Pharmaceutical production, food processing, oil and gas – is not an exhaustive list of branches of industry, quality control, which requires the recording and archiving of large amount of information about the course of technological processes. Compliance with production standards HACCP, GMP, FDA, … involves the monitoring and archiving of process data – sensor readings of the equipment data.

Automated data collection system based on Hyper Historian software is designed to capture and record real-time large amounts of data. On average, the data collection system based on Hyper Historian able to record and process up to 100-150 million tags per second. The total amount of data to be processed can be up to 1 000 000 tags.

By creating a system for its customers automated data collection, we offer them the opportunity to:

• Get data from the process equipment in a variety of formats – OPC UA, OPC DA, OPC XML DA, BACnet, SNMP, …
• Use the data warehouse on the basis of high-performance algorithm for structuring the necessary information from the raw data sets.
• Enjoy the advantages of a distributed architecture with multiple remote and local collectors to collect data.
• Use the system to work in the mission-critical applications that require continuous access and data collection. Built-in mechanism to ensure the integrity of the data array failures in systems allows a high degree of reliability of performance data archiving functions.
• Apply more sophisticated than simple filtering, archiving and compression mechanism to prevent accidental loss of data as a result of filtering.
• Analyze data using a simple to use various tools of visualization of current and historical data in the form of 2D & 3D.
• Get WEB – access to the tools of development and management.
• For use of the information by third-party applications (MES, ERP, BI) integrated system of automated data collection with any open database.
• Collects data from devices without compromising their ability to transfer data with a high degree of reliability for data capture, even when network failures.
• Get access to archived information using conventional SQL queries.