18281718. WIRE BONDING DEFECT DETECTION APPARATUS AND OPERATION METHOD THEREOF simplified abstract (LG Energy Solution, Ltd.)
Contents
- 1 WIRE BONDING DEFECT DETECTION APPARATUS AND OPERATION METHOD THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 WIRE BONDING DEFECT DETECTION APPARATUS AND OPERATION METHOD THEREOF - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
WIRE BONDING DEFECT DETECTION APPARATUS AND OPERATION METHOD THEREOF
Organization Name
Inventor(s)
WIRE BONDING DEFECT DETECTION APPARATUS AND OPERATION METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 18281718 titled 'WIRE BONDING DEFECT DETECTION APPARATUS AND OPERATION METHOD THEREOF
Simplified Explanation
The patent application describes an apparatus and method for detecting bonding defects during an ultrasonic wire bonding process between a battery cell and a busbar. The system collects ultrasonic bonding parameters continuously, performs machine learning training using a convolutional neural network, and detects bonding defects based on the collected data.
- Bonding parameter collector continuously collects ultrasonic bonding parameters during the wire bonding process.
- Machine learning training is performed using a convolutional neural network to analyze the collected data.
- Bonding defects are detected based on the analysis of the ultrasonic bonding parameters.
Potential Applications
This technology can be applied in the manufacturing of battery cells to ensure the quality and reliability of the bonding process.
Problems Solved
This technology helps in detecting bonding defects early in the process, preventing potential failures in battery cells due to poor bonding.
Benefits
- Improved quality control in the manufacturing process - Early detection of bonding defects leads to increased reliability of battery cells
Potential Commercial Applications
"Quality Control System for Battery Cell Bonding Process"
Possible Prior Art
There are existing systems for monitoring bonding processes, but the use of machine learning algorithms for defect detection in ultrasonic wire bonding processes is a novel approach.
Unanswered Questions
How does the system differentiate between normal variations in bonding parameters and actual defects?
The system likely uses a threshold or pattern recognition to distinguish between normal variations and defects.
What is the accuracy rate of defect detection using this system?
The accuracy rate would depend on the training data and the performance of the convolutional neural network.
Original Abstract Submitted
An apparatus and method are disclosed for detecting a bonding defect occurring during an ultrasonic wire bonding process between a battery cell and a busbar connected to each other by ultrasonic wire bonding. A bonding parameter collector, coupled to an ultrasonic wire bonding machine, may collect ultrasonic bonding parameters continuously during the ultrasonic wire bonding process, machine learning training may be performed by a convolutional neural network, and a bonding defect may be detected based thereon.
