Case Studies and Method Explanations of AI Utilization Using Time Series Anomaly Detection Applications (Held on November 25, Friday)
伊東商会
In the manufacturing field, where continuous improvement in productivity and quality assurance is required, efforts utilizing AI are accelerating to quickly detect equipment malfunctions or failures and to prevent issues such as the occurrence of defective products.
Various sensors and devices can be installed on production equipment and machinery, allowing for the acquisition of time-series data on measurement values and control parameters. The anomaly detection solution Impulse's "Anomaly Detection App" uses such time-series data to detect unknown anomalies by leveraging AI technology, rather than relying on traditional threshold-based systems, while the "Cause Analysis App" can analyze the factors leading to anomalies.
In this webinar, we will introduce case studies of time-series data analysis utilizing AI technology, and from those, we will pick up two specific cases to explain the creation and analysis methods of anomaly detection models using actual screens and data, along with demonstrations.
- Detection of precursors to plant equipment failures
- Analysis of defect factors in the injection molding process of automotive parts manufacturing
| Date and time | Friday, Nov 25, 2022 01:00 PM ～ 01:40 PM |
|---|---|
| Entry fee | Free |
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