Push, pull, or hybrid control in supply chain management

International Journal of Computer Integrated Manufacturing

Volumn 17, Issue 2, 2004, Pages 126-140

  Takahashi, Katsuhiko ^a   Nakamura, Nobuto ^a  

^a HIROSHIMA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; INVENTORY CONTROL; JUST IN TIME PRODUCTION; MATHEMATICAL MODELS; PRODUCTION CONTROL; STOCHASTIC CONTROL SYSTEMS;

HYBRID CONTROL; SUPPLY CHAIN MANAGEMENT (SCM);

COMPUTER AIDED MANUFACTURING;

EID: 1242285464     PISSN: 0951192X     EISSN: None     Source Type: Journal    
DOI: 10.1080/09511920310001593083     Document Type: Conference Paper

References (17)

1. CHEN, F., 1999, On (R, NQ) policies in serial inventory systems. In S. Tayur (ed.) Quantitative Models for Supply Chain Management (Massachusetts: Kluwer), Ch. 4, pp. 71-109.
2. CHEN, F., DREZNER, Z., RYAN, J. K., and SIMCHI-LEVI, D., 1999, The bullwhip effect: management insights on the impact of forecasting and information on variability in a supply chain. In Quantitative Models for Supply Chain Management, Ch. 14, pp. 417-439.
3. DELEERSNYDER, J. L., HODGESON, T. L., KING, R. E., O'GRADY, P. J., and SAVVA, A, 1992, Integrating kanban type pull systems and MRP type push systems: insights from a Markovian model. IIE Transactions, 24(3), 43-56.
4. ERENGÜÇ, S. S., SIMPSON, N. C., and VAKHARIA, A. J., 1999, Integrated production/distribution planning in supply chains: an invited review. European Journal of Operational Research, 115(2), 219-236.
5. GAVIRNERI, S. and TAYUR, S. R., 1999, Value of information sharing and comparison with delayed differentiation. In S. Tayur (ed.) Quantitative Models for Supply Chain Management (Massachusetts: Kluwer), Ch. 15, pp. 441-466.
6. IYER, A. V., 1999, Modeling the impact of information on inventories. In S. Tayur (ed.) Quantitative Models for Supply Chain Management (Massachusetts: Kluwer), Ch. 11, pp. 337-357.
7. KERKE, S., MUKHOPADHYAY, T., and SRINIVASAN, K., 1999, Modeling impacts of electronic data interchange technology. In S. Tayur (ed.) Quantitative Models for Supply Chain Management (Massachusetts: Kluwer), Ch. 12, pp. 359-379.
8. KIMURA, O. and TERADA, H., 1981, Design and analysis of pull system: a method of multi-stage production control. International Journal of Production Research, 19(3), 241-253.
9. LEE, H. L., PADMANABHAN, V. and WHANG, S., 1997, Information distortion in a supply chain: the bullwhip effect. Management Science, 43 (4), 546-558.
10. OLHAGER, J. and ÖSTLUND, B., 1990, An integrated push-pull manufacturing strategy. European Journal of Operational Research, 45(2-3), 135-142.
11. ORLICKY, J., 1975, Material Requirements Planning (McGraw-Hill).
12. SARMIENTO, A. M. and NAGI, R., 1999, A review of integrated analysis of production-distribution systems. IIE Transactions, 31(11), 1061-1074.
13. SUGIMORI, Y., KUSUNOKI, K., CHU, F., and UCHIKAWA, S., 1977, Toyota production system and kanban system: materialization of just-in-time and respect-to-human system. International Journal of Production Research, 15(6), 553-564.
14. TAKAHASHI, K., HIRAKI, S., and SOSHIRODA, M., 1994a, Pull-push integration in production ordering systems. International Journal of Production Economics, 33(1/3), 155-161.
15. TAKAHASHI, K., HIRAKI, S., and SOSHIRODA, M., 1994b, Flexibility of production ordering systems. International Journal of Production Research, 32(7), 1739-1752.
16. TAKAHASHI, K. and NAKAMURA, N., 1998, Ordering alternatives in JIT production systems. Production Planning and Control, 9(8), 784-794.
17. WANG, D. and XU, C.-G., 1997, Hybrid push/pull production control strategy: simulation and its applications. Production Planning and Control, 8(2), 142-151.