A Classification Method of Inventory Spare Parts Based on Improved Super Efficient DEA-ABC Model
Enterprises generally have the problem of high spare parts inventory costs at present. One of the main reasons for this problem is that the classification standard of spare parts inventory is single and the classification result is unreasonable. Based on the analysis of commonly used inventory spare...
Saved in:
Published in | Learning Technologies and Systems Vol. 12511; pp. 214 - 224 |
---|---|
Main Authors | , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2021
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Enterprises generally have the problem of high spare parts inventory costs at present. One of the main reasons for this problem is that the classification standard of spare parts inventory is single and the classification result is unreasonable. Based on the analysis of commonly used inventory spare parts classification methods, this paper proposes an improved ABC classification method based on super efficient DEA. It integrates the input-output efficiency of super efficient DEA into the supply chain of spare parts procurement and outbound use. In the process, the Delphi method is used to investigate the inventory management personnel, and the statistical results of the survey are added to super efficient DEA model as the weight restriction conditions, and than the improved super efficient DEA-ABC classification model was constructed. This model achieves a combination of subjective and objective, which increases the scientificity and practicality of the classification results. Finally, taking the inventory classification of subway spare parts in a certain city as an example, the effectiveness of the method is verified. |
---|---|
Bibliography: | Supported by the National Natural Science Foundation of China (Grant No. 71771078) and the Social Science Research Project of Hebei Provincial Department of Education of China (Grand No. SD101020). |
ISBN: | 303066905X 9783030669058 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-030-66906-5_20 |