基于性能分析的装配站生产状态快速配置方法

为了支持装配生产作业中市场需求、生产率和资源利用率的协调控制,保证企业的高效、精益生产,提出了一种基于性能分析的装配站生产状态快速配置方法。该方法首先构建支持性能分析的装配站作业网络图,实现在制品资源与可重用资源双重约束下的作业性能分析;然后,考虑闲置时间和成本浪费两类指标,给出装配站最优生产状态评价的多目标函数,并探讨问题求解的解空间特性;采用在制品控制和随机领域两个改进策略,建立生产状态快速配置的粒子群算法。最后,采用某型飞机机翼装配站为实例,验证了方法的有效性。     

Facial configuration and BMI based personalized face and upper body modeling for customer-oriented wearable product design

To realize truly customer-oriented wearable products, individual users’ unique characteristics and features should be properly captured and represented. This research focuses on an efficient methodology to generate low polygonal virtual human face models, which overcome the limitation of existing high polygonal models. To determine individuals’ characteristics in the conceptual design stage of wearable products, a computerized and personalized 3D face model should be efficiently generated and be able to interact with wearable products. This research formulates a computerized 3D face via a 3D feature-based transformation. The developed algorithm is able to concisely and efficiently create a 3D face by using frontal and lateral pictures of users. The performance of this algorithm is well adapted both to typical PCs and to mobile devices. The generated virtual face models can serve as communication media in a multi-device based collaborative design environment. Through experiments, the validity of the proposed modeling method is considerably acceptable with respect to the quality of the similarity between 3D faces and individual pictures. Finally, this paper discusses how the developed personalized face modeling can be successfully utilized for customer-oriented wearable product design by showing compatible matching of a hairstyle product as a user study.     

Rough set and PSO-based ANFIS approaches to modeling customer satisfaction for affective product design

Facing fierce competition in marketplaces, companies try to determine the optimal settings of design attribute of new products from which the best customer satisfaction can be obtained. To determine the settings, customer satisfaction models relating affective responses of customers to design attributes have to be first developed. Adaptive neuro-fuzzy inference systems (ANFIS) was attempted in previous research and shown to be an effective approach to address the fuzziness of survey data and nonlinearity in modeling customer satisfaction for affective design. However, ANFIS is incapable of modeling the relationships that involve a number of inputs which may cause the failure of the training process of ANFIS and lead to the ‘out of memory’ error. To overcome the limitation, in this paper, rough set (RS) and particle swarm optimization (PSO) based-ANFIS approaches are proposed to model customer satisfaction for affective design and further improve the modeling accuracy. In the approaches, the RS theory is adopted to extract significant design attributes as the inputs of ANFIS and PSO is employed to determine the parameter settings of an ANFIS from which explicit customer satisfaction models with better modeling accuracy can be generated. A case study of affective design of mobile phones is used to illustrate the proposed approaches. The modeling results based on the proposed approaches are compared with those based on ANFIS, fuzzy least-squares regression (FLSR), fuzzy regression (FR), and genetic programming-based fuzzy regression (GP-FR). Results of the training and validation tests show that the proposed approaches perform better than the others in terms of training and validation errors.     

基于条件属性依赖度的配置产品装配时间估算

准确地估算配置产品装配时间是确定产品销售报价和交货期的基础,是在大规模定制生产环境中取得竞争优势的关键。应用粗糙集的方法对企业现有产品的配置进行分析,定义了一个时间系数,并用回归分析的方法建立起该系数与装配时间的数学关系模型。此模型可通过新产品的时间系数对其装配时间进行估算。此外,以某企业的变压器装配时间为例对所提出的估算模型进行了验证,并对其误差作出了分析。     

基于UML与CCSP的产品配置方法

为了有效开发易维护可重用的产品配置模型以及实现配置问题的快速求解,提出了结合面向对象建模技术与条件约束满足问题理论的产品配置方法。给出了条件约束满足问题理论模型;提出了基于统一建模语言和条件约束满足问题的产品配置建模与求解方法;通过定义统一建模语言表示的产品配置概念模型与条件约束满足问题之间的映射规则集,建立了基于条件约束满足问题的产品配置模型。以某可配置医用监测器为应用实例,阐述了所提方法应用于配置模型构建与求解的可行性和有效性。     

Study on the production planning of apparel products: Determining optimal production times and quantities

Three types of aggregate production planning methods for the apparel industry are proposed, and the advantages and disadvantages of each are discussed. The methods respectively allow:

1. (I) Changing a production model seasonally and according to inventory requirements.

2. (II) Changing a production model seasonally and follow the actual demands.

3. (III) Maintaining the same production model for several seasons running and production for inventory.

Planning with method II is generally considered appropriate for the apparel industry. However, in this study, the profit by simulations of using method I , where the production run is determined maximization of profit, which is found to be as satisfactory as that by using method II.

And planning method III enables firms to obtain a profit equal to or higher than that by the others when the product is popular with consumers. This method is particularly useful, there are frequent changes in the product line.     

基于蚁群算法的产品配置方法及其应用

为了更有效地解决产品配置优化问题,建立了基于相关矩阵的多目标产品优化配置模型,运用了改进的层次分析法计算各目标权重,提出了一种基于蚁群算法的产品配置求解方法,并在C#环境下进行了仿真实验,利用多次实验优化了算法参数。实验结果表明,该方法能有效解决产品配置求解问题,具有一定的理论参考价值和实际意义。     

基于均匀尺度不变局部三元模式的背景建模及其在Intel HD显卡上的并行实现

针对尺度不变局部三元模式(SILTP)背景建模算法复杂度较高、计算速度较慢,不利于高速视频处理的问题,提出了一种新的均匀尺度不变局部三元模式(USILTP)背景建模并行算法。首先,通过规范SILTP编码的跳变次数得到USILTP纹理特征,实现了SILTP特征降维;其次,设计并实现基于英特尔核芯显卡(Intel HD)及开放式计算语言(OpenCL)的USILTP背景建模并行算法,进一步加速了USILTP背景建模算法;最后,通过融合多颜色通道模型结果,优化了USILTP背景建模算法的前景效果。实验结果表明,在Intel HD 4600上处理320×240分辨率的视频,该算法将速度提升至98 frame/s,比SILTP背景建模算法快4倍;在前景检测方面,该算法在背景公开数据库上的性能比SILTP背景建模算法提升了2.1%。     

基于加权灰关联的产品配置相似实例检索算法研究*

针对传统配置实例检索算法极少考虑实例属性间的关联性,结合欧几里得距离,将灰色关联理论应用到产品配置实例检索中,建立产品配置实例检索的灰色关联理论模型。利用层次分析法和熵技术来确定实例属性的权重值,避免了指标权重确定的主观性,增加检索结果的分辨性。最后通过一实例,证明该方法具有较好的分辨性。     

化工企业生产计划图形建模优化系统开发及其应用

为优化化工企业生产计划,本文建立了化工过程生产计划优化的混合整数非线性规划(mixed integer nonlinear program- ming)模型,并给出相应的迭代求解算法,实际应用表明该算法可以有效的求解模型。应用该MINLP模型和求解算法,在石化企业生产计划图形建模优化系统(graphic I/O petrochemical industry modeling system,GIOPIMS)已经成功开发和实施的基础上,针对化工企业的特点,重新开发出适合化工企业使用的生产计划图形建模优化系统(graphic I/O chemical industry modeling system,GIOCIMS)。GIOCIMS的实施表明,该系统在化工企业中间产品外购或自产,中间产品外销或深加工,工艺路线选择和装置负荷等优化方面发挥了重要作用,获得显著的经济效益?。     

Granular modeling and computing approaches for intelligent analysis of non-geometric data

Data analysis techniques have been traditionally conceived to cope with data described in terms of numeric vectors. The reason behind this fact is that numeric vectors have a well-defined and clear geometric interpretation, which facilitates the analysis from the mathematical viewpoint. However, the state-of-the-art research on current topics of fundamental importance, such as smart grids, networks of dynamical systems, biochemical and biophysical systems, intelligent trading systems, multimedia content-based retrieval systems, and social networks analysis, deal with structured and non-conventional information characterizing the data, providing richer and hence more complex patterns to be analyzed. As a consequence, representing patterns by complex (relational) structures and defining suitable, usually non-metric, dissimilarity measures is becoming a consolidated practice in related fields. However, as the data sources become more complex, the capability of judging over the data quality (or reliability) and related interpretability issues can be seriously compromised. For this purpose, automated methods able to synthesize relevant information, and at the same time rigorously describe the uncertainty in the available datasets, are very important: information granulation is the key aspect in the analysis of complex data. In this paper, we discuss our general viewpoint on the adoption of information granulation techniques in the general context of soft computing and pattern recognition, conceived as a fundamental approach towards the challenging problem of automatic modeling of complex systems. We focus on the specific setting of processing the so-called non-geometric data, which diverges significantly from what has been done so far in the related literature. We highlight the motivations, the founding concepts, and finally we provide the high-level conceptualization of the proposed data analysis framework.     

Solution of fuzzy integrated production and marketing planning based on extension principle

The integration of production and marketing planning is crucial in practice for increasing a firm’s profit. However, the conventional inventory models determine the selling price and demand quantity for a retailer’s maximal profit with exactly known parameters. When the demand quantity, unit cost, and production rate are represented as fuzzy numbers, the profit calculated from the model should be fuzzy as well. Unlike previous studies, this paper develops a solution method to find the fuzzy profit of the integrated production and marketing planning problem when the demand quantity, unit cost, and production rate are represented as fuzzy numbers. Based on Zadeh’s extension principle, we transform the problem into a pair of two-level mathematical programming models to calculate the lower bound and upper bound of the fuzzy profit. According to the duality theorem of geometric programming technique, the two-level mathematical program is transformed into the one-level conventional geometric program to solve. At a specific α-level, we can derive the global optimum solutions for the lower and upper bounds of the fuzzy profit by applying well-developed theories of geometric programming. Examples are given to illustrate the whole idea proposed in this paper.     

产品质量与生产过程的集成控制: 双率采样数据方法

本文在集成控制的框架下研究了工业过程中产品质量和生产过程的实时一体控制问题.首先,基于双速率采样数据提出了产品质量和生产过程的集成控制方案.然后,把控制器设计问题归结为求解一组非线性矩阵不定式,进而提出基于同伦算法的控制器设计方法.最后,通过数值仿真说明所提方法的有效.     

A nonlinear model for optimizing the performance of a multi‐product production line

This paper examines the measures of performance and in particular addresses the throughput of an automated production line processing multiple products. The line is composed of a sequence of workstations connected in series with finite buffers in between. We explore the effects of buffer size on attenuating the impact of line blocking and starvation that can cause a reduction in the output. Such effects are analyzed through a nonlinear mathematical programming model and the implications are examined. The aim of the model is to achieve the best performance subject to available workstation capacity without overexpenditure on buffer size. Single and multi‐objective optimizations are carried out in the paper. A numerical example of a production line with a given configuration of workstations; workstation capacity; and job mix is presented to demonstrate the model and its application. A discussion of the impact of buffer size on maximum throughput is also provided. The paper is concluded with a discussion on the decision‐making implications.     

目标造型意象约束的异质产品基因选择与优化方法研究

为了能够在目标造型意象约束下有效利用与目标产品有本质属性差异的异族产品的特征,提出异质产品概念,并建立了基于目标造型意象约束的异质产品基因选择与优化模型。用语义差异法获取目标造型意象,利用数量化一类理论确定异质产品基因,基于交互式遗传算法构建异质产品基因优化辅助系统,最终实现异质产品基因与目标产品基因的融合。通过手机壳造型设计验证了本方法的可行性。     

Feature extraction using rough set theory and genetic algorithms—an application for the simplification of product quality evaluation

Feature extraction is an important aspect in data mining and knowledge discovery. In this paper an integrated feature extraction approach, which is based on rough set theory and genetic algorithms (GAs), is proposed. Based on this approach, a prototype feature extraction system has been established and illustrated in an application for the simplification of product quality evaluation. The prototype system successfully integrates the capability of rough set theory in handling uncertainty with a robust search engine, which is based on a GA. The results show that it can remarkably reduce the cost and time consumed on product quality evaluation without compromising the overall specifications of the acceptance tests.     

基于多源数据的铝土矿浮选生产指标集成建模方法

在长流程浮选过程中,生产指标难以在线检测,造成操作不及时,影响系统的稳定运行.本文提出了一种基于多源数据的铝土矿浮选过程生产指标集成建模方法.首先结合浮选机理和现场工人经验,分析影响和反映生产指标的多源数据(生产数据和泡沫图像特征数据);然后分别建立各生产指标预测子模型和同步误差补偿子模型;最后采用信息熵和智能协调策略分别构建精矿品位和尾矿品位的集成预测模型.工业验证和工况分析表明,本文集成建模方法具有良好的预测性能和较强的泛化性,为基于生产指标的浮选过程操作参数控制和全流程优化奠定基础.     

多视图下的生产线建模与仿真

在多品种、小批量的生产环境中,企业不仅需要查看实体生产线,同时需要从不同的产品维度监控和管理生产线的运行状况。应用领域驱动设计方法对实体生产线建立完整的领域对象,将每个工件品种的加工流程定义为一个虚拟的生产线视图,为虚拟生产环境建立领域对象,并将其映射到软件系统中。基于MVC模式设计仿真系统,以多个视图对生产线进行展示。给出了仿真系统的原型实现,验证了仿真系统设计的可行性。生产线的管理者不仅可以通过实体生产线视图查看设备的工作状态,同时还可以通过虚拟生产线视图直观地查看每个品种的加工流程。     

基于BP算法的IFPN参数优化方法

针对直觉模糊Petri 网(IFPN) 模型自学习能力差的缺陷, 将神经网络中的BP 误差反传算法引入IFPN 模型 的参数寻优过程, 提出一种基于此的参数优化方法. 该算法通过建立变迁点燃和直觉模糊推理的近似连续函数, 摆脱 了参数对经验的依赖, 更加符合实际系统的需求, 同时使得IFPN 具有较强的泛化能力和自适应功能, 推理结果更加 准确可信. 最后通过典型实例验证了该参数优化方法的有效性和优越性.

     

一类混合生产过程的混杂Petri 网建模与调度

针对混合整数线性规划方法在解决混合生产过程调度中存在的问题,提出一种混合间歇/连续生产过程的时间约束混杂Petri网模型,该模型能够对间歇操作时间可变和连续速率可变的混合生产过程进行有效描述.结合模型行为演变和遗传算法提出一种新的混合生产过程调度方法.实验结果表明了所提出方法的有效性.