Block stacking storage guarantees high storage density for end-of-line warehouses in product flow manufacturing systems, which are mostly diffused in food processing and beverage industry. These storage systems, characterized by high volumes per item and limited inventory mix, are organized through storage deep lanes of homogeneous items. Setting the optimal lane depths for the incoming stock-keeping-units (SKUs) influences the overall space and time efficiency performances, as well as the layout of the storage zones, the selection of the proper storage modes and equipment. This paper illustrates an original decision-support model to (1) manage existing block storage warehouses, and (2) to aid the design of new block storage systems from green field. The management of a warehouse (1) deals with the assignment of the incoming product lots to the optimal lane depth, storage mode, and zone in a constrained and capacitated storage environment. The design of a warehouse from green field (2) is aided by identifying the optimal configuration of lane depths and storage modes that minimizes the infrastructural costs. The proposed model is formulated via integer linear programming (ILP) and minimizes mutually the costs generated by space and time inefficiencies. The illustrated results obtained by its application to a real case study from the beverage industry, candidate the model as a tool to aid operative and strategic layout issues in deep lane storage systems.
The International Journal of Advanced Manufacturing Technology – Springer Journals
Published: Feb 16, 2017
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