Integration Objects announced the release of its latest version of KnowledgeNet Analytics, also known as KNet Analytics. Integration Objects is a world-leading software solutions provider specialized in operations and manufacturing intelligence, Big Data analytics, plant automation, command and control systems.

Integration Objects’ KNet Analytics is a big data analytics software designed for capturing, storing, processing, analyzing and visualizing all your raw data. KNet Analytics new alarm analytics module combines several data analytics and advanced techniques allowing end users to extract knowledge from alarm databases and go beyond classical alarm management. This alarm analytics module allows to:

  • Audit the performance of alarm systems and pinpoint nuisance alarms such as frequent, chattering, stale and standing alarms
  • Identify alarm correlations and clustering to remove redundant alarms and reduce alarm floods
  • Use pattern recognition tools such as sequence mining and association rules to predict the future behavior of alarms for increased safety and reliability
  • Correlate alarms with process data for a better troubleshooting and root cause analysis

KNet Analytics alarm analytics module was designed to remove end users’ frustration of not getting enough insights from their alarms and events. The new features of this module include:

  • Alarm System Assessment

This feature provides insights into alarm frequency, statistics, operators’ acknowledgements, priority distributions, alarms timeline and alarm system performance. Results are presented in detailed reports, charts and dashboards. Alarms KPIs are calculated and benchmarked against ISA 18.2 standard recommendations. Deviations are then pinpointed for further actions and improvements.

  • Alarm Reduction

KNet Analytics alarm module captures and analyzes all alarms and events data to extract knowledge about nuisance alarms such as frequent, chattering, redundant, and alarm-related issues. It also provides guidance for efficient alarm reduction.

  • Alarm Correlation and Clustering

KNet Analytics provides an advanced algorithm to define alarm clusters based on similar, redundant and cross-correlated alarms. Knowledge of alarm clusters can be used to dramatically decrease the number of alarms raised during alarm floods, avoid overloading and misleading information and contribute to a safer alarm system.

  • Alarm Flood Detection

The “Flood Detection” tool in KNet Analytics allows an easy detection of the alarm floods occurrences in a historical database. The feature includes statistics about the alarms that occurred in each flood of events and an alarm timeline that represents them. “Flood Detection” can be combined with other  knowledge extraction tools such as sequential rules and association rules for further investigations of flood reasons, thus reducing the root cause analysis cycle time.

  • Intuitive & Graphical User Interface

The new alarm analytics features can be configured within few clicks using intuitive and graphical user interfaces. Configuration time is also reduced by providing advanced technics such key variables recognition.