Case study card:
Manufacturing logistics optimisation
Primary Industries and Infrastructure
RUSAL is the second largest aluminium producer in the world, with over $9 billion in sales.
Mining and manufacturing industries face huge logistics costs. Maritime and land transportation costs are a substantial expenditure.
Time constraints lead managers to use primitive route planning methods.
The solution accounts for various business factors: loading rate, the distance between destinations, average vehicle speed, the sailing time between ports, oil consumption, MGO, order volume and material type.
The system groups orders into the batches and plans a calendar for 3 months in advance, updating the SAP system daily.
The system automatically chooses the best day of dispatch for each batch of orders, considers deadlines, loading speed, incoterms and client preferences.
Further, predictive algorithms predict market vessel prices based on macroeconomic factors and seasonality, to optimise delivery cost.
Mining & Metals (supply chain)