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

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.

Keywords:

• simulation
• supply uncertainty
• production uncertainty
• dynamic scheduling
• information sharing

Acknowledgments

The authors would like to thank Mr. Pietro Lucidi, IT project manager, for his kind participation in this research project, Ms. Alice Tasin and Ms. Fen Ren, for helping refining the assumptions of this paper, by working on similar yet different problems, the editor and the anonymous reviewers for their helpful comments and suggestions.