Shipment Consolidation Policy Project

Detta är en Master-uppsats från Lunds universitet/Produktionsekonomi

Sammanfattning: Title: Shipment Consolidation Policy Project. A case study at the Integrated Logistics Product Area at the Case Company. Authors: Carl Tornerhjelm, Tom Wachtmeister. Supervisor: Peter Berling, the Division of Production Management. Background: Larger corporations that distribute products and goods globally face both internal and external demands from stakeholders. High service levels call for frequent shipping for goods to arrive on time. However, frequent shipping comes at a higher cost. Lately, this has become an issue for the case company. At its cross-docking warehouse - which ships unique orders - high safety stock is not an option. Therefore, to reduce the shipping cost, the company’s alternative would be to increase lead times and consolidate shipments into larger batches. This will reduce the number of shipments and hence reduce the transportation cost. The key is to find a balance between these two alternatives to satisfy all parties by implementing an appropriate consolidation policy. Purpose: The purpose of this thesis is to evaluate whether a new shipment consolidation policy could be implemented for selected test locations. Research Questions: (1) Will a shipping consolidation policy reduce the total shipping costs while maintaining a reasonable service level? (2) For locations with different order frequencies, is the consolidation cost reduction benefit equal? Methodology: The methodology framework was inspired by Höst et al. The process included first defining the problem to be able to acknowledge what relevant data needed to be collected. This included both quantitative and qualitative data, as well as the literature required to solve the research study. When all necessary data had been collected, statistical data analysis was completed for the order arrival time, weight and volume to use as input for the developed model. vi Conclusion: The belief is that the case company should implement a consolidation policy for the selected locations. At reasonable service levels, all locations show significant shipping cost reductions. The researchers found that the cost reduction benefit is equal for different order frequency locations if the optimal Time and Quantity- based policy is implemented. However, due to the holding period restrictions set by the case company, the team recommends that the company focuses on high-frequency locations, as these show a greater cost reduction benefit for short holding periods. Furthermore, the data analysis found that the data can be used in the mathematical model obtained in the literature with some modifications. Moreover, the model is proven to be robust as the output is only slightly affected by changes in estimated parameter inputs

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