工业工程

工业工程 ›› 2015, Vol. 18 ›› Issue (4): 132-139.

• 实践与应用 • 上一篇    下一篇

基于持续抽检的电力物资多阶段动态采购模型及系统

  

  1. （1. 广东工业大学 广东省计算机集成制造重点实验室，广东 广州 510006；2.华南农业大学 理学院，广东 广州 510642; 3. 香港大学 工业及制造系统工程系，中国 香港）
  • 出版日期:2015-08-30 发布日期:2015-10-15
  • 作者简介:徐杰（1989-），男，安徽省人，硕士研究生，主要研究方向为制造物联网、采购管理.
  • 基金资助:

    国家自然科学基金资助项目（51475095）； 2014年广东省高等学校高层次人才资助项目；国家科技支撑计划资助项目（2012BAF12B10）

A Multi-stage Sourcing Model and System for Electric Power Materials Based on Continuous Sampling Inspection

  1. (1. Guangdong CIMS Provincial Key Laboratory, Guangdong University of Technology, Guangzhou 510006, China; 2. Department of Science, South China Agricultural University, Guangzhou 510642, China; 3.Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong ,China)
  • Online:2015-08-30 Published:2015-10-15

摘要： 针对电力物资集中采购模式中由于采购批量大、合同周期长而导致的不稳定供应问题，提出一种多阶段迭代修正式的电力物资动态采购模型，运用持续质量抽检进行供应商动态调整。首先根据经济订购批量模型确定最佳招标批次、划分标包，并设定多阶段招标模式及供应商评价指标体系；同时依托供应商绩效评价系统，获取历史抽检数据并迭代预测各供应商物资质量，通过建立标包份额动态分配模型动态修正供应商供应量。通过具体案例对模型进行了示例和验证，并对产品质量与供货量的关联性进行了敏感性分析，为采购方有效控制物资质量、供应商提高中标率提供了指导。最后，介绍了项目组开发的一个基于移动物联网的电力物资送检系统，为本文所提的评价模型提供了可行的实施环境。

关键词: 集中招标采购, 经济订购批量模型, 网络分析法, 物联网

Abstract: To deal with the unsteady supply problem of power materials caused by the centralized procurement adopting high-volume and long-period purchasing, a multistage iterative revising sourcing model is proposed. The main idea is to dynamically adjust the sourcing amount from suppliers based on continuous sampling inspection. Firstly, the best bidding stages and batches are determined based on the economic order quantity model, while the multi-stage bidding pattern and electrical material supplier evaluation index system are built. With supplier performance evaluation system, historic service data of electric power materials is captured for the prediction of the material service quality of next stage, which is then imported by the dynamic standard package allocation model to revise the suppliers′ sourcing quantity. A demonstrative case is adopted to exemplify the usage of the above model, and a series of sensitivity analyses are conducted to provide instructive guidance for both material purchasers and suppliers. At last, a mobile internet-of-thingsbased electric power material monitoring system is developed to construct a feasible working environmental for the proposed model.

Key words: centralized bid procurement, economic order quantity model, analytic network process, internet of things