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
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 | 11월 28, 2023 | Smart Manufacturing, AHHA Labs' products, AI, Data
Embracing the Future: Why Data CAMP Outshines Traditional SCADA 4 Limitations of Traditional SCADA Software: What is SCADA Software? Supervisory Control and Data Acquisition (SCADA) systems utilized in smart factories are critical for manufacturers. They enable...
에 의해서 Chloe Woo | Content Strategist | 11월 21, 2023 | Data, Smart Manufacturing, en
Navigating the Future: Unleashing the Potential of Digital Twin Technology in Manufacturing The concept of Digital Twin has recently emerged as a core technological trend in the manufacturing industry. As the product life cycle becomes shorter and predicting product...
