Parameter Search Apparatus for Balancing Performance and Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing optimization algorithms struggle to simultaneously optimize manufacturing parameters for product performance and efficiency, often compromising on either performance or efficiency due to the incorporation of constraint terms into the objective function.
Innovation Solution
A parameter search apparatus that sets target performance and target parameters, constructs a model representing the objective function, and selects parameter values that satisfy both performance and efficiency criteria by balancing the objective function and constraint terms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If constraint terms are incorporated into the objective function to optimize manufacturing efficiency, then productivity improves, but the performance specifications may not be satisfied
Solution Approach 1:
The patent segments the optimization problem into two independent parts: (1) an objective function that only evaluates product performance, and (2) separate constraint conditions that evaluate manufacturing efficiency. This segmentation allows the objective function to focus solely on performance optimization while constraints handle efficiency requirements, resolving the contradiction between improving productivity and maintaining performance specification satisfaction.
Solution Approach 2:
The patent introduces a selection unit as an intermediary component that chooses from multiple candidate parameter values. This selection unit acts as a mediator between the objective function evaluation and the final parameter selection, enabling the system to satisfy both performance requirements (through the objective function) and efficiency requirements (through constraint-based filtering and selection) without compromising either aspect.
2Productivity
If the objective function is changed by incorporating constraint terms, then manufacturing efficiency is optimized, but it becomes impossible to refer to the performance of the product alone
Solution Approach 1:
The patent maintains clear segmentation between the objective function (which evaluates only product performance) and the constraint conditions (which evaluate manufacturing efficiency). This segmentation preserves the integrity and interpretability of the objective function while separately handling efficiency considerations through constraints, thus preventing loss of performance information isolation.
3Reliability
If a single point with the best objective function value is selected, then product performance is maximized, but manufacturing efficiency may be compromised
Solution Approach 1:
The patent implements a dynamic selection process where multiple candidate parameter values are generated and evaluated. Instead of directly selecting a single best point, the system dynamically filters candidates through constraint conditions and selects from multiple viable options. This dynamic approach enables balancing between performance maximization and efficiency optimization by considering multiple solutions rather than committing to a single point.
Solution Approach 2:
The patent incorporates feedback mechanisms where the selection unit evaluates multiple candidate parameter values against both the objective function and constraint conditions. This feedback loop allows the system to iteratively refine parameter selections, ensuring that both performance requirements and efficiency requirements are satisfied before finalizing the parameter values for manufacturing.
Data Source
AI summary
An apparatus sets an objective function based on a first function evaluating a parameter value based on a performance value and a second function evaluating a parameter value based on a target parameter. The apparatus calculates an objective function value by applying to the objective function a performance value corresponding to a parameter value to be evaluated and/or the performance value. The apparatus constructs a model representing the objective function based on the parameter value and the objective function value stored in a memory and determines a parameter value to be evaluated next based on the model. The apparatus selects a parameter value satisfying a criterion based on the target performance and the target parameter from the parameter value stored in a memory.