Aggregating Demand Orders for Supply Chain Pegging
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Solution Overview
Problem
Current supply chain planning systems face inefficiencies in calculating alerts and pegging due to the time-consuming process of reading all input and output nodes, which can be cumbersome and memory-intensive, especially in high-volume situations, making it difficult to present meaningful information to users.
Innovation Solution
The system aggregates demand orders into an aggregated demand order and forms an aggregated demand timeline, performing pegging operations between supply and demand orders to reduce the number of operations and visualize supply and demand more efficiently, allowing for the calculation of alerts based on deviation in quantity and earliness/lateness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all input and output nodes are read to calculate pegging and alerts, then complete supply chain tracking is achieved, but the process becomes time-consuming and memory-intensive
Solution Approach 1:
The patent segments the supply chain data by grouping input nodes and output nodes into aggregated demand orders and supply orders. Instead of processing all individual nodes separately, the system aggregates them into meaningful groups that can be processed more efficiently while still maintaining complete tracking capability.
Solution Approach 2:
The patent merges multiple input nodes into aggregated demand orders and multiple output nodes into supply orders. This combining of similar elements reduces the total number of processing operations required while preserving the essential supply chain relationships needed for accurate pegging and alert calculation.
2Reliability
If all input and output nodes are read to calculate pegging and alerts, then accurate material supply matching is achieved, but memory consumption increases significantly
Solution Approach 1:
The patent segments the large set of individual nodes into aggregated groups, reducing the memory footprint by storing summary information about groups rather than detailed information about every individual node. This segmentation maintains the ability to accurately match supply and demand while consuming less memory.
Solution Approach 2:
The patent combines multiple similar nodes into aggregated orders, merging redundant information storage. By storing aggregated data rather than individual node data for all nodes, the system achieves accurate material matching with reduced memory consumption.
3Loss of information
If individual orders are processed separately for pegging, then detailed order-level information is maintained, but the number of operations increases making it difficult to present meaningful information
Solution Approach 1:
The patent merges individual order processing into aggregated order processing, reducing the number of operations from individual node level to aggregated group level. This merging maintains the essential supply-demand relationships while dramatically improving productivity and making information presentation more efficient.
Solution Approach 2:
The patent changes the dimension of processing from individual node level to aggregated group level. By operating at a higher level of aggregation, the system reduces computational complexity while still providing meaningful supply chain insights through the aggregated view.
Data Source
AI summary
A system and method for performing supply chain planning, includes providing a plurality of demand orders, each demand order including at least one input interface node, each input interface node identifying a type of material required by said demand order, a quantity of the material required by said demand order and a requirements date the material is required by said demand order, providing a plurality of supply orders, each supply order including at least one output interface node, each output interface node identifying a type of material provided by said supply order, a quantity of the material provided by said supply order and a date the material is provided by said supply order, combining a plurality of said demand orders into an aggregated demand order and forming an aggregated demand time line, each aggregated demand order indicating a quantity of material required, the quantity of material required being a sum of the quantities of the material required by said plurality of demand orders combined into the aggregated demand order and performing an operation for pegging the plurality of supply orders to the aggregated demand orders