Reduce Inventory Costs and Free Up Working Capital While Lowering the Risk of Stock-outs
C3 AI Inventory Optimization™ applies advanced AI-machine learning and optimization techniques to help discrete manufacturers reduce inventory levels of parts that are required in manufacturing activities, while maintaining confidence that they will not run out of parts.
Manufacturers of expensive and sophisticated industrial equipment often allow customers to configure hundreds of individual options on their products, leading to products that could have thousands of permutations. Since the final configuration of a product is often not known until close to submission of the order for that product, manufacturing companies need to have significant excess inventory on hand to be able to fulfill their orders on time. Over the years, manufacturing companies have deployed Material Requirements Planning (MRP) software solutions that support planning and automated inventory management. However, most MRP software solutions were not designed to optimize inventory levels by learning continually from data.
C3 AI Inventory Optimization solves this problem by considering several real-world uncertainties including variability in demand, supplier delivery times, quality issues with parts delivered by suppliers, and production line disruptions. C3 Inventory Optimization then dynamically and continually optimizes reorder parameters and minimizes inventory holding and shipping costs for each part.
In order to do this, C3 AI Inventory Optimization aggregates data from different disparate source systems including production orders (actuals and planned), product configurations, bills of material, inventory movements (e.g., arrivals from suppliers, consumption in a production line, intra- and inter- facility shipments), historical settings of re-order parameters, lead time and shipping costs from suppliers, and part-level costs for each location where inventory is maintained.