Screening Design Generation for Complex System Factor Identification
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Solution Overview
Problem
In complex systems, identifying the specific combination of options or factors that lead to failures is challenging due to the difficulty in visualizing and analyzing multiple components and their interactions, especially when there are numerous factors involved.
Innovation Solution
A computer-program product is provided that generates an updated screening design for an experiment by selecting initial and modified screening designs based on criteria such as efficiency, metric N, and quantity p, to identify active factors affecting the outcome, and outputs an indication of the most likely potential cause for a failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a test suite is constructed to represent different test cases for multiple components in a complex system, then the ability to test different combinations of configurable options is improved, but the difficulty of visualizing and analyzing the options and results increases
Solution Approach 1:
The patent segments the complex system into individual components, each with their own configurable options. The test suite is divided into test cases that systematically combine these options. This segmentation allows the testing coverage to be improved while managing complexity by breaking down the overall system into manageable parts that can be analyzed separately.
2Reliability
If the number of factors in an experiment is increased to comprehensively test a complex system, then the completeness of testing is improved, but the difficulty of identifying active factors affecting the outcome increases
Solution Approach 1:
The patent employs partial action by using screening designs that test a selected subset of all possible factor combinations rather than exhaustively testing every combination. This approach achieves sufficient testing completeness for identifying active factors without the prohibitive complexity of complete enumeration, applying the principle of doing enough rather than everything.
3Productivity
If a screening design is used to identify active factors in an experiment, then the efficiency of identifying active factors is improved, but the ability to comprehensively test all factor combinations is reduced
Solution Approach 1:
The patent extracts and focuses on identifying the most influential active factors from the complete set of factors using screening designs. Rather than attempting to analyze all factors equally, the methodology extracts the subset of factors that have the greatest impact on the outcome, achieving efficient identification of active factors while maintaining sufficient testing completeness for practical purposes.
Data Source
AI summary
A computing device obtains a metric N indicating a quantity of a plurality of test cases for an output design of an experiment Each element of a test case of the output design is a test condition for testing one of factors for the experiment. The computing device obtains input indicating a quantity p of an indicated plurality of factors for the output design. The computing device determines whether there are stored instructions for generating an initial screening design for the experiment. The computing device responsive to determining that there are stored instructions, selects, using the stored instructions, the initial screening design for the experiment. The computing device determines whether to modify the initial screening design based on modification criteria comprising a secondary criterion, the metric N, and/or the quantity p. The computing device outputs an indication of the updated screening design for the output design of the experiment.