Time Series DBMS Use Cases
Machbase edge computing database uses range from process data management in the semiconductor industry, to product lifecycle and predictive maintenance in high-tech industries, as well as real-time data processing in precision industrial environments.
Manufacturing Use Cases
Machbase edge computing database manufacturing uses range from process data management in the semiconductor industry, to product lifecycle and predictive maintenance in high-tech industries, as well as real-time data processing in precision industrial environments. In addition, Machbase supports real-time monitoring and diagnosis, machine learning and optimal operation management of large industrial machine assemblies.
Cement
Background
Cement factory sensor data is checked once every two hours, and analog data is processed manually without any real-time data measurements. Users are not able to check on real-time flow conditions or intermediate process status.
Requirements
Experimental data was stored in the existing in-memory database, but real-time monitoring of ‘quality’ data changes (grade changes) for each process step was difficult due to the characteristics of the relational database.. The key requirement was to increase the data precision by increasing the acquisition cycle from 15 minutes to a second.
Effect of application
Customer implemented a time series database (Machbase) and dashboard capable of real-time continuous processes monitoring of ‘quality’ aggregation data. Allowing the customer to collect‘ quality’ or grade data of raw material (i.e. limestone) in seconds. In addition, by using the ‘sampling’ results based to data quantity and grade changes data, the customer was able to monitor specific equipment status along with process data at any time point of time along the entire line.
Paper
Background
During the rolling stage of the paper-making process, Jams (folding or tangling) results in unnecessary consumption of heat energy and power. The existing real-time database (RTDB) and relational database (RDB) in the ESS (Energy Storage System) was incapable of collecting 1,000 records per second.
Requirements
There was an urgent need for flexible integration with existing OPC DA. More than one thousand data points were collected per second together with the connection between the DB and OPC DA server in this ESS application platform.
Effect of application
Data was input in units of one second while collecting more than 1,000 tags per second while integrating between the OPC DA server and the collector using Machbase. Implemented to be automatically ingested when reconnecting the tag values ​​of collected sensor data, It was possible to accelerate collection and storage of ESS platform significantly.