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Silesian Catalysts

Microsoft Partner

Advanced platform for analysis of process data from production facilities. The new solution combines extensive engineering knowledge of the company’s experts with state-of-the-art BIG DATA analysis solutions.

Advanced Process Analytics Suite

Complete Industry 4.0 solution

Advanced Process Analytics Suite is an advanced platform for analyzing process data from production installations. The new solution combines a rich engineering knowledge of the company’s chemistry experts with a modern BIG DATA analysis solutions from Microsoft.

The Advanced Process Analytics Suite allows you to diagnose a process in its real time.

  • It provides predictive diagnostics of process equipment.
  • Thanks to intelligent virtual sensors, it analyzes the reliability of data that comes from control and measurement instruments.
  • It provides advanced analysis to identify causes of process anomalies.

 

Advanced Process Analytics Suite

Behavioral analysis of industrial processes

Most recent achievements in information and communication technology, simplify in a big way the collection and storage of huge amounts of data about technological processes. Unfortunately many companies do not use the full potential hidden in their data sets

The analysis of process data usually comes down to trend and deviations tracking for each process parameter individually. In complex process installations, operators are under high-level attack of a large number of individual process alarms. It happens because the indications of the control and measurement instruments are often undergo to temporary deviations.

Those situations increases the risk of the operators resistance to the alarm signals, which, as a result, leads to dangerous process incidents.

Behavioral analysis allows to change the approach to evaluate the current state of the industrial process in a fundamentally way.

The intelligent system for evaluating the current process situation is based on the sum of the impact of all measured parameters on the process status. At the stage of implementation a behavioral analysis, diagnostic system is taught the patterns of the correct trajectory process. It is possible to continually improve the system by teaching it with a new process data. As a result, the system analyzes the process situation on a regular basis and, with respect to the pattern, detects any deviations from the typical state. The system can also be extended with a module for analysis of decisions made by the installation operators.

Benefits:

  • improvement reproducibility of processes,
  • reduction of production costs,
  • increased process safety,
  • rationalization of the number of process alerts,
  • reporting only significant alarms by SCADA systems,
  • improvement operators work quality.

 

Advanced Process Analytics Suite

Predictive diagnostics of process equipment

Predictive maintenance is a maintenance strategy that optimizes the using of machinery and equipment by eliminating the occurrence of failures and optimizes the planning of maintenance work.

A modern maintenance strategy uses the Risk-Based Inspection RBI to planning the inspection of process equipment. With the RBI methodology, it is possible to make the inspection stops  as short as it can be and also to extend the period between inspections.

Predictive diagnostics of process equipment analyses the technical condition of machinery and devices, in the direction of probability of failure. It all goes in a real time.

Predictive system is taught patterns of approaching device failure, based on historical data. This allows to estimate the risk of impending equipment failure during operation, and also classify their type based on real-time analysis of process parameters.

Benefits:

  • extension of periods between inspections,
  • reduction of inspection costs,
  • improvement of risk management of failures,
  • improvement the management of maintenance services,
  • improvement process safety.

 

Advanced Process Analytics Suite

Intelligent Virtual Sensors

Control and measurement system is a critical area for any industrial installation. The security of the process depends on the proper operations of this system.

Implementation of the Intelligent Virtual Sensors technology allows detecting irregularities in the indications of supervised measuring sensors.

The working principle of the virtual sensor is based on the predictive modelling of the correct measurement value. This in turn, is based on the analysis of the indications of other process parameters. In addition, for the value predicted by a virtual sensor, in relation to the value measured by the sensor, the time series analysis is performed. This allows to detect small measurement anomalies, which accumulation during time can lead to a process incident.

Another Virtual Sensor application area is prediction of the process parameter value, which, for technical reasons, cannot be monitored, due to lack of control and measurement instruments. For example, there is a lot of product’s quality parameters impossible to measure in a real time, due to the unavailability of an appropriate measuring technique.

Benefits:

  • improvement the safety of the technological process
  • improvement of the product quality and technological process management by monitoring non-measurable parameters with classical techniques
  • detecting cyber-attacks, which causing falsification of control and measurement instrument indications.

 

Advanced Process Analytics Suite

Process anomalies analysis

 

One of the principal tasks of safety engineers is identifying the causes of breakdowns and improving the technological process to eliminate them.

As part of the investigation of the accident causes, the records of the installation’s operation, the register of operational decisions taken, physicochemical tests of process apparatus elements as well as samples of raw materials and products are analysed.

The complexity of modern process installations makes it necessary to analyse large sets of data describing the course and causes of a process incident.

The Advanced Process Analytics Suite significantly improves the data analysis process and allows for quickly identifying key parameters associated with the occurrence of the investigated incident.

Data analysis is based on algorithms that automatically analyzes the entire available process data collection. After defining the breakdown pattern, an analysis of the significance of the process parameters, on the occurrence of this incident is conducted. The result of the system operation is a map of parameters, which correlate with a causes of failure together with the indication of the correlation power. The safety engineer will very quickly get a set of suggestions about the possible causes of failure, which can be analyzed to detect the real causes of breakdown.

 Benefits:

  • automation of process data analysis,
  • automatic detection of probable causes of failure,
  • automatic detection of non-obvious factors affecting the course of failure,
  • shortening of the analysis time
  • limiting the costs of determining the causes of the accident.

Advanced Process Analytics Suite– technical characteristics

  • 1. Compatibility with any SCADA system as a source for process data.
  • 2. Possibility of non-invasive process metering using IoT.
  • 3. Silesian Catalysts Machine Learning Techniques.
  • 4. Predefined, customizable Microsoft Power BI data visualization desktops.
  • 5. Creating an advanced reports in Microsoft Power BI.
  • 6. Reporting analysis results to SCADA system.
  • 7. The highest level of cyber security confirmed by independent audits.
  • 8. Full scalability with Microsoft Azure.

PREDICTIVE
SYSTEMS

Construction and implementation of a predictive industrial risk management system.

CONSULTING
SERVICES

Comprehensive support in the process of building a business continuity strategy in line with the standard.

CHEMICAL
ANALYSIS

Chemical analysis of sediments in industrial installations. Predictive care of the industry installation.

PROCESS
MODELING

Modelling of industrial operating processes through laboratory scale experiments.