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1.
企业中的数据存在于各个异构的传统数据库系统中,数据仓库是企业整合数据的一种有效途径。数据仓库使得企业的信息变得易于获取并且为企业决策提供可靠依据。然而建设一个企业级数据仓库是一项巨大的工程。根据数据仓库的特点和功能以及软件设计的模块化思想,提出一种三层数据模型结构,即面向企业全局视图的逻辑层数据模型(LDM)、面向数据处理的ETL数据模型和面向前台展示的分析层数据模型(ADM)并在银行系统中予以实现。  相似文献   

2.
为有效对船舶企业产品质量进行控制和分析,针对造船企业质量信息特点,提出了基于过程质量数据仓库的多维数据模型,建立了面向主题的船舶企业质量数据仓库。并通过对OLAP数据源中抽取的数据进行转换,构建了面向产品实现全过程的企业主题数据模型,为船舶企业质量管理体系的稳步改进提供了技术保证。通过在某船舶企业的实际应用,验证了该模型和方法的合理性和有效性。  相似文献   

3.
网络制造 《计算机》2001,(15):20-20
数据仓库是一种管理技术,它将分 布在企业网络中不同站点的商业数据集成到一起,为决策者提供各种类型的、有效的数据分析,起到决策支持的作用。数据仓库为决策支持系统开辟了一种新途径。随着数据仓库的广泛应用,基于数据仓库的决策支持系统应运而生。 数据仓库的使用分三大类:1、提高数据分析的速度和灵活性;2、为访问和综合大量数据提供集成基础;3、促进或再创造商业过程。利用数据仓库建立的应用系统,在激烈的市场竞争中,为企业领导者的决策支持起到了明显的作用。这种应用系统是一种新形式的决策支持系统。下面给出NCR公…  相似文献   

4.
电信网络管理的数据仓库解决方案   总被引:4,自引:0,他引:4  
数据仓库技术是近几年迅速发展起来的一种技术。国际上许多电信运营企业都积极关注数据仓库技术在电信运营部门和网络操作上的应用。对数据仓库技术在电信管理网(TMN)中的应用作了一些探讨,并提出了一种具体的应用方案。  相似文献   

5.
数据仓库技术是近几年迅速发展起来的一种技术,国际上许多电信运营企业都积极关注于数据仓库技术在电信运营部门和网络操作上的应用。本文对数据仓库技术在电信管理网(TMN)中的应用作了一些探讨,并提出了一种具体的应用方案。  相似文献   

6.
面向企业的混合型分布式数据仓库的数据集成方法   总被引:1,自引:0,他引:1  
吴彭年  邵贝恩 《计算机应用》2004,24(Z2):236-238
混合型分布式数据仓库是一种适合集团型企业特点的数据仓库解决方案,但它数据分层存储的结构使得总部决策支持系统访问子公司细节数据发生困难.文章分析了混合型分布式数据仓库的体系结构,结合JW-DSS项目提出了一种借助远程视图从总部决策支持系统直接访问局部数据仓库细节数据的方法,最后还提出了一种通过分层映射数据解决连接远程视图导致总部数据仓库访问效率降低的方法.  相似文献   

7.
高性能数据仓库平台构建的研究   总被引:2,自引:0,他引:2  
程平  黄仁  陈艳  柳刚 《计算机工程与设计》2006,27(12):2189-2191
随着数据仓库逐渐成为企业决策支持的重要技术手段,提高数据仓库的综合性能问题日益成为人们重视与关注的焦点之一。在描述形成高性能数据仓库平台及高性能数据仓库环境的基本观点和技术的基础上,给出了建立高性能数据仓库平台的几个关键要素,提出了一种基于可扩展的数据集市的数据仓库系统结构。  相似文献   

8.
企业中的数据存在于各个异构的传统数据库系统中,数据仓库是企业整合数据的一种有效途径.数据仓库使得企业的信息变得易于获取,并且可为企业决策提供可靠依据.本文概述了基于数据仓库技术的客户信用管理系统的设计思想、主要功能、实现平台及其主要技术实现方法和手段.  相似文献   

9.
数据仓库多维模式的变化会影响OLAP查询结果的正确性,因此有必要对多维模式的历史变化进行维护。文章给出了时态数据仓库多维模型的一种形式定义,并在此定义的基础上,设计并实现了具有时态特性的煤矿企业产量数据仓库。  相似文献   

10.
数据仓库已发展成为一种联合仓库,它由知识库和一系列的过程和服务组成,以支持企业知识的创建、提炼、检索、发布和演变.描述了异构数据仓库环境下的企业知识管理体系结构,并对数据仓库中的知识管理问题进行了论述.  相似文献   

11.
A number of business requirements (e.g. compliance with regulatory and legal provisions, diffusion of global standards, supply chain integration) are forcing consumer goods manufacturers to increase their efforts to provide product data (e.g. product identifiers, dimensions) at business-to-business interfaces timely and accurately. The quality of such data is a critical success factor for efficient and effective cross-company collaboration. If compliance relevant data (e.g. dangerous goods indicators) is missing or false, consumer goods manufacturers risk being fined and see their company’s image damaged. Or if logistics data (e.g. product dimensions, gross weight) is inaccurate or provided not in time, business with key account trading partners is endangered. To be able to manage the risk of business critical data defects, companies must be able to a) identify such data defects, and b) specify and use metrics that allow to monitor the data’s quality. As scientific research on both these issues has come up with only few results so far, this case study explores the process of identifying business critical product data defects at German consumer goods manufacturing company Beiersdorf AG. Despite advanced data quality management structures such defects still occur and can result in complaints, service level impairment and avoidable costs. The case study analyzes product data use and maintenance in Beiersdorf’s ecosystem, identifies typical product data defects, and proposes a set of data quality metrics for monitoring those defects.  相似文献   

12.
The low degree of enterprise digitization and the existence of personalized customization and small batch production manufacturing modes lead to the characteristics of small samples and high dimensions of data collected by manufacturing enterprises. The product quality prediction method based on big data is prone to overfitting in the small sample and high dimensional data environment, and the model generalization performance is poor. In order to solve the above problems, this paper conducts research in two aspects of data augmentation and model optimization respectively. At the data augmentation level, a data generation model RVAE-CGAN is proposed, RVAE constrains the value space of GAN and eliminates the influence of outliers in the original data on the quality of generated samples. Using DBSCAN to cluster raw data to generate conditional vectors for guiding sample generation, and finally obtain high-quality generated samples. At the model optimization level, a product quality prediction model PPO-SVR is proposed. The PPO method is used to optimize the hyperparameters of the SVR model and improve the prediction effect of the model. RVAE-CGAN and PPO-SVR models are combined, and RVAE-CGAN is used to expand the number of samples to train PPO-SVR. The experimental results show that the product quality prediction model constructed based on RVAE-CGAN and PPO-SVR outperforms the BP neural network prediction model trained on mixed data. Therefore, the combination of data augmentation and model optimization proposed in this paper can significantly improve the prediction effect of the product quality prediction model in the small sample data environment.  相似文献   

13.
In semiconductor manufacturing, the monitoring system has been developed very excellently and can be used for comprehensively collecting the historical data of process information and quality characteristics of equipment. However, due to the high turnover rate of personnel and the great variance in manufacturing process, the previous control technique by using intuition and experience of engineers for manufacturing process parameter settings to achieve good product quality is no longer appropriate. Therefore, this research establishes a quality predictor for analyzing the relationship between manufacturing process parameter setting and final product quality in the plasma-enhanced chemical vapor deposition (PECVD) of semiconductor manufacturing by applying the back-propagation neural network (BPNN) algorithm and Taguchi method. The experimental data are categorized into 500 pieces of training data and 150 pieces of verifying data. The proposed analysis method for using in the PECVD process of semiconductor manufacturing is verified by comparing the predicted film thickness of SiO2 and the predicted refractive index of silicon dioxide films with the measured data. According to the comparison result, the proposed model has an excellent prediction capability of final product quality and can be applied in process control for related manufacturing fields.  相似文献   

14.
Metal products are susceptible to factors such as cutting force, clamping force and heat in the machining process, resulting in product quality problems, such as geometric deformation and surface defects. The real-time observation and control of product quality are integral to optimizing machining process. Digital twin technologies can be used to monitor and control the quality of products via multi-scale based quality analysis. However, previous research on digital twin lacks a fine-grained expression and generation method for product multi-scale quality, making it impossible to carry out an in-depth analysis of product quality. Aiming at addressing this challenge, we study the multi-scale evolution mechanism of the digital twin model and explore the knowledge generation method of the digital twin data. The proposed method constructed the digital twin quality knowledge model from the macro, meso, and micro levels by utilizing the data of the digital twin mimic model. These multi-scale quality knowledge models can express product quality in a fine-grained way and provide data support for digital twin-based decision-making. Finally, we tested the method in monitoring and controlling the machining quality of an air rudder to verify the feasibility of the proposed method.  相似文献   

15.
The global trade item number (GTIN) is traditionally used to identify trade items and look up corresponding information within industrial supply chains. Recently, consumers have also started using GTINs to access additional product information with mobile barcode scanning applications. Providers of these applications use different sources to provide product names for scanned GTINs. In this paper we analyze data from eight publicly available sources for a set of GTINs scanned by users of a mobile barcode scanning application. Our aim is to measure the correctness of product names in online sources and to quantify the problem of product data quality. We use a combination of string matching and supervised learning to estimate the number of incorrect product names. Our results show that approximately 2 % of all product names are incorrect. The applied method is useful for brand owners to monitor the data quality for their products and enables efficient data integration for application providers.  相似文献   

16.
Rapid and accurate identification of consumer demands and systematic assessment of product quality are essential to success for new product development, in particular for fast moving consumer goods such as food and drink products. This paper reports an investigation into a belief rule-based (BRB) methodology for quality assessment, target setting and consumer preference prediction in retro-fit design of food and drink products. The BRB methodology can be used to represent the relationships between consumer preferences and product attributes, which are complicated and nonlinear. A BRB system can initially be established using expert knowledge and then optimally trained and validated using data generated from consumer or expert panel assessments or from tests and experiments. The established BRBs can then be used to predict the consumer acceptance of new products or set product target values in retro-fit design. The proposed BRB methodology is applied to the design of a lemonade drink product using real data provided by a sensory product manufacturer in the UK. The results show that the BRB methodology can be used to predict consumer preferences with high accuracy and to set optimal target values for product quality improvement.  相似文献   

17.
A good or bad product quality rating can make or break an organization. However, the notion of ??quality?? is often defined by an independent rating company that does not make the formula for determining the rank of a product publicly available. In order to invest wisely in product development, organizations are starting to use intelligent approaches for determining how funding for product development should be allocated. A critical step in this process is to ??reverse-engineer?? a rating company??s proprietary model as closely as possible. In this work, we provide a machine learning approach for this task, which optimizes a certain rank statistic that encodes preference information specific to quality rating data. We present experiments on data from a major quality rating company, and provide new methods for evaluating the solution. In addition, we provide an approach to use the reverse-engineered model to achieve a top ranked product in a cost-effective way.  相似文献   

18.
A bootstrap aggregated model approach to the estimation of product quality in refineries with varying crudes is proposed in this paper. The varying crudes cause the relationship between process variables and product quality variables to change, which makes product quality estimation by soft-sensors a difficult problem. The essential idea in this paper is to build an inferential estimation model for each type of feed oil and use an on-line feed oil classifier to determine the feed oil type. Bootstrap aggregated neural networks are used in developing the on-line feed oil classifier and a bootstrap aggregated partial least square regression model is developed for each data group corresponding to each type of feed crude oil. The amount of training data in crude oil distillation is usually small and this brings difficulties for classification and estimation modelling. In order to enhance model reliability and robustness, bootstrap aggregated models are developed. The inferential estimation results of kerosene dry point on both simulated data and industrial data show that the proposed method can significantly improve the overall inferential estimation performance.  相似文献   

19.
计算机集成制造(CIM)技术研究的难点之一是信息的集成。从技术发展看,CIM信息的集成两个层次,其一是(:IM系统中各“孤岛”之间信息的自动转换,其二是基于并行工程思想的信息共。由于历史原因,CAD、CAPP、IQS、CAM系统各自独立发  相似文献   

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