Low-Toughness Workpiece Cutting With Fracture Defect Prediction

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Solution Overview

Problem

Cutting low toughness materials like intermetallic compounds and ceramics is challenging due to their brittleness, leading to high defect rates during milling processes, as existing methods struggle to predict and prevent defects effectively.

Innovation Solution

A defect prediction device and method that analyzes tool, material, and cutting data to simulate deformation and fracture, predicting defect occurrence by comparing surface energy and strain energy changes, and adjusting cutting parameters to prevent defects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If the feed amount increases during milling of intermetallic compounds, then cutting force increases and process efficiency improves, but likelihood of defect increases due to material brittleness

Engineering Contradiction:

Improvecutting efficiencyVSAvoiddefect occurrence rate

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system performs preliminary analysis of deformation and fracture before the actual cutting process by calculating strain energy and surface energy using finite element method. This allows prediction of defect occurrence in advance, enabling optimization of cutting parameters (feed amount, cutting speed, depth of cut) before machining begins, thus preventing defects while maintaining high cutting efficiency

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system establishes a feedback loop where cutting parameters are adjusted based on predicted defect likelihood. The analysis results feed back into the cutting parameter selection process, allowing continuous optimization of the cutting conditions to balance cutting efficiency and defect prevention during the machining of intermetallic compounds

Inventive Principle:

Principle #23Feedback

2Reliability

If the feed amount decreases to reduce defect likelihood, then material brittleness is better managed, but process efficiency decreases

Engineering Contradiction:

Improvedefect occurrence rateVSAvoidcutting efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system changes multiple cutting parameters simultaneously (feed amount, cutting speed, depth of cut) based on the predicted defect likelihood. Rather than simply reducing feed amount which lowers efficiency, the system optimizes the combination of parameters to achieve high efficiency cutting while maintaining low defect rates through scientifically determined parameter sets

Inventive Principle:

Principle #35Parameter changes

3Ease of manufacture

If conventional milling processes are used on low toughness materials, then existing equipment and methods are utilized, but defect prediction and prevention capabilities are insufficient

Engineering Contradiction:

Improveprocess simplicityVSAvoiddefect prediction accuracy

Core Design Contradiction:

Ease of manufactureVSReliability

Solution Approach 1:

The system replaces conventional empirical milling processes with a computer-based simulation and prediction system. Using finite element method and energy-based fracture criteria, the system substitutes trial-and-error mechanical testing with theoretical calculations that accurately predict defect occurrence, enabling precise control of cutting parameters before actual machining

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables prediction and prevention of defects in low toughness materials during cutting, improving process efficiency and reducing defect rates by optimizing cutting conditions based on fracture mechanics principles.

Implementation Method 1

performs, based on the tool data, the cutting data and the material data, an analysis of deformation of the workpiece due to a cutting force and an analysis of fracture due to the deformation

Methodology Applied

Scientific EffectFracture mechanics: Fracture Mechanics

Implementation Method 2

performing a prediction of an occurrence of defect and/or a non-occurrence of defect of the workpiece due to the cutting process

Methodology Applied

Scientific EffectEnergy analysis:

Data Source

PatentUS12197197B2Low toughness workpiece cutting apparatus, low toughness workpiece manufacturing method and recording medium storing low toughness workpiece manufacturing program

Publication Date: 2025.01.14 MITSUBISHI HEAVY IND LTD

AI summary

A low toughness workpiece cutting apparatus, a low toughness workpiece manufacturing method and a low toughness workpiece manufacturing program for predicting an occurrence of defect and/or non-occurrence of defect before a cutting process of low toughness material. A defect prediction device is provided with a storage device, a processor and an interface. The storage device stores tool data that represent physical characteristics and a shape of a tool, cutting data that represent a group of parameters of a cutting process to be performed to a workpiece by use of the tool and material data that represent physical characteristics and a shape of the workpiece. The processor performs an analysis of deformation of the workpiece due to a cutting force and an analysis of fracture due to the deformation, and performs a prediction of an occurrence of defect and/or a non-occurrence of defect of the workpiece due to the cutting process.