Destination-Based Packing in Automated Fulfillment for Customer Preferences
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Solution Overview
Problem
Automated inventory management systems lack the capability to pack ordered fungible and non-fungible goods according to customer preferences, which is essential for efficient and customer-centric fulfillment.
Innovation Solution
An automated service model that includes an integrated system of order processing, automated order fulfillment, and delivery fulfillment, utilizing a computing device with specialized software and mobile robots to manage inventory and pack goods based on customer-specified destinations and preferences, employing a Material Control System (MCS) that uses algorithms for item compatibility and destination-based packing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated mobile robots are used to move inventory in and out of storage racks, then productivity and automation extent are improved, but the system lacks capability to pack goods according to customer preferences
Solution Approach 1:
The system segments the fulfillment process into distinct modules: automated inventory retrieval by mobile robots, centralized order management, and destination-based packing algorithms. This segmentation allows each component to specialize, with robots handling movement efficiently while the control system handles customer preference logic, resolving the contradiction between automation and adaptability.
Solution Approach 2:
An intermediary control system acts as the mediator between the automated robots and customer preferences. This intermediary receives customer preference data, processes packing requirements, and directs the robots accordingly, enabling the automated system to adapt to individual customer needs without reducing automation extent.
2Device complexity
If fungible and non-fungible goods are stored together in the same inventory system, then device complexity is reduced, but packing according to customer preferences becomes more difficult
Solution Approach 1:
The system applies local quality by assigning different handling and packing attributes to different types of goods within the same storage system. Fungible goods are tracked by quantity and destination, while non-fungible goods are tracked by individual identifiers and customer-specific preferences. This allows the system to maintain a unified storage structure while applying differentiated packing logic locally to each good type.
Solution Approach 2:
The control system dynamically changes tracking parameters based on good type and customer preferences. For non-fungible goods, the system activates individual item tracking and preference-matching parameters, while for fungible goods, it uses aggregate quantity and destination parameters. This parameter flexibility allows easy handling of both good types without increasing physical system complexity.
3Productivity
If goods are packed by destination without considering customer unpacking preferences, then productivity is improved, but customer satisfaction decreases
Solution Approach 1:
The system performs preliminary action by analyzing customer preferences and determining optimal packing sequences before actual packing occurs. The control system calculates the most efficient packing order that respects customer unpacking preferences, allowing automated high-speed packing while maintaining customer convenience. This pre-planning enables both productivity and ease of operation.
Data Source
AI summary
A system and method are disclosed relating to an automated store or system including an automated fulfillment section having a storage structure for storing fungible and/or non-fungible goods. The fungible and/or non-fungible goods may be retrieved from storage in response to a customer order. The system and method of the present technology allows retrieved fungible and/or non-fungible goods to be sorted and packed in accordance with stored customer preferences.