Spare parts management for irregular demand items

被引:35
作者
Costantino, Francesco [1 ]
Di Gravio, Giulio [1 ]
Patriarca, Riccardo [1 ]
Petrella, Lea [2 ]
机构
[1] Univ Rome Sapienza, Dept Mech & Aerosp Engn, Via Eudossiana 18, Rome, Italy
[2] Univ Rome Sapienza, Dept Methods & Models Econ Terr & Finance, Via C Laurenziano 9, I-00161 Rome, Italy
来源
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE | 2018年 / 81卷
关键词
Inventory management; Logistic; Intermittent demand; Lumpy demand; Zero-inflated model; EMERGENCY SUPPLY FLEXIBILITY; INTERMITTENT DEMAND; MULTI-INDENTURE; COUNT DATA; REPAIRABLE ITEM; INVENTORY MODEL; LUMPY DEMAND; LATERAL TRANSSHIPMENTS; REGRESSION-MODELS; STOCK CONTROL;
D O I
10.1016/j.omega.2017.09.009
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Inventory optimization of high-value spare parts may generate a significant reduction of cost to allow a better allocation of resources in maintenance management. Sherbrooke's METRIC (Multi Echelon Technique for Recoverable Item Control) is the most common method to define an overall optimization process adopting a system-approach. Its main assumption consists of adopting a Poisson distribution to describe the demand pattern of the items. However, many studies proved that in high-availability systems, high-cost spare parts often follow irregular demand patterns, with very frequent zero-demand values. For this purpose, we propose an innovative model for a single site, the ZIP-METRIC, to take advantage of a distribution yet widely adopted in the healthcare and biological sciences, i.e. the Zero-Inflated Poisson. A case study of 1745 items of a European airline fleet demonstrates the model effectiveness, confirming that the ZIP-METRIC outperforms the traditional Poisson-based approach. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:57 / 66
页数:10
相关论文
共 72 条
[1]   Two-part regression models for longitudinal zero-inflated count data [J].
Alfo, Marco ;
Maruotti, Antonello .
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2010, 38 (02) :197-216
[2]   Modeling emergency supply flexibility in a two-echelon inventory system [J].
Alfredsson, P ;
Verrijdt, J .
MANAGEMENT SCIENCE, 1999, 45 (10) :1416-1431
[3]  
[Anonymous], 2011, R: A Language and Environment for Statistical Computing
[4]   An optimal policy for a two depot inventory problem with stock transfer [J].
Archibald, TW ;
Sassen, SAE ;
Thomas, LC .
MANAGEMENT SCIENCE, 1997, 43 (02) :173-183
[5]   MODELING EMERGENCY LATERAL TRANSSHIPMENTS IN INVENTORY SYSTEMS [J].
AXSATER, S .
MANAGEMENT SCIENCE, 1990, 36 (11) :1329-1338
[6]   Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice [J].
Bacchetti, Andrea ;
Saccani, Nicola .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2012, 40 (06) :722-737
[7]  
Basten R.J. I., 2014, Surveys in Operations Research and Management Science, V19, P34, DOI [10.1016/j.sorms.2014.05.002, DOI 10.1016/J.SORMS.2014.05.002]
[8]   A dynamic hurdle model for zero-inflated panel count data [J].
Belloc, Filippo ;
Bernardi, Mauro ;
Maruotti, Antonello ;
Petrella, Lea .
APPLIED ECONOMICS LETTERS, 2013, 20 (09) :837-841
[9]  
Boylan, 2006, FORESIGHT INT J APPL, V4, P39
[10]   Classification for forecasting and stock control: a case study [J].
Boylan, J. E. ;
Syntetos, A. A. ;
Karakostas, G. C. .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2008, 59 (04) :473-481