Fine Blanking Rollover Prediction via Image Processing

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Solution Overview

Problem

Current methods for predicting rollover in fine blanking processes are unreliable and require extensive experimentation and computational resources, leading to increased material consumption and tooling wear, as they lack a systematic approach to accurately predict rollover before part production.

Innovation Solution

A method involving image processing techniques, including blurring of cutting contours using calibrated filters, to determine residual sheet metal thickness and predict rollover without producing actual parts or conducting complex simulations, by differentiating colors and processing color gradations to assess rollover based on material ductility.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If complex finite element simulations and experiments are used to predict rollover, then prediction reliability is improved, but computational resources and time are excessively consumed

Engineering Contradiction:

Improverollover prediction reliabilityVSAvoidprediction time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces complex mechanical finite element simulations with an image processing-based computational approach. By converting the cutting contour into a digital image and applying blurring filters, the system predicts rollover through mathematical image operations rather than physically intensive simulations, dramatically reducing computational time while maintaining prediction accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates a digital copy of the cutting contour as an image file, which serves as a surrogate for the actual physical part. This digital replica allows rollover prediction to be performed on the image data itself through filtering operations, eliminating the need for time-consuming physical experiments or complex simulations of the actual part

Inventive Principle:

Principle #26Copying

2Reliability

If starting sheet metal thickness is increased to compensate for unpredictable rollover, then part function is maintained, but material consumption increases

Engineering Contradiction:

Improvepart function reliabilityVSAvoidmaterial consumption

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The patent performs rollover prediction in advance using the image processing method before finalizing the part design and material selection. By knowing the predicted rollover depth and width from the filtered image, designers can precisely calculate the minimum required starting thickness, avoiding the conservative practice of over-specifying material thickness and thereby reducing material consumption

Inventive Principle:

Principle #10Preliminary action

3Reliability

If thicker starting material is used to account for rollover, then manufacturing robustness is improved, but tooling wear increases due to greater metal forming forces

Engineering Contradiction:

Improvemanufacturing robustnessVSAvoidtooling wear

Core Design Contradiction:

ReliabilityVSObject-generated harmful factors

Solution Approach 1:

The patent changes the approach from using thicker material as a crude compensatory measure to precisely controlling the starting thickness parameter based on predicted rollover. By optimizing the starting thickness to match the actual required thickness (starting thickness = final thickness + predicted rollover), the metal forming forces are reduced to the minimum necessary, thereby reducing tooling wear while maintaining manufacturing robustness

Inventive Principle:

Principle #35Parameter changes

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

This approach allows for accurate and rapid prediction of rollover, reducing material usage and tooling wear, enhancing design reliability and simulation accuracy by eliminating the need for complex experiments and simulations.

Implementation Method 1

In a preferred embodiment, a Gaussian filter and/or a Laplace filter are employed for the method according to the invention, which blur the cutting contour by means of gradual blending using various gray scales that correspond to the relative sheet metal thickness in comparison with the original sheet metal thickness.

Methodology Applied

Scientific EffectGaussian filter:

Implementation Method 2

Methodology Applied

Scientific EffectLaplace filter:

Data Source

PatentUS8639051B2Method for the prediction and respectively determination of the collection on a stamping part

Publication Date: 2014.01.28 FEINTOOL INTERNATIONAL HOLDING AG

AI summary

Rollover for a part generated by virtual fine blanking is predicted and determined prior to producing the part. A digital image, in particular the cutting contour of the part, is generated, provided as an image file and subjected to image analysis in an image processing device. The image analysis provides individual color gradations of the cutting contour. The gradations are associated with a residual thickness in the region of the cutting contour, so as to be indicative of rollover.