Mitigating supply and production uncertainties with dynamic scheduling using real-time transport information

Mogre, R.; Wong, C.Y.; Lalwani, C.S.

doi:10.1080/00207543.2014.900201

Mitigating supply and production uncertainties with dynamic scheduling using real-time transport information

Mogre, R.; Wong, C.Y.; Lalwani, C.S.

Authors

Dr Riccardo Mogre riccardo.mogre@durham.ac.uk
Associate Professor

C.Y. Wong

C.S. Lalwani

Abstract

Supply and production uncertainties can affect the scheduling and inventory performance of final production systems. Facing such uncertainties, production managers normally choose to maintain the original production schedule, or follow the first-in-first-out policy. This paper develops a new, dynamic algorithm policy that considers scheduling and inventory problems, by taking advantage of real-time shipping information enabled by today’s advanced technology. Simulation models based on the industrial example of a chemical company and the Taguchi’s method are used to test these three policies under 81 experiments with varying supply and production lead times and uncertainties. Simulation results show that the proposed dynamic algorithm outperforms the other two policies for supply chain cost. Results from Taguchi’s method show that companies should focus their long-term effort on the reduction of supply lead times, which positively affects the mitigation of supply uncertainty.

Citation

Mogre, R., Wong, C., & Lalwani, C. (2014). Mitigating supply and production uncertainties with dynamic scheduling using real-time transport information. International Journal of Production Research, 52(17), 5223-5235. https://doi.org/10.1080/00207543.2014.900201

Journal Article Type	Article
Acceptance Date	Feb 19, 2014
Online Publication Date	Mar 24, 2014
Publication Date	Sep 2, 2014
Deposit Date	Sep 3, 2015
Publicly Available Date	Sep 14, 2015
Journal	International Journal of Production Research
Print ISSN	0020-7543
Electronic ISSN	1366-588X
Publisher	Taylor and Francis Group
Peer Reviewed	Peer Reviewed
Volume	52
Issue	17
Pages	5223-5235
DOI	https://doi.org/10.1080/00207543.2014.900201
Keywords	Simulation, Supply uncertainty, Production uncertainty, Dynamic scheduling, Information sharing.
Public URL	https://durham-repository.worktribe.com/output/1403326

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Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Production Research on 24/03/2014, available online at: http://www.tandfonline.com/10.1080/00207543.2014.900201.