Data management - key to successs

Safety first.

  • IT monitoring
  • IDS - Intrusion Detection System
  • IPS - Intrusion Protection System
  • Honeypot
  • Context Awareness
  • Data diode
  • Enterprise log management

Report and process 24/365

Connect, share and evolve

  • ESB  - Enterprise Serial Bus
  • ERP/SAP Connector
  • EAI – Enterprise Application Integration
  • SOA – Service Oriented Architecture
  • OPC – OLE for Process Control

 Oil & rafinery

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Heavy Industry (Coal, Steel)

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Agriculture 

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Pharmaceuticals

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Telecommunication 

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Power Industry 

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Heat Industry 

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Energy & Natural Resources 

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Manufacture & Warehouse 

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Data management - key to successs

Safety first.

  • IT monitoring
  • IDS - Intrusion Detection System
  • IPS - Intrusion Protection System
  • Honeypot
  • Context Awareness
  • Data diode
  • Enterprise log management

Report and process 24/365

Connect, share and evolve

  • ESB  - Enterprise Serial Bus
  • ERP/SAP Connector
  • EAI – Enterprise Application Integration
  • SOA – Service Oriented Architecture
  • OPC – OLE for Process Control

 Oil & rafinery

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Heavy Industry (Coal, Steel)

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Agriculture 

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Pharmaceuticals

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Telecommunication 

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Power Industry 

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Heat Industry 

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Energy & Natural Resources 

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed purus ante, fringilla ullamcorper diam id, volutpat volutpat lectus. Nullam sed rhoncus magna.

Manufacture & Warehouse 

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AMDV - Advanced Measurement Data Validation 

The purpose of validation is to prepare measurement values. The gross errors will be detected and corrected. Values out of range, or values with errors will be substituted with modeled values.

 

 

The Advanced Measurement Data Validation module is an implementation of an empirical method of signal verification based on mathematical and thermo-dynamical models of the measurements created basing on self-organizing maps. Additionally, device characteristics can be implemented in the system. ADV makes it possible to validate /mode multiple signals modelled with a single or multiple neural networks or composite device characteristics. 

 

 

The system is able to check data based on Sensor/measurement range and Model based checks for consistency of data. It is a system created as a response to the need to verify the measurements, their credibility and quality.

The value that the system adds lies not only in providing continuous measurements of the process parameters but also the possibility to feed data to 3rd party systems that require this data like for example operational calculations systems, technical analysis systems, optimizers or predictive systems. The usage of this module in software allows the measurement signals to be verified to increase the quality of results generated basing on them.

Example type of validation are: 

Verification of the correctness of the read data can be done by analyzing the read value of the point and comparison with the predefined allowable range of variability of the given point. Another way of verification is to compare the read value of the measuring point with the output value of the modelled measurement in the ADV.

The signal models are created basing on a dedicated application. Each model can be used to verify one or more signals. Each of these signals has a weight assigned to it in the self-organizing map basing on the value of the measurement of one or more values that are treated as independent weights in the map. 

Data validation and enhancement consisting of:

  • Collection of process data from the data source provided by the Client.
  • Measured data reconciliation.
  • Calculation of directly unmeasured variables, KPIs and model parameters.
  •  Identification of erroneous instruments.
  • Application of different modeling techniques (not only self-organizing maps) 
  • Depending on the signal that is modelled an appropriate validation method is chosen.