Diagnostic Matrix Evaluation for Unambiguous Component Defect Pinpointing
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Solution Overview
Problem
Current diagnostic methods for motor vehicle components lack efficiency in determining whether a defect is unambiguously identifiable through predefined diagnostic options, leading to subjective evaluations and incomplete troubleshooting processes.
Innovation Solution
A method and device that utilize a matrix of numerical parameters to assess the pinpoint capability of diagnostic options by selecting relevant rows and calculating a result vector through element-wise multiplication, allowing for automated evaluation and unambiguous identification of defects, thereby eliminating human discretion and enabling dynamic generation of guided troubleshooting processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated evaluation using matrix calculation is implemented, then objectivity and completeness of diagnostic evaluation are improved, but device complexity increases
Solution Approach 1:
The patent replaces subjective human evaluation with automated mathematical calculation. A calculation device computes a result vector by element-wise multiplication of matrix rows corresponding to diagnostic options, objectively determining pinpoint capability without human discretion. This substitution of mechanical/mathematical system for human judgment resolves the contradiction by providing reliable, objective evaluation while managing complexity through algorithmic automation.
Solution Approach 2:
The patent transforms the diagnostic evaluation problem into a mathematical parameter-based system. By representing diagnostic options and defects as matrix rows and columns with numerical parameters, and computing a result vector through element-wise multiplication, the system objectively determines pinpoint capability. This parameter transformation enables automated, consistent evaluation that improves reliability while the structured mathematical approach manages system complexity.
2Reliability
If comprehensive diagnostic options analysis is performed, then diagnostic capability quality is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary analysis by pre-organizing diagnostic options and defects in a matrix structure with numerical parameters before actual defect diagnosis. This preliminary setup enables rapid automated evaluation during actual use, as the calculation device can quickly compute result vectors without performing comprehensive analysis from scratch each time. The upfront structuring reduces time loss during actual diagnostic operations while maintaining comprehensive evaluation quality.
Solution Approach 2:
The patent creates a mathematical model (matrix with result vector) that copies and represents the complex diagnostic relationships in a simplified computational form. Instead of performing comprehensive diagnostic analysis directly on physical systems, the system uses this mathematical copy to evaluate pinpoint capability rapidly. This copying approach maintains diagnostic quality while significantly reducing the time required for defect identification.
3Productivity
If automated diagnostic evaluation is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent replaces manual diagnostic evaluation with automated calculation using a processing device. The device automatically computes result vectors by element-wise multiplication of matrix rows, determining pinpoint capability without human intervention. This automation dramatically improves productivity by eliminating manual analysis time, while the standardized mathematical algorithm manages complexity through systematic computation rather than ad-hoc procedures.
Data Source
AI summary
A device for determining whether a defect of a component is determinable based on results of predefined diagnostic options, including: storing, in a matrix, parameters which, for each combination of one component defect and one diagnosis result, provide a measure of whether the respective defect is possible for the respective diagnosis result, the matrix rows being assigned to one of the diagnosis results, the matrix columns being assigned to one of the defects; selecting at least two matrix rows which, for a diagnosis result consistent with the defect to be identified, include a parameter greater than a predefined first limiting value; calculating a result vector by the element-wise multiplication of the selected matrix rows; and determining whether the result vector includes at least one element not smaller than a predefined second limiting value, the result vector elements, which are smaller, not being greater than a predefined third limiting value.