Inbound Product Scheduling and Stowing via Dynamic Zone Prediction
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Solution Overview
Problem
Current systems for receiving and stowing inbound products in fulfillment centers lack efficiency in scheduling deliveries based on priority rules and accurately monitoring errors, leading to delays in shipment and delivery due to manual processes and fixed product locations.
Innovation Solution
A computer-implemented system that schedules inbound deliveries based on a predetermined priority rule, predicts stowing zones for products using parameters like priority level, dimension, weight, or expiration date, and assigns error barcodes for quick error reporting, allowing for intelligent delivery scheduling and efficient error tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual scanning and reporting processes are used for inbound errors, then workers can identify and report errors, but the process is time-consuming and causes delays in shipment and delivery
Solution Approach 1:
The patent replaces manual mechanical scanning and reporting processes with an automated optical/image recognition system. The system captures images of inbound products, automatically identifies errors through image analysis, and generates error reports without manual intervention, thereby maintaining detection accuracy while eliminating time delays
Solution Approach 2:
The system enables self-service error detection by automatically analyzing product images and identifying errors without requiring worker intervention. The automated system performs detection, classification, and reporting functions that previously required manual labor, significantly reducing processing time while maintaining detection capabilities
2Ease of operation
If fixed locations are designated for stowing different product types, then product organization is simplified, but the system lacks flexibility and efficiency in handling diverse inbound products
Solution Approach 1:
The patent implements a dynamic stowing system where product locations are not fixed but determined by real-time analysis of product characteristics from images. The system adaptively assigns stowing locations based on current inventory levels, product dimensions, weight, and other parameters, allowing the organization structure to change dynamically rather than relying on static fixed locations
Solution Approach 2:
The system changes multiple parameters simultaneously to optimize stowing decisions - including product dimensions, weight, priority level, expiration date, and current warehouse capacity. This multi-parameter approach allows flexible adaptation to diverse product types while maintaining organized storage through systematic parameter-based allocation
3Productivity
If delivery scheduling is not optimized with priority rules, then all deliveries are treated equally, but this leads to inefficient resource allocation and delays in processing high-priority products
Solution Approach 1:
The patent introduces priority level as a key parameter in the scheduling system, allowing deliveries to be classified and processed according to their urgency. The system uses image analysis to extract product parameters and automatically assigns priority levels, enabling differentiated processing without requiring complex manual scheduling procedures
Solution Approach 2:
The system performs preliminary classification and priority assignment of inbound products through automated image analysis before physical processing begins. By pre-determining priority levels and processing sequences based on image data, the system prepares the workflow in advance, avoiding the need for complex real-time scheduling decisions and improving overall productivity
Data Source
AI summary
The present disclosure provides systems and methods for receiving inbound products, comprising a memory and a processor configured to schedule a delivery of an inbound pallet based on a predetermined priority rule, receive at least one of a waybill number, a reservation number, or a purchase order number associated with the inbound pallet containing a product, and modify a database to assign an inbound barcode and at least one of the waybill number, the reservation number, or the purchase order number to the inbound pallet, receive at least one of the inbound barcode or a product identifier associated with the product, predict a zone for stowing the product, receive a tote identifier associated with a tote containing the product, and modify the database to assign the product identifier associated with the product and the tote identifier to the zone.