What is needed to create the model
Parameters that characterize the operation and condition of the equipment
Working fluid pressures
Environmental characteristics are also taken into account when preparing the model.
Oil temperatures and pressures
Sequence of system implementation
Technological Audit of Data
Obtain a dataset of historical data with specific characteristics: defined level of granularity, continuity, accumulated data for a period of at least a year, parameters representativeness, and equipment failure statistics. Evaluation of the data and creation of a positive assessment.
Data audit has been conducted to assess their completeness for further use
Building machine learning models based on the operational data. Additionally, a development of physics-based mathematical models of equipment to enhance model accuracy in cases of data scarcity (hybrid modeling).
The models of equipment / technological process are developed
Integration with Customer’s IT Infrastructure
Development of a connector to the Customer’s APCS/MES/IIot/SCADA systems using standard protocols such as OPC UA, TCP/IP, Modbus to obtain the real-time operational data from the Customer.
Integration for real time work has been successfully completed
The software has been launched into pilot testing mode. Technical and economic effects are being evaluated. The monitoring results – commissioning works have been completed. The decision has been made to proceed with production run.
Commissioning works and pilot testing have been completed
Provision ongoing methodological and technical support for the software within the Customer’s environment on ongoing basis.
To implement the system, an extensive industrial automation and manufacturing execution system (IIoT/SCADA) should be deployed on the production site.
We are already working with ZIIoT, Winnum, Safe Plant, and others
Example of diagnostics based on digital models
Analysis of efficiency improvement through monitoring changes in operational parameters
Tracking changes in temperature and pressure
Detection of temperature increase and air pressure decrease after the compressor indicates contamination of the compressor flow path and a decrease in efficiency
Discrepancy analysis and recording of results
Indicators of the calculated process model