18510375. FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF simplified abstract (KIA CORPORATION)

FASTENING TOOL SYSTEM AND CONTROL METHOD THEREOF

Organization Name

KIA CORPORATION

Inventor(s)

Tae Mun Hwang of Jeonju-si (KR)

DongHa Jeong of Uiwang-si (KR)

Byung Cheol Song of Seoul (KR)

Dong Yoon Choi of Seosan-si (KR)

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 photographing a fastening portion of a component part, pre-processing the image, estimating the fastening portion using a CNN algorithm, and setting a torque value based on the recognized fastening portion.

• Photographing of fastening portion through camera mounted on fastening tool
• Pre-processing: Rotating input image to match representative model image
• Estimating fastening portion through CNN algorithm-based image classification
• Setting torque value based on recognized fastening portion

Potential Applications

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

Problems Solved

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

Benefits

1. Increases efficiency and productivity in assembly processes 2. Improves quality control by ensuring proper fastening of parts 3. Enhances worker safety by reducing the risk of improperly fastened parts

Potential Commercial Applications

Optimizing Torque Control System for Component Fastening in Manufacturing

Possible Prior Art

There may be prior art related to computer vision systems used in manufacturing processes to ensure accurate assembly and fastening of parts.

Unanswered Questions

How does this technology impact the overall cost of manufacturing processes?

The article does not delve into the cost implications of implementing this technology in manufacturing operations. It would be interesting to explore whether the initial investment in such a system is offset by long-term savings in terms of reduced errors and improved efficiency.

What are the potential cybersecurity risks associated with using a control method that relies on image processing and neural networks?

The article does not address the cybersecurity aspects of implementing this technology. It would be important to consider potential vulnerabilities in the system that could be exploited by malicious actors.

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.