performance selected to evaluate the processes are tool life and metal removal rate, and the corresponding cutting parameters are milling type, spindle speed, feed per tooth, radial depth of cut, and axial depth of cut. In this study, the process is intrinsically with multiple performance indexes so that grey relational analysis that uses grey relational grade as performance index is specially adopted to determine the optimal combination of cutting parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively described. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of cutting parameters. Hence, this confirms that the proposed approach in this study can be an useful tool to improve the cutting performance of rough cutting processes in high-speed end milling process.