The costs and benefits of commonality in assemble-to-order systems with a (Q, r)-policy for component replenishment

被引:25
|
作者
Hillier, MS [1 ]
机构
[1] Univ Washington, Dept Management Sci, Seattle, WA 98195 USA
关键词
inventory; manufacturing; commonality;
D O I
10.1016/S0377-2217(01)00279-X
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In assemble-to-order systems, it has been shown that replacing a number of specific components by a smaller number of general-purpose, common components can reduce required safety stock levels due to the benefits of risk pooling. Previous research using single-period models has shown that even if the common components are somewhat more expensive than the unique components they replace, the benefits of risk pooling often outweigh the added purchasing costs. However, this has been shown often not to be the case with multiple-period models - in the long run, the added purchasing costs dominate the benefits of risk pooling. However, both single- and multiple-period models ignore one of the benefits of commonality - order pooling. With commonality, demand is pooled into a smaller number of components, reducing the required number of orders (or setups). After re-optimizing the order quantities and order intervals, both the ordering costs and cyclic carrying costs are reduced. This paper develops a model to consider the assemble-to-order environment where components are replenished according to a (Q, r)-policy. Results show that order pooling is a significant benefit; in many cases it is much more important than the risk-pooling benefit. In contrast to multiple-period models, there is often a total cost benefit with commonality, even when the common component is several percent more expensive than the unique components it replaces. (C) 2002 Elesvier Science B.V. All rights reserved.
引用
收藏
页码:570 / 586
页数:17
相关论文
共 50 条
  • [41] Component-based product knowledge modeling and management for assemble-to-order enterprise
    Zhang, JS
    Zheng, SY
    Xue, CF
    Proceedings of the 2005 International Conference on Management Science and Engineering, 2005, : 785 - 792
  • [42] The Impact of Demand Aggregation Through Delayed Component Allocation in an Assemble-to-Order System
    Bernstein, Fernando
    DeCroix, Gregory A.
    Wang, Yulan
    MANAGEMENT SCIENCE, 2011, 57 (06) : 1154 - 1171
  • [43] Optimal and heuristic policies for assemble-to-order systems with different review periods
    Karaarslan, Gonul A.
    Atan, Zumbul
    de Kok, Ton
    Kiesmueller, Gudrun P.
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2018, 271 (01) : 80 - 96
  • [44] Leadtime-inventory trade-offs in assemble-to-order systems
    Glasserman, P
    Wang, YS
    OPERATIONS RESEARCH, 1998, 46 (06) : 858 - 871
  • [45] Product selection and pricing policy of assemble-to-order manufacturer based on heterogeneous demands
    Li Y.
    Huang B.
    Huang H.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2022, 28 (07): : 2263 - 2272
  • [46] Optimal control policies for assemble-to-order systems with commitment lead time
    Ahmadi, Taher
    Atan, Zumbul
    de Kok, Ton
    Adan, Ivo
    IISE TRANSACTIONS, 2019, 51 (12) : 1365 - 1382
  • [47] Single-Product Assemble-to-Order Systems with Exogenous Lead Times
    Muharremoglu, Alp
    Yang, Nan
    Geng, Xin
    OPERATIONS RESEARCH, 2024, 72 (03) : 916 - 939
  • [48] A stochastic program based lower bound for assemble-to-order inventory systems
    Reiman, Martin I.
    Wang, Qiong
    OPERATIONS RESEARCH LETTERS, 2012, 40 (02) : 89 - 95
  • [49] Single-Period Two-Product Assemble-to-Order Systems with a Common Component and Uncertain Demand Patterns
    Xiao, Yongbo
    Chen, Jian
    Lee, Chung-Yee
    PRODUCTION AND OPERATIONS MANAGEMENT, 2010, 19 (02) : 216 - 232
  • [50] Performance analysis and optimization of assemble-to-order systems with random lead times
    Song, JS
    Yao, DD
    OPERATIONS RESEARCH, 2002, 50 (05) : 889 - 903