Autonomous Polytope Analysis Tool for Supply Chain Planning
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Solution Overview
Problem
Existing supply chain planning systems are inefficient, error-prone, and lead to suboptimal decisions due to the need for multiple planners to work sequentially on what-if scenarios, resulting in lengthy and manpower-intensive processes.
Innovation Solution
The development of a system that enables autonomous assumption-based planning, using graphical user interfaces to generate and analyze scenarios, store assumptions, and model their impact on supply chain networks, allowing for the creation of response plans and mitigation strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple planners work sequentially on what-if scenarios, then scenario analysis can be performed, but the planning process becomes lengthy and manpower-intensive
Solution Approach 1:
The system enables self-service through automated scenario generation and analysis. The polytope analysis module automatically generates multiple what-if scenarios based on input data and assumptions, eliminating the need for multiple planners to manually create and evaluate scenarios sequentially. The system serves itself by autonomously performing the planning analysis that previously required human intervention.
Solution Approach 2:
The patent replaces the mechanical system of manual sequential planning with an automated computational system. The polytope analysis module uses algorithms to automatically generate, evaluate, and compare multiple scenarios, substituting the manual mechanical process of planners working in sequence with an automated electronic system that performs the same function much faster.
2Reliability
If multiple planners work sequentially, then scenario evaluation can be performed, but the process becomes error-prone and inefficient
Solution Approach 1:
The system incorporates feedback mechanisms where the polytope analysis module automatically evaluates scenarios against defined criteria and provides feedback on which scenarios are most promising. This automated feedback loop eliminates human error in scenario evaluation while maintaining high productivity, as the system continuously refines and compares scenarios based on quantitative criteria rather than relying on sequential human review.
3Adaptability or versatility
If what-if scenarios are considered only on planner initiative, then manual control is maintained, but important scenarios may be missed
Solution Approach 1:
The system performs preliminary action by automatically generating a comprehensive set of potential scenarios before human review. The polytope analysis module pre-generates multiple what-if scenarios based on input data and assumptions, ensuring that important scenarios are not missed due to human oversight. This automated preliminary generation expands scenario coverage while the system remains easy to operate through automated processing.
Data Source
AI summary
A system and method are disclosed for autonomously performing a polytope analysis. The method further includes autonomously identifying input for use in the polytope analysis using natural language processing techniques, performing a polytope analysis using the identified input, generating response plans based on the performed polytope analysis, displaying the generated response plans, and executing at least one of the generated response plans. The method includes where the identified input comprises assumptions, goals, and levers for a polytope analysis. The method further includes providing a GUI that is configured to perform altering, adding and removing assumptions, goals and levers. The method further includes displaying assumption data associated with the polytope analysis, where the assumption data comprises type, priority, one dates, confidence, description and scope.