The algorithms can be configured to fulfill our customers unique needs:
Picking algorithms These algorithms are used to optimize the picking process by determining the most efficient pick load carriers and routes for order picking, as well as the best sequencing of tasks. They may take into account factors such as product and packaging dimensions, order priority, item location, and picking method (e.g. batch picking, zone picking, or wave picking).
Placement algorithms Algorithms that help to determine the optimal placement of goods within the warehouse based on factors such as item velocity, size, and demand. They may also take into account factors such as item compatibility and storage restrictions, e.g. temperature or humidity requirements.
Routing algorithms Algorithms that help to determine the most efficient routes for moving items within the warehouse, whether for put-away, replenishment, or order picking. They may take into account factors such as traffic flow, congestion, and proximity to other tasks or operations.
Predictive analytics Algorithms and AI are being used to analyze historical data and identify patterns and trends to predict future inventory placement and levels and ensure that the right products are in stock at the right place.
Machine learning Machine learning algorithms are being used in IMI’s warehouse management solutions to learn from past data and improve decision-making. For example, machine learning algorithms can be used to optimize picking routes or to predict the most efficient way to store products in the warehouse.
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