Exaquantum can acquire data from all facets of a process and transform that data into easily usable, high-value, widely distributed information. The data then becomes an integral part of the set of tools used by the business in vital decision-making processes. Exaquantum Overview Exaquantum is Yokogawa’s plant historian suite that provides a central database from yokogawa dcs centum cs 3000 pdf information can be extracted and presented to users throughout the organisation, enabling them to achieve safe, reliable and optimal plant operations.
Exaquantum turns data into actionable information, enabling the smooth running and optimization of process operations. Exaquantum delivers a wide range of functionality suitable for many different production environments. Exaquantum provides an extremely powerful and flexible analysis and reporting facility. OLE DB and API component technology provides extensive information exchange with other applications for inclusion in reports, distributing information etc.
Comprehensive trending facilities provide real time and historical, single or multi-trend groups. This architecture enables applications from small single process installations to very large plant-wide systems. Exaquantum has a very clear business-directed focus to integrate data across an enterprise, delivering operational information to the whole business. Exaquantum provides industry with powerful plant information management, covering both business and process control domains. It eliminates the gap between business systems and process control by integrating information to meet complex business requirements.
Drink, Manufacturing and other continuous or batch processing industries. LIMS packages to be reported to Exaquantum users throughout the plant. Data is passed into Exaquantum tags whenever a test result is released by an authorised laboratory person. VPN enables business systems to extract data from the process environment, without compromising security. By storing the data into the Real-Time database, graphical screens, calculations and aggregations will be updated.
FDM checks each file folder for the presence of new files is configurable. On each folder access, all CSV files present in the folder are processed up to a configured maximum number of files for that Read Interval. Files continue to be processed at each successive Read Interval until no further files remain in the File folder. After processing in file creation order, files with no errors are moved to a specified Archive files folder while files which cause errors during the read are moved to a specified Error files folder. The maximum number of files kept in each folder may be specified to prevent unlimited use of disk space. File names written to a File folder must be unique. If a file with the same name already exists in the Error or Archive files folder then the newly-processed file is simply deleted.
If an error occurs while moving a file to the Archive or Error files folder an error is logged and the file is deleted. If present, the Quality will be stored with the Tag Value. A Timestamp for the Tag Value can be entered otherwise the current time when the CSV file is read will be used. The timestamp format is configurable for instance ‘ddMMyyyy HHmm’ or ‘ddMMyyyy HH:mm:ss’. The following is an example of a CSV file containing two rows. Events received from Non-Yokogawa DCSs, ESDs, etc. The Problem The ability to create a common graphical screen hierarchy and run-time features accessible by all users, such as linked trend groups and report selections, is time consuming, inefficient and difficult to manage.
These screens can be accessed by supervisors and managers needing to view the plant’s processes. Screen interrelationships and linked features such as access to screen specific Microsoft Excel reports and trends provide in-depth access to key information. Screens are grouped within plant hierarchies. The Problem Plant personnel often require detailed analysis of data collected by their Exaquantum Historian to identify problems, reduce plant maintenance, improve production, etc. Microsoft Excel reports using Exaquantum Historian data. Total system integration for large-scale biotech production facility.
The highly reliable CENTUM CS 3000 system has also helped TOL maintain high productivity at this plant. Exaquantum provides data on long-term trends needed to make improvements to plant processes. Yokogawa also delivered two high fidelity operator training simulators for this plant. Yokogawa proposed to provide its systems and services as the main instrument vendor. KKPC needed to expand its SBC capabilities and improve production efficiency at its plants.
Improve quality and yield through proactive maintenance of plant assets. Following an upgrade to the CENTUM CS 3000 Production Control System, leading pulp and paper supplier CENIBRA saw the potential for further savings and efficiencies through tighter control of the production process. Mori Building owns 127 buildings and many of them are located in the center of Tokyo. Overview: Eraring Power Station, located just north of Sydney, is one of the largest power stations in Australia, comprising four 660MW coal-fired units. The power station has operated reliably since 1981.
The visualization of all data on items such as motor and pump operating time and chemical consumption amount allows operators to optimize key operation items. Process data management by Exaquantum is a key issue in the petrochemical complex. Sharjah plant’s existing legacy DCS with Yokogawa CENTUM VP. Overview: Rousselot Ghent won Belgium Factory of the Future Award.
Yokogawa has supported Rousselot with automation systems since 1993. Data of 20,000 tags gathered by Exaquantum helped to find the ideal production parameters. Overview: ARC believes that by implementing procedural automation, many process plants can minimize variability to help ensure smooth, efficient, and safe state transitions. Overview: Modern historians do much more than just store process data. They also provide analysis, reports, and valuable operational and business information. Overview: Improved plant operation efficiency and reduced maintenance costs based on appropriate predictive maintenance are the common objectives that need to be achieved in every manufacturing domain.