Lin, Junyi and Naim, Mohamed Mohamed ORCID: https://orcid.org/0000-0003-3361-9400 2017. Dynamic modelling and analysis of a personal computer supply chain: a control engineering approach. Presented at: 24th International Conference on Production Research, Poznan, Poland, 30 July- 3 August 2017. |
Abstract
The hybrid Assembly-to-Order (ATO) supply chain, combining make-to-stock and make-to-order (MTS-MTO) production separated by a customer order decoupling point (CODP), is well-recognized in the personal computer (PC) sector to achieve a competitive balance between customer responsiveness and minimum reasonable inventory. Empirical evidence suggests that such a hybrid system can mitigate poor supply chain dynamics, but few researchers have attempted to model and analyse its dynamic behaviour. Hence, our aim is to determine the implications of the system dynamics on the hybrid ATO system including delivery lead times (MTO), inventory holding and capacity variations (MTS). Based on a PC company’s supply chain, we develop a non-linear dynamic model of an ATO supply chain and benchmark against the well-known Inventory and Order Based Production Control System (IOBPCS) family. A system dynamics simulation is utilized to examine the impact of major control policies on the dynamic performance metrics in responding to deterministic demand. Results showed that a trade-off design between customer lead time and capacity evenness should be considered. A compromise between CODP inventory and capacity variations should also be evaluated, which is profoundly driven by the CODP inventory control policy. Finally, dynamic behaviour is amplified from downstream to upstream echelons in the ATO environment, thus managers should aware the balance between benefit of implementing CODP strategy and the cost of supply chain dynamics.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Completion |
Status: | Unpublished |
Schools: | Business (Including Economics) |
Subjects: | H Social Sciences > HD Industries. Land use. Labor |
Last Modified: | 02 Nov 2022 11:17 |
URI: | https://orca.cardiff.ac.uk/id/eprint/101483 |
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