American Journal of Operations Management and Information Systems
Volume 4, Issue 1, March 2019, Pages: 26-38
Received: Dec. 4, 2018;
Accepted: Jan. 11, 2019;
Published: Apr. 26, 2019
Views 272 Downloads 24
Jianhong Yu, School of Business, Jianghan University, Wuhan, China
Jennifer Shang, Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, USA
Wenchyuan Chiang, Collins College of Business, The University of Tulsa, Tulsa, USA
The synchronization and coordination of material flows is a key element in the supply chain management. To analyze the effects of coordinated replenishment for components, we consider an assembly system with two component-suppliers, one supply-hub and one manufacturer, under stochastic final product demand. We propose three different strategies: (i) the decentralized replenishment, (ii) the coordinated replenishment without coordinated quantity, and (iii) the coordinated replenishment policy with coordinated quantity for infinite planning horizon. We propose optimal decisions for all strategies. Results show that policy (ii) is always better than policy (i). We further identify the conditions under which the third strategy outperforms the other two. Policy (iii) is better on cost saving and service level, only when it satisfies certain conditions. Numerical studies are conducted to validate the model and to derive managerial implications.
Coordinated Replenishment Policy in an Assembly System Based on Supply-Hub, American Journal of Operations Management and Information Systems.
Vol. 4, No. 1,
2019, pp. 26-38.
Song J. S, Zipkin P. Supply chain operations: assemble-to-order systems. A. G. de Kok, S. C. Graves, eds. Handbooks in Operation Research and Management Science, 11. Supply Chain Management. Elsevier, Amsterdam, The Netherlands, 2003.
Shah J, Goh M. Setting operating policies for supply-hubs. International Journal of Production Economics, 2006, 100 (2), 239–252.
Guruprasad P, Chen Z. L. Joint cyclic production and delivery scheduling in a two-stage supply chain. International Journal of Production Economics, 2009, 119 (1), 55–74.
Timmer J, Chessa M, Boucherie R. J. Cooperation and game-theoretic cost allocation in stochastic inventory models with continuous review. European Journal of Operational Research, 2013, 231 (3), 567–576.
Khouja M, Goyal S. A review of the joint replenishment problem literature: 1989-2005. European Journal of Operational Research, 2008, 186 (1): 1-16.
Qu W. W, Bookbinder J. H, Iyogun P. Integrated inventory-transportation system with modified periodic policy for multiple products. European Journal of Operational Research, 1999, 115:254-269.
Minner S, Silver E. A. Multi-product batch replenishment strategies under stochastic demand and a joint capacity constraint. IIE Transactions, 2005, 37:469-479.
De Boeck, L, Vandaele N. Analytical analysis of a generic assembly system. International Journal of Prduction Economics, 2011, 131, 107-114.
De Boeck L, Vandaele N. Coordination and synchronization of material flows in supply chains: an analytical approach. International Journal of Production Economics, 2008, 116: 119-207.
Sternatz J. The joint line balancing and material supply problem. International Journal of Production Economics, 2015, 159: 304-318.
Antonio C. C, Pacifico M. P, Paolo S. Planning models for continuous supply of parts in assembly systems. Assembly Automation, 2015, 35 (1): 35-46.
Simon E, Michel G. Scheduling in-house transport vehicles to feed parts to automotive assembly lines. European Journal of Operational Research, 2017, 260 (1): 255-267.
Barnes E, Dai J, Deng S. On the Strategy of Supply-hubs for Cost Reduction and Responsiveness: White Paper on Electronics Supply Chain. Georgia Institute of Technology and National University of Singapore, 2000.
Ma S. H, Gong F. M. Collaborative decision of distribution lot-sizing among suppliers based on supply-hub. Industrial Engineering and Management, 2009, 14 (2): 1-9.
Li S. Y, Zhang D. Z, Jin F. P. Base inventory cooperation strategy of multi-parts with supply-hub. International Journal of Business and Management, 2013, 8 (20): 96-104.
Li G, Lv F, Guan X. Collaborative scheduling model for supply-hub with multiple suppliers and multiple manufacturers. The Scientific World Journal, 2014, 12 pages, http://dx.doi.org/10.1155/2014/894573.
Zhong Jin-Hong, Jiang Rui-Xuan, and Zheng Gui. Multi-item distribution policies with supply hub and lateral transshipment. Mathematical Problems in Engineering, 2015, Article ID 702482, 12 pages, http://dx.doi.org/10.1155/2015/702482.
Zhang Ling-rong, Zhang Xing-long, Zhao Gan. Collaborative replenishment decision based on supply-hub in the condition of uncertain demand. Systems Engineering, 2016, 34 (10): 98-107.
Zhang Libin, Cheng Yaorong, Liang Jiajia. Mechanism of leader-follower distribution decision of the suppliers with the supply hub. Journal of Systems & Management, 2017, 26 (3): 577-582.
Chen Jianhua, Li Li, Yang Huan. Simulation model of buffer inventory control in ATO supply chain based on supply-hub. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2018, 42 (5): 738-743.
Goyal, S. K. Note on: manufacturing cycle time determination for a multi-stage economic production quantity mode. Management Science, 1976, 23, 332–333.