에 의해서 Chloe Woo | Content Strategist | 7월 4, 2024 | Predictive Maintenance
A successful case of reducing ‘false-positives’ by applying a deep learning model to detect ‘type 1 errors’ Challenge If the test standard is set too sensitively to achieve 0% ‘false-negative’, ‘false-positive (type 1 error)’ increases. Inefficiency due to...
에 의해서 Chloe Woo | Content Strategist | 7월 3, 2024 | Predictive Maintenance
Success case of monitoring ‘data drift’ and performing predictive maintenance with a data quality index (DQI) model Challenge Consistent optical images must be taken at all times to properly train the model and increase the accuracy of quality...
에 의해서 Chloe Woo | Content Strategist | 7월 3, 2024 | Predictive Maintenance
Configuring an AI model pipeline to detect robotic grasping anomalies in real time Challenge Robot drops battery, causing downtime Difficulty utilizing existing machine learning solutions due to ‘class imbalance’ problem Difficulty treating footage...
에 의해서 Chloe Woo | Content Strategist | 7월 3, 2024 | Quality Control
How the Anomaly Detector model was used to automate the quality control process using only normal data Challenge Pouch-type batteries have flexible surface geometry, complicating defect identification. This makes it challenging to use existing rule-based...
에 의해서 Chloe Woo | Content Strategist | 12월 14, 2023 | Quality Control
Implementing Quality Control in Multi-Product Small-Batch Production through the Utilization of Data CAMP’s ‘RECIPE’ feature 1. Challenge Managing Varied Quality Standards for Each Model without a Centralized History View The latest trend in...
에 의해서 Chloe Woo | Content Strategist | 12월 14, 2023 | Quality Control
[Case Study] Data Integration: Managing Inspection Data by Barcode Number for a Secondary Battery Manufacturer with Data CAMP 1. Challenge Lack of a production history management solution to manage product inspection data by barcode number In 2015, the introduction of...
