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Overview
An internationally prominent zinc smelting company required a solution to help offset disruptive cyclical economic conditions and maximize the returns from purchased raw materials for three distributed plants.
Problem Description
Due to cyclical economic variations that affected operating costs, the client, a global zinc smelting company, was facing issues in planning and procuring raw materials efficiently. Without a centralized and coordinated solution, it was difficult to manage inventories across three distributed plant locations and keep operating costs down. Further, unpredictability in the inventory supply affected the overall process stability of the company, resulting in reduced profitability.
Solution
Nagarro built a web-based decision support system that was able to compute the best possible distribution of raw material between the three plants during a specified planning horizon, by combining several separate data sources. The system consisted of several interconnected models, each designed to solve a different problem. All models were simultaneously solved using an optimization algorithm, which encapsulated the problem logic and took into consideration several hundred applicable weighted constraints.The algorithm used a third party non-linear solver to do the numerical solution.Specific components of the system include
- A Detailed Planning Model at each plant location to ensure that the raw materials are available at that location and the plant capacity is utilized in a manner that maximizes the throughput of impurities within the limits of local process constraints and environmental regulations.
- A Consumption Model to compute the planned consumption at each plant location for a given planning horizon.
- A Stock Model to represent the availability of stock at each plant location in terms of the “days of inventory of optimum blend.”
- A Distribution Model to specify how the different raw materials are to be distributed among the three plant locations.
- A Dispatching Model to specify how the distribution model is to be implemented in reality (taking into consideration for rail, barge, and other modes of transportation the frequency of operation, available capacities, costs, and so forth).
- An Economic Model to quantify the solution in $ terms, and aid in the preparation of a more effective budget plan.
- Convenient web-based user interface allows for formulation of problems and constraints, monitoring of process, viewing of results, and generation of reports and graphs
Benefits
- Saved $5 million in working capital due to reduction of raw material inventory by 25,000 tons
- Reduced overall distribution budget by 7.5%
- Ability to offset impact of regional transportation cost spikes through optimized transportation planning
- Cost savings as a result of increased process stability
- Optimized solutions helped in planning procurement and plant operations
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