Camera-Guided Workpiece Sorting on Flatbed Machine Tables
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Solution Overview
Problem
The existing methods for sorting workpieces produced by flatbed machine tools, such as laser cutting or punching, are time-consuming and prone to errors, especially when dealing with a large variety of parts, as they rely on visual comparison and paper-based systems, which become inefficient and error-prone, especially for small or complex parts.
Innovation Solution
Implementing a method that uses cameras to detect and image the sorting table, generating image data sets before and after workpiece removal, and comparing these to a processing image data set to generate a sorting signal containing information about the type, position, and shape of the removed workpiece, which is then used to support the sorting process by guiding the operator to the correct placement and monitoring the operation, thereby reducing errors and increasing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If visual comparison with paper-based drawings is used for sorting workpieces, then the sorting process can be performed with simple equipment, but the sorting time increases and error rate increases especially when dealing with many different part forms
Solution Approach 1:
The patent replaces the mechanical visual comparison process with an optical imaging system. A camera captures images of workpieces on the sorting table, and image processing algorithms automatically identify and classify parts, substituting the operator's visual inspection with automated optical-mechanical systems.
Solution Approach 2:
The patent creates digital copies of workpieces through camera imaging. Instead of comparing physical parts against paper drawings, the system captures optical images of actual workpieces and processes these digital copies to identify part types, enabling faster and more accurate sorting.
2Device complexity
If visual comparison with paper-based drawings is used for sorting workpieces, then the equipment remains simple, but the error rate increases especially when dealing with many different part forms
Solution Approach 1:
The patent replaces the mechanical visual comparison process with an optical imaging system. A camera captures images of workpieces on the sorting table, and image processing algorithms automatically identify and classify parts, substituting the operator's visual inspection with automated optical-mechanical systems.
Solution Approach 2:
The system provides feedback by comparing captured images with reference data and generating sorting signals that indicate the identified part type and its intended destination. This automated feedback loop eliminates human error in part identification and sorting decision-making.
3Ease of operation
If projector markings are used to simplify workpiece sorting, then visual identification is improved, but the markings become difficult to recognize when workpieces are very small
Solution Approach 1:
Instead of marking the workpieces with projectors as in conventional methods, the patent inverts the approach by using the workpieces themselves (or their positions) as the information carriers. The camera captures the actual workpieces or their locations on the sorting table, and the system extracts identification information directly from these images without requiring additional markings.
4Reliability
If repeated imaging and comparison of sorting table is performed, then real-time sorting support is achieved, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary imaging of the sorting table to capture the initial state before workpieces are removed. This preliminary action establishes a reference state that enables rapid comparison with subsequent images, reducing the computational burden during real-time sorting operations.
Solution Approach 2:
The patent implements selective imaging and comparison, skipping redundant processing steps. Instead of continuously processing all image data, the system focuses on detecting changes between sequential images and only processes relevant differences, rushing through unnecessary computational steps to minimize processing time.
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 significantly reduces errors and increases efficiency in the sorting process by providing real-time guidance and feedback, allowing for faster and more accurate sorting of workpieces, even for complex or small parts, and enables integration into intelligent factory systems for improved production flow.
Implementation Method 1
imaging based detecting of the sorting table with a plurality of workpieces arranged spatially next to one another and generation of a first sorting image data set
Data Source
AI summary
A method for supporting a sorting process of workpieces arranged on a sorting table that have been produced on a machine tool by a processing plan, comprising providing of a processing image data set of the processing plan based on the arrangement of at least one workpiece. The method further relates to an imaging-based capturing of the sorting table having a plurality of adjacent workpieces to each other and generating a first sorting image data set, and repeated image-based capturing of the sorting table and generating of a second sorting image data set once at least one workpiece has been removed from the sorting table. The method comprises comparing of the sorting image data sets, incorporating the processing image data set, wherein a sorting signal is generated which contains information that comprises the type, the position and/or the shape of the at least one removed workpiece.