Parameter Configuration System Using Directed Acyclic Graphs
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Solution Overview
Problem
Current techniques for adjusting product parameters are time-consuming and often result in less than optimal settings, requiring manual trial and error from customers.
Innovation Solution
A system and method for simultaneously determining settings for multiple parameter variations by organizing them into segments, using a directed acyclic graph (DAG) to ensure consistency and optimize settings across these segments, with settings determined using algorithms that balance quality and performance characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual parameter adjustment is used, then customers can customize settings, but it results in time-consuming trial and error and less than optimal settings
Solution Approach 1:
The system pre-calculates and stores optimal settings for multiple parameter variations before the customer needs them. When a customer selects a parameter variation, the corresponding pre-determined optimal settings are automatically applied, eliminating the need for time-consuming manual trial and error adjustment while ensuring optimal performance
Solution Approach 2:
The system automatically determines and applies optimal settings based on the selected parameter variation without requiring customer intervention in the adjustment process. The automated system serves itself by identifying the appropriate settings and applying them, freeing the customer from manual adjustment while maintaining ease of operation
2Manufacturing precision
If multiple parameter variations are analyzed individually, then each setting can be optimized, but the process becomes complex and time-consuming
Solution Approach 1:
The system segments the analysis process by organizing parameter variations into distinct groups or categories. Each segment can be analyzed and optimized independently using systematic methods, reducing the overall complexity compared to analyzing all parameters simultaneously while still achieving comprehensive optimization across all parameter variations
Solution Approach 2:
The system employs systematic parameter change methodologies where settings are adjusted according to predefined patterns or relationships between parameters. By understanding how parameters interrelate and changing them in coordinated ways, the system achieves precise optimization without requiring complex ad-hoc analysis for each parameter variation
3Measurement precision
If comprehensive parameter analysis is performed, then optimal settings can be determined, but it requires significant computational resources and time
Solution Approach 1:
The system performs comprehensive parameter analysis and determines optimal settings in advance, storing the results for rapid retrieval. This pre-computation approach maintains high measurement precision for settings determination while dramatically improving productivity by eliminating the need to perform the same complex analysis repeatedly for each customer or session
Data Source
AI summary
A system, method, and computer program product are provided for simultaneously determining settings for a plurality of parameter variations. In use, a plurality of parameter variations associated with a device is identified, where the plurality of parameter variations are organized into a plurality of segments. Additionally, settings for each of the plurality of parameter variations are determined and consistency of the settings across the plurality of segments is ensured.