Container Labeling Rotation Control Using Manual Reference Position
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing labeling machines require complex operator input for determining container rotation curves, leading to susceptibility to errors and high expertise demands.
Innovation Solution
A labeling machine with a control unit that determines and controls container rotation based on a manually set rotational position, simplifying the process by allowing operators to easily set positions and automatically calculate necessary rotations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If complex procedures are used to determine rotation curves based on numerous entered positions, then labeling quality and position requirements can be met, but operator workload and susceptibility to errors increase
Solution Approach 1:
The system automatically determines the rotation curve by capturing images of the container at different positions and using image recognition to identify features and calculate the required rotation. This eliminates the need for manual entry of rotation positions by the operator, reducing workload while maintaining precision
Solution Approach 2:
The manual mechanical process of entering rotation positions is replaced with an automated optical system using cameras and image processing algorithms. The system captures images, processes them computationally, and automatically generates the rotation curve without human intervention
2Manufacturing precision
If complex procedures are used to determine rotation curves, then labeling position requirements can be met, but the system becomes more susceptible to errors
Solution Approach 1:
The system performs self-measurement by automatically capturing and processing images to determine the rotation curve. This eliminates human error in manual data entry and calculation, improving reliability while maintaining the precision needed for correct label positioning
Solution Approach 2:
The system uses image feedback from cameras to continuously monitor and adjust the rotation curve determination. By comparing actual container features captured in images with expected positions, the system can automatically correct deviations and ensure accurate labeling while reducing error susceptibility
3Measurement precision
If manual rotation position entry is required for each container, then precise rotation control can be achieved, but the process becomes more complex and requires high operator expertise
Solution Approach 1:
The complex manual process of entering rotation positions is replaced with automated image capture and computational processing. Cameras capture container images at multiple positions, and software algorithms automatically determine the rotation curve, simplifying the overall process while maintaining measurement precision
Solution Approach 2:
An image processing intermediary system is introduced between the container and the rotation control mechanism. The system captures images, processes them to extract geometric features, and uses this information to calculate the rotation curve, thereby simplifying the control process while maintaining precision
Data Source
Figure 1
Figure 2
AI summary
Labeling machine (100) for labeling containers (130), the labeling machine (100) comprising a container holder (111) for rotatably receiving a container (130) and for transporting the container (130) along a transport direction (T), a functional component (121-124) for performing a function associated with labeling the container (130) at a position of the container (130) along the transport direction (T), and a control unit (180), wherein the control unit (180) is configured to determine a necessary rotation of the container (130) and to control the rotation of the container (130) based on a manually set rotational position of the container (130) in the holder at the position.