Correlating Maximum Configuration Data Sets for Multi-Model Validation
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Solution Overview
Problem
Manufacturers of complex products face challenges in maintaining consistency across various data stores due to differing data structures, naming conventions, and version control practices, leading to errors and increased costs in manufacturing and post-sale operations.
Innovation Solution
A method and system that enhance data set definitions to accommodate multiple product configurations, using a processor to apply matching algorithms and effectivity expressions to identify perfect and partial matches between data sets, enabling comparisons across unlike data models and structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data comparison methods are used between like units of the same product model, then comparison accuracy is maintained, but the scope of comparison is limited and productivity is reduced
Solution Approach 1:
The patent creates a universal comparison framework that can handle both like and unlike product models through maximum configuration data sets. The system compares actual configuration data against a comprehensive maximum configuration that encompasses all possible variations, enabling one comparison operation to validate multiple product models simultaneously while maintaining accuracy through effectivity expressions that account for model-specific differences.
Solution Approach 2:
The patent introduces a new dimensional approach by creating maximum configuration data sets that represent all possible product configurations across multiple models. This transforms the comparison from a one-to-one unit comparison to a many-to-one comparison against a comprehensive configuration space, enabling validation of unlike models through a unified comparison dimension.
2Measurement precision
If one-to-one comparisons are performed between individual units, then comparison accuracy is maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent merges multiple individual comparison operations into a single batch comparison operation. By consolidating configuration data from multiple units and models into a unified data set that is compared against a maximum configuration, the system achieves the accuracy of individual comparisons while executing all validations simultaneously, dramatically reducing total comparison time and resource consumption.
Solution Approach 2:
The patent performs preliminary actions by pre-defining maximum configuration data sets that contain all possible configuration variations before actual product comparisons are needed. This preparatory work enables rapid validation of multiple products without requiring complex real-time analysis, as the comparison framework is already established with all reference configurations in place.
3Adaptability or versatility
If data stores maintain different data structures and naming conventions, then organizational flexibility is improved, but data consistency and reliability deteriorate
Solution Approach 1:
The patent introduces maximum configuration data sets as an intermediary layer between diverse organizational data stores. This mediator translates and harmonizes different data structures, naming conventions, and formats into a unified comparison framework, allowing organizations to maintain their flexible, decentralized data storage approaches while ensuring consistency through standardized comparison against the maximum configuration reference.
Solution Approach 2:
The patent dynamically adjusts comparison parameters through effectivity expressions that adapt to different data structures and models. The system modifies comparison criteria, data mapping, and validation rules based on the specific characteristics of each data store being compared, enabling consistent reliability assessment across diverse organizational systems without requiring uniform data structures.
Data Source
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AI summary
A method of correlating data for multiple product configurations is provided comprising enhancing, by a processor, data set definition to accommodate data models of data sets describing multiple product configurations. The method also comprises comparing, by the processor, values of the data sets utilizing at least one matching algorithm and effectivity expressions identifying relevant rows for comparison in the data sets. The method also comprises enhancing, by the processor, the at least one matching algorithm to identify perfect and partial matches between the data sets wherein values of all data contained in the data sets are compared in one single operation comprising simultaneous validation of engineering data for the multiple product configurations.