Voxel-Based Machining Condition Setting for Complex Workpiece Surfaces

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Solution Overview

Problem

In NC machining, inexperienced operators face difficulties in determining desired machining conditions, especially when working with complex-shaped workpieces, as existing methods rely heavily on operator experience and know-how.

Innovation Solution

A method and device that convert shape data of known workpieces into voxels, set machining conditions for each voxel, perform machine learning to determine machining conditions for target workpieces with no existing patterns, and display the conditions as visually identifiable features, allowing for automatic determination of machining conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If machining conditions are determined based on operator experience and know-how, then machining quality can be maintained for known workpiece types, but inexperienced operators cannot determine desired machining conditions for complex-shaped workpieces with no existing patterns

Engineering Contradiction:

Improvemachining condition accuracyVSAvoidapplicability to new workpiece types

Core Design Contradiction:

Manufacturing precisionVSAdaptability or versatility

Solution Approach 1:

The system performs preliminary actions by collecting machining conditions from multiple example workpieces and storing them in a database before new machining tasks are encountered. When a new complex-shaped workpiece is processed, the system retrieves and applies pre-stored machining conditions from similar example cases, eliminating the need for operators to have prior experience with every workpiece type.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of machining conditions from example workpieces and applies them to new workpieces with similar characteristics. By converting workpiece shapes into voxel representations and comparing these digital copies, the system can automatically transfer appropriate machining conditions from known examples to new complex shapes without requiring operator knowledge transfer.

Inventive Principle:

Principle #26Copying

2Adaptability or versatility

If machine learning is used to automatically determine machining conditions for target workpieces, then determination can be achieved for workpieces with no existing patterns, but the system requires conversion to voxels and processing of multiple example cases

Engineering Contradiction:

Improveability to handle new workpiece patternsVSAvoidprocessing complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system replaces the mechanical/cognitive process of operator experience-based decision-making with an automated machine learning system. The machine learning model automatically processes voxel representations of workpieces and retrieves appropriate machining conditions from the database, substituting human operator judgment with algorithmic processing that can handle any workpiece pattern without additional training.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Manufacturing precision

If machining conditions are manually set for each surface based on operator expertise, then accurate conditions can be determined for known workpieces, but the process becomes time-consuming and difficult for complex shapes

Engineering Contradiction:

Improvemachining condition accuracyVSAvoidcondition determination time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system enables self-service by automatically determining machining conditions without requiring operator intervention. The machine learning system independently processes workpiece voxel data, queries the database for matching example cases, and automatically sets appropriate machining conditions for each surface, freeing operators from time-consuming manual configuration tasks.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12138726B2Method and device for determining processing condition

Publication Date: 2024.11.12 MAKINO MILLING MASCH CO LTD

AI summary

A method is provided with a step of converting shape data (51) into a plurality of voxels (55) for each of a plurality of known objects being processed, a step of setting, for each of the known objects being processed, a processing condition for a voxel (55) constituting a processing surface, a step of using the voxel (55) of the plurality of known objects being processed and the processing condition to perform machine learning in which an input is the voxel (55) and an output is a processing condition, a step of converting shape data (52) of a candidate object being processed into a plurality of voxels (56), a step of setting, on the basis of results of machine learning, a processing condition for a voxel (56) constituting a processing surface of the candidate object being processed, and a step of determining a processing condition for each processing surface of the candidate object being processed, a processing condition that is set for the largest number of voxels (56) in one processing surface being determined as a processing condition for said processing surface.