Dynamic Inventory Management Level Selection
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Solution Overview
Problem
Conventional inventory management systems fail to distinguish between situations where managing items at the case level or individual level is more advantageous, leading to inefficiencies and inconsistencies in stocking and retrieval processes at retail sales facilities.
Innovation Solution
A system and method using electronic devices with processors to receive data on product cases, obtain inventory management factors, and estimate whether items should be picked and stored at the case level or individual level, providing indications to workers on the appropriate level for storage bin management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If items are managed at case level for efficiency, then inventory management time is reduced, but retrieval efficiency decreases when individual items need to be accessed
Solution Approach 1:
The system dynamically determines the management level (case or individual) for each item based on real-time analysis of multiple factors including item characteristics, storage bin properties, and operational context. This allows the system to adapt the management approach for each item rather than using a static case-level or individual-level approach for all items.
Solution Approach 2:
The system changes the management parameter (case level vs. individual level) based on calculated scores derived from multiple factors. Items with certain characteristics (e.g., large size, low turnover) are managed at case level, while items with different characteristics (e.g., small size, high turnover) are managed at individual level, optimizing both management efficiency and retrieval efficiency for different item types.
2Adaptability or versatility
If stocking associates use judgment to decide case vs. individual level, then flexibility is improved, but consistency and accuracy decrease due to user error
Solution Approach 1:
The system provides feedback to stocking associates by calculating a score that indicates the recommended management level for each item. This feedback mechanism replaces subjective judgment with objective, consistent criteria while maintaining the flexibility to handle different item types, thereby improving both accuracy and consistency of decisions.
Solution Approach 2:
The system enables items to effectively 'decide' their own management level based on their inherent characteristics (size, weight, turnover rate) and the storage bin's properties. The algorithm automatically determines the optimal management level without requiring human judgment, ensuring consistent and accurate decisions across all items.
3Ease of operation
If items are managed at individual level, then retrieval efficiency is improved, but time consumption increases for routine inventory management
Solution Approach 1:
Different management levels are applied to different items based on their local characteristics. High-turnover, small items that benefit from individual management are handled at individual level, while low-turnover, large items are managed at case level. This localized approach optimizes retrieval efficiency for items that need it while minimizing time consumption for items that don't.
Data Source
AI summary
In some embodiments, methods and systems of locating overstock items at a retail sales facility include receiving data when a worker of the retail sales facility scans a product case containing a product using an inventory management electronic device including a processor; obtaining at least one inventory management factor associated with the product; estimating whether the product is to be picked by the worker from a storage bin at a stock room location while packed in the product case or after being removed from the product case; and outputting, based on the estimating step, an indication to the worker either that the product is to be picked from the storage bin without being removed from the product case, or that the product is to be picked from the storage bin after being removed from the product case.


