基于SAS数据挖掘技术在钢铁生产管理中的应用研究

发布时间：2018-01-10 21:09

本文关键词：基于SAS数据挖掘技术在钢铁生产管理中的应用研究　出处：《安徽工业大学》2013年硕士论文　论文类型：学位论文

【摘要】：钢铁的实际生产中，生产管理成为企业充分利用资源的重要过程。结合钢铁企业实际生产过程的某个问题来反映影响企业效益的因素，本文选取由无委托原因造成的合同完成率下降、库存上升等问题为实例，通过实例的有效性证明SAS数据挖掘技术在钢铁生产管理的应用价值。 1.面向钢铁某实际生产的实例形成问题，构建数据挖掘模型。在分析数据挖掘的体系结构、挖掘工具以及数据挖掘各个模型的基础上，建立起SAS关联规则数据挖掘模型，为下文数据挖掘的进行提供有效的挖掘工具平台。 2.在企业真实数据的环境下，构建数据化的挖掘平台。结合本人在某钢铁企业的实际工作，借鉴该钢铁企业数据库的建立过程，在此基础上利用SAS软件对钢铁生产管理数据集市进行了构建，为后续的数据挖掘提供挖掘平台。 3.在挖掘平台上进行数据挖掘，寻找并发现了影响实例问题的关键因素。在挖掘工具和挖掘平台的基础上，针对由于各无委托原因造成的合同完成率下降问题进行分析作为本文数据挖掘的实例，，通过合理的参数配置，得出有效的各无委托原因之间的关联规则。 4.通过可视化展示，找出改善实例的解决方法。通过SAS提供的图形可视化软件，把挖掘结果展示给用户，用户通过分析挖掘的规则提出由于无委托原因造成的合同下降问题的解决方法，从而形成有效决策。通过对实例的结果分析，结合该钢铁实际生产，与挖掘前后的真实数据作对比，证明了本文工作的价值性。
[Abstract]:In the actual production of iron and steel, production management has become an important process for enterprises to make full use of resources. In this paper, some problems such as the decline of contract completion rate and the increase of inventory caused by non-entrustment are selected as examples to prove the application value of SAS data mining technology in iron and steel production management. 1. A data mining model is constructed for a practical production of iron and steel. On the basis of analyzing the architecture of data mining, mining tools and each model of data mining, the data mining model of SAS association rules is established. Provide an effective mining tool platform for the following data mining. 2. Build a data mining platform in the environment of enterprise real data. Combined with my actual work in a certain iron and steel enterprise, the establishment process of the steel enterprise database is used for reference, and on this basis, the data Mart of iron and steel production management is constructed by using SAS software. Provides the mining platform for the subsequent data mining. 3. Data mining is carried out on the mining platform, and the key factors affecting the problem are found. On the basis of mining tools and mining platform, the reduction of contract completion rate caused by no delegation is analyzed as an example of data mining in this paper, through reasonable parameter configuration. The effective association rules between various undelegated reasons are obtained. 4. Through visual display, find out the solution to improve the example. Through the graphical visualization software provided by SAS, the mining result is displayed to the user. The user puts forward the solution to the problem of contract decline caused by no delegation by analyzing the rules of mining. Through the analysis of the result of the example, combining the actual production of the steel with the real data before and after mining, the value of this work is proved.
【学位授予单位】：安徽工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.13;F273;F426.31

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