Automated Procurement Device Combining Restocking Operations
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Solution Overview
Problem
Current IoT systems lack efficient methods to automatically combine commodity restocking operations across multiple networked bins to maximize cost savings, often resulting in suboptimal pricing and increased operational costs due to individual bin restocking.
Innovation Solution
A computerized method and system that collect pricing metrics and combine restocking operations across multiple bins when the quantity of a commodity in one bin falls below a threshold, identifying potential cost savings by integrating restocking operations to optimize resource allocation and reduce shipping costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If individual bin restocking operations are executed separately, then each bin can be restocked independently and quickly, but the overall cost increases due to loss of bulk pricing opportunities
Solution Approach 1:
The system combines multiple individual restocking operations into a single consolidated restocking operation. When the processor determines that multiple bins require restocking, it merges these separate operations into one combined operation, enabling the organization to qualify for bulk pricing and shipping discounts while still addressing each bin's restocking needs.
2Loss of energy
If restocking operations are combined across multiple bins, then cost savings are achieved through bulk pricing, but the complexity of managing combined operations increases
Solution Approach 1:
The system implements automated self-service functionality where the processor automatically monitors inventory levels across multiple bins, identifies when restocking is needed, combines appropriate restocking operations, and executes the consolidated order without requiring manual intervention. This automation handles the complexity of managing combined operations while preserving the cost benefits.
Solution Approach 2:
The system uses continuous feedback from inventory monitoring to trigger restocking operations. When the processor detects that bin inventory levels fall below predetermined thresholds, it automatically initiates the combination analysis and restocking process, ensuring that combined operations are formed based on real-time needs rather than manual planning.
3Loss of energy
If automated combination of restocking operations is implemented, then cost savings are maximized, but the system complexity and initial investment increase
Solution Approach 1:
The processor is designed to perform multiple functions: it monitors inventory levels, determines when restocking is needed, analyzes potential combinations of restocking operations, calculates cost savings, and executes the consolidated orders. This multi-functionality consolidates what could be separate complex systems into a single automated platform, maximizing cost savings while managing overall system complexity.
Data Source
AI summary
Processors configured by aspects of the present invention collect pricing metrics that are applicable to restocking operations executed to restock different individual commodities within different respective ones of a plurality of networked bins. In response to determining that a quantity of a first commodity within a first of the bins is below a threshold restocking level, processors combine a first restocking operation that restocks a first restocking quantity of the first commodity within the first bin with a second restocking operation that restocks a second restocking quantity of a second commodity within a second bin of the plurality of bins into a combined restocking operation, in response to determining that executing the combined restocking operation generates a combination cost saving relative to a cost of executing the first restocking operation without combining with the second restocking operation.