Automatic judgment of waveform characteristics obtained with an oscilloscope using AI! Automating the visual judgment work of engineers with "Waveform meister."
Do you have any of the following concerns? ● It takes time to check waveforms ● Past judgment results are not shared ● There is variability in waveform checks ▼ Leave it to our automatic waveform characteristic judgment tool, Waveform Meister! ――Features――――――――――――――――― ◆ Reduces the time for waveform checks with automatic judgment ◆ Eliminates variability with expert judgment models ◆ Adds past judgment results to the judgment model ―――――――――――――――――――――― Waveform Meister is an AI platform specialized in waveform characteristic judgment, providing a package for learning, evaluation, and judgment. In LSI development, electrical characteristic evaluation and waveform confirmation using oscilloscopes relied heavily on visual judgment by engineers for large amounts of waveform data. Waveform Meister enables rapid abnormal judgment, characteristic classification, and specific waveform detection regardless of engineers' skill levels, contributing to the efficiency and quality improvement of the development process.
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■What is Waveform Meister? This product is an AI platform specialized in waveform characteristic assessment, providing a packaged solution for learning, evaluation, and judgment. As an optional service using Waveform Meister, we also offer "Waveform Insight," which assists developers by providing "cause explanations" for anomalies detected in data (waveforms) obtained from oscilloscopes, as well as "remedial methods" to resolve abnormal conditions. ■Features of the Automatic Waveform Characteristic Assessment Tool - AI makes judgments instead of technicians - Capable of assessing multiple waveforms simultaneously - Provides learning, evaluation, and judgment on the same platform - Supports input in image data and numerical data - Can be integrated into existing evaluation test systems for automated judgment - Supports supervised and unsupervised learning ■Waveform Meister Execution Procedure INPUT waveform data ▼ ―Waveform Meister ―― 1. Data Learning 2. Judgment Accuracy Evaluation 3. Data Judgment ――――――――――――― ▼ OUTPUT judgment results
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Applications/Examples of results
Evaluation of Electrical Characteristics of Power ICs 【Confirmation of Effect】 Visual Confirmation AI Judgment ―――――――――――――――――― Judgment Time: 4.1h 0.6h Judgment Accuracy: 98.4% 98.1% ―――――――――――――――――― ⇒ Reducing judgment time by 85% without compromising judgment accuracy!
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We will provide optimal solutions that contribute to our customers' businesses through our "extensive experience and achievements accumulated over many years" and "high technical capabilities" in the fields of embedded and LSI design.