基于大数据分析的矿山备件采购预测模型  

Prediction Model of Mine Spare Parts Procurement Based on Big Data Analysis

作　　者：刘伟 李国清[1,2] 侯杰[1,2] 王浩 陈连韫[1,3] 范纯超 LIU Wei;LI Guoqing;HOU Jie;WANG Hao;CHEN Lianyun;FAN Chunchao(School of Civil and Resource Engineering,University of Science and Technology,Beijing 100083,China;Key Laboratory of the Ministry of Education for Efficient Mining and Safety of Metal Mines,Beijing 100083,China;Shandong Gold Group Co.,Ltd.,Jinan 250102,China)

机构地区：[1]北京科技大学土木与资源工程学院,北京100083 [2]金属矿山高效开采与安全教育部重点实验室,北京100083 [3]山东黄金集团有限公司,山东济南250102

出　　处：《金属矿山》2022年第11期179-185,共7页Metal Mine

基　　金：国家自然科学基金项目(编号:52074022)。

摘　　要：为了解决传统矿山备件采购过度依赖人为经验、采购策略单一等问题,借助大数据分析技术实现备件采购策略优化与智能决策。在对矿山企业备件采购流程进行梳理的基础上,运用大数据分析技术构建了以“备件智能分类—备件消耗预测”为核心框架的矿山备件采购预测模型,形成了用于指导矿山企业备件采购的决策方法。将传统ABC分类法在属性分类上加以扩展,分别选取采购价格、消耗速度、采购周期作为备件的分类维度,并利用Kmeans算法对备件进行智能化分类。针对不同类别备件的采购特征,构建了Prophet-LSTM备件消耗组合预测模型,根据预测结果确定合理的备件采购数量与采购周期,实现矿山备件智能化采购。以山东某黄金地下矿山的备件数据为基础进行了模型验证,结果表明:应用备件采购预测模型制定采购计划,有效提升了矿山企业备件管理水平和科学采购能力。In order to solve the problems of over reliance on human experience and single procurement strategy in the process of traditional mine spare parts procurement,big data analysis technology is used to realize optimization of spare parts procurement strategy and intelligent decision-making.On the basis of sorting out the process of spare parts procurement in mining enterprises,the mining spare parts procurement prediction model with"intelligent classification of spare parts-consumption prediction of spare parts"as the core framework is constructed,and the decision-making method for guiding spare parts procurement of mining enterprises is formed.The traditional ABC classification method is extended in attribute classification,and purchase price,consumption speed,and purchase cycle are selected as the classification dimensions of spare parts,and the Kmeans algorithm is used to realize spare parts classification.Aiming at the procurement characteristics of different types of spare parts,the Prophet-LSTM combination prediction model was constructed,and the reasonable spare parts procurement quantity and procurement time were determined according to the prediction results,so as to realize the intelligent procurement of spare parts in mines.Based on the spare parts data of an underground gold mine in Shandong Province,the model was verified and the results showed that the application of spare parts procurement prediction model to formulate procurement plans effectively improved the management level of spare parts and scientific procurement capabilities of mining enterprises.

关 键 词：矿山备件 大数据分析 采购策略 聚类分析 组合预测 

分 类 号：TD67[矿业工程—矿山机电]