Condmaster Ruby 2019

Connectivity for the Smart Factor

Focusing on connectivity and efficiency, this further development of Condmaster Ruby adds options that
further simplify the process of exchanging data with automation assets, IIoT devices, and control systems in
smart manufacturing. The capability to merge high-quality condition monitoring data into Big Data analytics
and machine learning enables more accurate predictions and sharper analysis.
The new release comes with a REST API (Application Programming Interface), an easy to implement, Industry
4.0-friendly feature enabling Condmaster to act as a hub for condition monitoring data that other resources
can access for further processing or analysis. In an upcoming revision, OPC UA will also be supported to
further expand interoperability.

High-efficiency Data Handling

In Condmaster Ruby 2019, numerous improvements substantially enhance database performance. Extended
parallel computing enables faster execution of processes and calculations, thus supporting Big Data analytics.
In many cases, users will experience performance speedups of up to ten times, such as in machine
fault symptoms calculations and backups. Enhancements include faster database synchronization with reinforced
data integrity, updated backup management, and extended backup options.

In-depth KPI follow-up with Plant Performer

A key feature of the new software release is the Plant Performer statistics module, which has undergone
extensive further development. Plant Performer compiles and visualizes statistics relating to technical and
economic KPIs in the OEE/TEEP area for display, evaluation, and printing in Condmaster Entity Server. The
module is a very useful tool to demonstrate the benefits of condition monitoring and communicate its technical
and economic impact to all levels of the organization. Plant Performer data can be exported to other
systems by means of an application programming interface (API). Statistics from an unlimited number of
Condmaster databases can be exported and imported – such as from other divisions, production units,
plants, or an entire group – for easy comparison of data.