Data Extraction with AI-powered Anomaly Detection

Identifies technical faults through advanced diagnostic analytics

  • by Yazzoom
  • March 13, 2020
  • Data Extraction with AI-powered Anomaly Detection
    Data Extraction with AI-powered Anomaly Detection

YANOMALY is a software solution from Yazzoom which aims to answer the today’s data challenges, such as the difficulty to extract valuable information. It allows to use the data collected from machines, assembly lines, packaging lines and continuous or batch production processes, for real time monitoring in the condition of the user’s assets through AI-powered anomaly detection. Thus, the goal is to troubleshoot technical faults or production issues through advanced diagnostic analysis and to build predictive or prognostic models using high performance proprietary machine learning algorithms specifically developed for industrial data.

Easy integration into existing monitoring platforms through a modular highly scalable architecture

The software includes web-based GUI to allow non data scientists to select data, train the computer models, and to validate, deploy, and monitor and maintain those models. Designed to be interfaced or integrated with existing data monitoring or IoT platforms, YANOMALY can process all types of data from sensor signals and other time-series data to event logs or machines, categorical data coming from ERP and MES systems and more. It features AI-powered functionalities such as anomaly detection. This functionality can be helpful since 80% of downtime is caused by never-seen-before technical or process issues. The software doesn't need an issue to have already occurred in the past to detect it. The diagnostic analytics module enables to identify the main factors that influence key performance indicators and metrics. Last, the predictive modeling (virtual sensors) helps build machine-learning models and deploy them in production.

Graduated in political sciences and international relations in Paris, Anis joined the team in early 2019. Editor for IEN Europe and the new digital magazine AI IEN, he is a new tech enthusiast. Also passionate about sports, music, cultures and languages. 

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