Data Analysis

Pick-up Optimization at the Warehouse for Production Orders:

In company X, final products are assembled based on customer specific workorders. Each work order is scheduled by the planning department, and once their schedule is set the warehouse receives an order to prepare the components that will be required to start that work order. Each work order requires around 30 components on average, and during a 12-hour shift the warehouse is expected to process 10 such orders. The warehouse uses a dynamic addressing system, so no item has a fixed address in the warehouse.

Effective Capacity Allocation and Planning

Company X has been manufacturing seven main classes of sanitary ware products, which demonstrate different trends in sales figures in recent years. Since all these products are produced using a common pool of resources, capacity planning and allocation becomes a challenging task for the company. In the context of this project, the group is expected to analyze historical sales data for the products and develop scenarios for the upcoming two years. Based on these forecasts, capacity requirements will determined using an allocation model.

Designing an auto-adaptive inventory replenishment system

In a periodic-review inventory replenishment system, two key questions are when to order (at which level of inventory) and how much to order (order up to which level). A periodic-review replenishment policy requires these two parameters (s,S)  be specified for each stock keeping unit (SKU). These parameters should be estimated based on the demand pattern of the corresponding SKU. However, in a volatile business environment a certain parameter set can be outdated very frequently.

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