FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF

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FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF - A simplified explanation of the abstract

This abstract first appeared for US patent application 18510375 titled 'FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF

Simplified Explanation

The control method of a fastening tool involves using a camera to photograph a fastening portion of a component part, pre-processing the image to match a model image, estimating the fastening portion using a convolutional neural network algorithm, and setting a torque value based on the recognized fastening portion.

Pre-processing involves rotating the input image to match a representative model image.
Estimating the fastening portion is done through an inference process using a convolutional neural network algorithm.
Setting a torque value is based on the recognized fastening portion when the probability value exceeds a predetermined reference ratio.

Potential Applications

This technology can be applied in manufacturing industries where accurate and efficient fastening of component parts is crucial, such as automotive assembly lines, electronics manufacturing, and aerospace engineering.

Problems Solved

1. Ensures accurate and consistent fastening of component parts. 2. Reduces the risk of human error in fastening processes.

Benefits

1. Improved quality control in fastening operations. 2. Increased efficiency and productivity in assembly processes. 3. Enhanced precision in torque application.

Potential Commercial Applications

Optimizing Torque Control Method for Fastening Tools in Manufacturing Industries

Possible Prior Art

There may be prior art related to computer vision systems for quality control in manufacturing processes, as well as torque control methods for fastening tools.

What are the potential limitations of this technology in real-world applications?

The abstract does not mention any potential limitations of this technology. However, in real-world applications, challenges such as environmental factors affecting image quality, calibration issues, and the need for regular maintenance of the system could arise.

How does this technology compare to existing methods of fastening tool control?

The abstract does not provide a direct comparison to existing methods of fastening tool control. However, this technology appears to offer a more automated and precise approach to fastening tool control compared to traditional manual methods.

Original Abstract Submitted

A control method of a fastening tool for fastening a component part includes photographing a fastening portion of the component part through a camera portion mounted on the fastening tool. The control method includes pre-processing that rotates an input image, which has been photographed by the camera portion, to match with representative model image. The control method includes estimating the fastening portion through an inference process through a convolutional neural network (CNN) algorithm-based image classification work on a video input image of a same fastening portion finished with the pre-processing work. The control method also includes setting a torque value that is matched with a recognized fastening portion when a probability value of the fastening portion in the inference process exceeds a predetermined reference ratio.

18510375. FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF simplified abstract (HYUNDAI MOTOR COMPANY)

Contents

FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF

Organization Name

Inventor(s)