Machining Parameter Search Using Simulation and Preference Learning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing parameter adjustment methods for machine tools require significant time and effort to converge on a worker's preference, often necessitating trial and error, and fail to maintain accuracy when the workpiece shape differs from the test program.
Innovation Solution
A parameter adjustment device that includes a feature calculation unit, evaluation index calculation unit, and a first optimal solution search unit to simulate machining operations, infer evaluation index values, and search for parameter sets that optimize machining results in line with worker preferences, using a neural network to learn and adjust parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional trial-and-error parameter adjustment methods are used, then parameter adjustment can be performed, but the adjustment process requires huge amount of time and repeated trial and error
Solution Approach 1:
The patent creates a virtual copy of the machining process through simulation, allowing parameter adjustment to be performed on the virtual model rather than through repeated physical trial-and-error. The simulation system replicates the machining behavior digitally, enabling fast evaluation of multiple parameter sets without actual machining time consumption.
Solution Approach 2:
The patent performs preliminary simulation and evaluation of parameter sets before actual machining. By pre-evaluating multiple parameter combinations through the virtual machining system, the optimal parameters are determined in advance, avoiding time-consuming trial-and-error during actual production.
2Measurement precision
If test programs are changed repeatedly to maintain accuracy for different workpiece shapes, then parameter adjustment accuracy is maintained, but the adjustment work must be restarted from the first step
Solution Approach 1:
The patent creates a universal simulation system that can handle different workpiece shapes and machining conditions through a single integrated platform. The virtual machining system is designed to be shape-agnostic, allowing the same system to accurately simulate various workpiece geometries without requiring separate test programs or restarting the adjustment process.
Solution Approach 2:
The patent utilizes parameter changes in the simulation model to adapt to different workpiece shapes. By modifying the input parameters and geometric data in the virtual machining system, the same simulation framework can accurately represent different workpiece configurations, maintaining parameter adjustment accuracy across varying shapes without restarting the process.
3Adaptability or versatility
If a large number of parameters are adjusted to accommodate different machining priorities, then machining preferences can be satisfied, but the adjustment process becomes complicated
Solution Approach 1:
The patent implements a feedback mechanism where the simulation system evaluates machining results based on predefined priorities (cycle time, machining accuracy, surface quality) and provides feedback on parameter performance. This automated feedback loop guides the parameter adjustment process, reducing complexity by systematically identifying optimal parameters based on machining priorities rather than requiring manual adjustment of numerous parameters.
Solution Approach 2:
The simulation system performs self-evaluation of parameter sets based on machining priorities. Instead of requiring operators to manually adjust and evaluate numerous parameters, the system automatically assesses parameter performance against the specified priorities and identifies optimal settings, reducing the complexity of parameter adjustment while maintaining adaptability to different machining preferences.
Data Source
AI summary
In a parameter adjustment device, the feature calculation unit calculates a feature of machining by simulating an operation of a machine tool from the tool travel command. The evaluation index calculation unit calculates evaluation index values for evaluating a machining result from the feature of machining. The first optimal solution search unit infers the evaluation index values corresponding to a first search command value generation parameter set by using a first learning result, and, by using a result of the inference, searches for command value generation parameter set candidates that simultaneously optimize the respective evaluation index values. The display control unit displays the feature of machining calculated when the command value generation parameter set candidates are set on a command value generation device that generates the tool travel command, and the respective evaluation index values.