https://store-images.s-microsoft.com/image/apps.29882.7e185010-cd3e-4091-9600-9b409135a30f.31c9d29c-56a9-4d14-aedf-927d42e5d433.cdd516cd-5325-4467-84e6-def9702d7fa7
DictumPro AI Predictive Operation and Maintenance
Автор: NETGAS RESEARCH & DEVELOPMENT SRL
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Predictive-prescriptive solution for improved industrial process and asset operability
Improve the efficiency of your operations and value of your industrial assets by:
- detecting or predicting the occurrence of industrial process disruptions and facility outages
- evaluating their criticality for achieving your planned operational performance and the risks for safety and facility integrity
- prescribing optimal prevention and contingency measures, which seamlessly complete standard procedural framework, in full compliance with current regulations.
Capabilities:
- real time anomaly detection in process and equipment performance and functionality;
- intelligent instantaneous diagnosis of process and equipment problem;
- real-time monitoring of large number of processes and equipment, capturing the anomalies and operational problems;
- dynamic real-time criticality and risk determination & ranking of detected problems;
- precise causal analysis with fast determination of degradation and failure modes;
- analysis and determination of optimal prevention or contingency measures to be undertaken against a degradation or failure mode
- accurate failure or degradation prediction for process performance and equipment reliability;
- prescriptions triggered by detections and predictions alerts.
Быстрый обзор
https://store-images.s-microsoft.com/image/apps.6568.7e185010-cd3e-4091-9600-9b409135a30f.31c9d29c-56a9-4d14-aedf-927d42e5d433.71390ab2-8753-4536-ac12-87d059a06bc2
https://store-images.s-microsoft.com/image/apps.35504.7e185010-cd3e-4091-9600-9b409135a30f.31c9d29c-56a9-4d14-aedf-927d42e5d433.8a4d9144-775e-48bd-bccd-5e8b6ffbfcf3
https://store-images.s-microsoft.com/image/apps.61142.7e185010-cd3e-4091-9600-9b409135a30f.31c9d29c-56a9-4d14-aedf-927d42e5d433.11b62536-7ea6-4e23-a439-6a9097ec9ae9
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