18363757. EVALUATION SITE ACCURACY CONTROL METHOD AND PRODUCTION METHOD simplified abstract (HONDA MOTOR CO., LTD.)
Contents
- 1 EVALUATION SITE ACCURACY CONTROL METHOD AND PRODUCTION METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 EVALUATION SITE ACCURACY CONTROL METHOD AND PRODUCTION METHOD - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
EVALUATION SITE ACCURACY CONTROL METHOD AND PRODUCTION METHOD
Organization Name
Inventor(s)
EVALUATION SITE ACCURACY CONTROL METHOD AND PRODUCTION METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18363757 titled 'EVALUATION SITE ACCURACY CONTROL METHOD AND PRODUCTION METHOD
Simplified Explanation
The production method described in the abstract involves using finite element analysis, regression models, Bayesian estimation, and selecting adjustment sites to produce a completed component efficiently and accurately.
- Finite element analysis is used to determine changes in evaluation sites of the completed component when displacement is applied to joining areas.
- Critical evaluation sites with significant changes are identified along with their corresponding critical joining areas.
- Regression models are generated through Lasso regression to analyze the data.
- Bayesian estimation is performed to make accurate predictions.
- Adjustment sites of individual parts are selected to optimize the production process.
- The completed component is then produced using the information gathered.
Potential Applications
This technology can be applied in various industries such as automotive, aerospace, and manufacturing where complex components need to be produced with high precision and efficiency.
Problems Solved
This method helps in identifying critical areas of a completed component that may undergo changes during production, allowing for preemptive adjustments to be made to ensure the final product meets the desired specifications.
Benefits
The use of finite element analysis, regression models, and Bayesian estimation streamlines the production process, reduces errors, and improves the overall quality of the completed component.
Potential Commercial Applications
"Optimized Production Method for Completed Components in Manufacturing"
Possible Prior Art
Prior art may include traditional production methods that do not utilize advanced technologies such as finite element analysis and regression models to optimize the production process.
What are the specific regression models used in this production method?
The abstract mentions the use of Lasso regression to generate regression models. Lasso regression is a type of linear regression that uses regularization to prevent overfitting and select the most important features in the data.
How are the adjustment sites of the individual parts selected in this production method?
The abstract states that an adjustment site of the individual parts is selected, but it does not provide specific details on the criteria or methodology used for this selection process. Further information on how these adjustment sites are determined would be beneficial for a deeper understanding of the production method.
Original Abstract Submitted
Provided is a production method for a completed component, the production method including: a first step for performing finite element analysis to determine an amount of change at evaluation sites of the completed component on a three-dimensional model of the completed component that occurs when displacement is applied to joining areas between the individual parts on the three-dimensional model; a second step for extracting combinations of critical evaluation sites having a relatively large amount of change among the evaluation sites on the three-dimensional model and their corresponding critical joining areas among the joining areas on the three-dimensional model; a third step for generating regression models through Lasso regression; a fourth step for performing Bayesian estimation; a fifth step for selecting an adjustment site of the individual parts; and a sixth step for producing the completed component.
