에 의해서 webmaster | 1월 16, 2025 | Predictive Maintenance
Detecting Inspection Data Drift Caused by Material Changes: A Case Study on the Data Quality Index (DQI) Model Challenge In manufacturing, consistently capturing high-quality optical images is essential for training machine learning models and ensuring high...
에 의해서 webmaster | 1월 16, 2025 | Predictive Maintenance
Predicting Motor Failures with Vibration Sensor Data (Predictive Maintenance) Challenge Previously, vibration sensors were installed on power plant motors, and inspections were conducted based on predefined rules. However, since the specific influence of each...
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...
