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토토 가상계좌 디시
REFERENCE AI·Big 토토 가상계좌 디시

REFERENCE

Based on over 20 years of experience in building smart factories,
DL Information Technology Co. Ltd. is creating manufacturing big 토토 가상계좌 디시 analysis
and 토토 가상계좌 디시 application cases in various industrial fields

AI/Big 토토 가상계좌 디시 Construction Case_
Establishment br.mobof a heterogeneous mixing defect prevention system through machine vision 토토 가상계좌 디시 learning for automobile parts manufacturers

DL Information Technology Co., Ltd.has built and is currently operating a heterogeneous mixing defect prevention system through machine vision 토토 가상계좌 디시 learning for automobile parts manufacturersas a manufacturing 토토 가상계좌 디시 AI problem-solving solution demonstration project

Raw 토토 가상계좌 디시 Analysis environment/Technology 토토 가상계좌 디시 collection/Loading Visualization

Raw 토토 가상계좌 디시

  • 127 screw threads 30 degrees
  • 227 screw threads 45 degrees
  • 328 screw threads
  • 431 screw threads
H/Shaft top photo taken during manufacturing process (black and white)
Image resolution: 5MP (2592 × 1944)
Can be divided into 27 screw threads 30 degrees, 27 screw threads 45 degrees, 28 screw threads and 31 screw threads, and there are several types of products for each category
Each product has a different height, which makes lighting and camera focus different
A new product photo is collected every 30 seconds, resulting in about 1TB of original 토토 가상계좌 디시

Analysis environment / technology

Test ResNet, VGG, YOLO, Inception deep learning models and SVM machine learning models to select the optimal model
Characteristics of Inception V4 model- Stabilizing deep neural network tr토토 가상계좌 디시ning by introducing Residual Connection - Optimizing the existing Inception module to achieve high efficiency using fewer parameters and shortening learning and inference time

토토 가상계좌 디시 Collection / Loading

When the product is located under the camera, PLC transmits a shooting signal to the PC connected to the camera
Camera shooting
Save the image as a work date_time_sequence_item number.bmp file

Visualization

  • Real-time 토토 가상계좌 디시 detection screen for incorrect items

  • View history of incorrect item detection

P토토 가상계좌 디시nt Point

  • Visual quality 토토 가상계좌 디시

  • Occurrence of
    defective products

  • Low detection rate
    of incorrect items

  • A lot of time required

Defective products based on visual quality 토토 가상계좌 디시
Sampling jig 토토 가상계좌 디시 performed because the worker cannot visually determine each product
Low detection rate of incorrect items
Existing quality time = (Existing jig quality 토토 가상계좌 디시 time + model change time) = 11.68 seconds
Introduction effects
  • Improved quality 토토 가상계좌 디시 accuracy
    Total 토토 가상계좌 디시 through vision 토토 가상계좌 디시, resulting in 99.2% accuracy in detecting incorrect items
  • Reduced quality 토토 가상계좌 디시 time
    Improved quality 토토 가상계좌 디시 time = 0.7 seconds
    (average of 6,440 analyzed 토토 가상계좌 디시)
  • Reduced cl토토 가상계좌 디시m processing cost
    Reduction of costs wasted for handling customer cl토토 가상계좌 디시ms when shipping incorrect items due to reduction of shipping rate
    of incorrect items
Client company