Equipment and process monitoring systems are a type of PARADIGMA-based integration solutions.
This solution is designed to provide real-time monitoring of equipment and key process parameters and can be applicable to separate production units, groups of units, complete lines or plants or the whole site.
It is a versatile solution designed for such industries as steel, machinery, power, mining and others.
- Real-time equipment monitoring by unit, line, plant or at a site in general.
- Process parameters monitoring.
- Out-of-range parameter indication.
- Critical trends.
- System event and alarm detection and logging.
- User-friendly visualization of process data (mnemocircuits).
PARADIGMA constitutes the core of the system. Apart from its standard functionality of data acquisition, processing, storage and transmission, PARADIGMA consolidates the data coming from versatile sources while enabling a standardized access to the data for MES.
The system clients are based on the web interface and the Flash technology and include a set of workstations used for visualization (usually visualization only) of equipment statuses and current process parameters.
No additional software is required on the client stations as all screens are accessible as common web pages via standard browsers (for example, Internet Explorer).
A user workstation usually contains the main mnemocircuit, which shows the key process and the status of equipment of a separate line, plant or the site in general, and specific mnemocircuits, which show particular groups of units with all the auxiliary systems.
For detailed information about the process or the equipment the user can go to the target mnemocircuit either from the main screen or using navigation tags.
As agreed with the customer, any other data visualization technology or software from the industry leaders (such as Simatic Win CC and Wonderware InTouch) can be adopted.
This solution delivers the following benefits: prompt access to the equipment performance data, remote process control, visualization of all status data, reduced downtime and reduced maintenance costs due to early detection of potential failures.