The challenge
Ensuring material availability at minimal cost is a greater challenge than ever before for manufacturing companies. Minimum order quantities and increasing customer requirements are leading to rising inventories of raw sheet metal and high handling costs for stock transfers in many manufacturing companies. In the transfer project “Artificial Intelligence Based Optimization of Sheet Sourcing” (AI-BOSS), an AI solution for sheet metal assortment formation was developed to reduce the inventory of raw sheet metal in manufacturing companies.
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The solution
Clustering sheet metal requirements with the same quality, surface finish, and thickness but different lengths and widths can reduce inventory costs while increasing material availability. Optimal clustering must take into account the trade-off between scrap and assortment costs (storage, capital commitment, handling). The methods and the associated tool can be used not only in the metalworking industry but also in other industries with similar problems.
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