Improve visibility of stranded assets and empower field workers with diagnostics and smart procedures to act at the point of inception (faster and better decisions) with the ability to capture and annotate pictures, capture video and audio, edit documentation and write notes to enhance SME communication. Mobile learning through consistent instruction, limits and messaging.
Protect Critical Assets with Predictive Analytics
Software-based modeling of equipment using machine learning and advanced pattern recognition. Leveraging historical data to describe how equipment normally operates and using that to build a model ensures real-time monitoring of the assets behavior. Alerts when the operation deviates from normal, early warning detection of equipment reliability and performance problems. Advanced analytical capabilities including problem identification and root cause analysis ensure critical assets are always protected.
Maximum Performance for Process Economies
Extract maximum performance benefits from existing equipment while respecting operating constraints by connecting to automation systems across sites and leverage data (real-time and historical) to analyse and build cause-effect relationship.
Real time dynamic combustion optimisation to reduce thermal NOx generation
Heat rate and ramp rate improvements to increase plant efficiency and flexibility
Reduced operating costs for secondary NOx reduction systems (lower reagent, utilities consumption and extended catalyst life for SNCR/SCR)
Many other applications such as steam temperature control and optimized soot blowing
Enforce Standard Operating Procedures
Companies have many active strategic initiatives within their organisation and these strategic initiatives have multiple objectives and these objectives involve establishing setting up business processes, policies, and procedures to aid execution and measurement. A robust industrial workflow management tool can be the enabling framework to manage these strategic initiatives. A robust workflow management tool compiles data from multiple sources – MES, System Platform, Historian, Predictive Asset Analytics etc. to highlight inconsistencies, coordinate reviews or additional actions based on disposition eg: lock-out/tag-out activities, normal/abnormal events etc.
Monitoring and Diagnostic-as-a-Service
A value-added service where your assets are continually monitored by our engineers to provide early warning alerts, and diagnostic guidance, to improve reliability, reduce maintenance costs, improve equipment performance, reduce capital expenditures and reduce total cost of ownership. The Monitoring and Diagnostics Service Centre (MDSC) located in Chicago, IL is staffed with subject matter experts in the fields of power plant operation and maintenance. The MDSC provides daily, weekly, monthly, and quarterly activities to help users get the most out of their investment. Usage of machine learning and diagnostics technology, coupled with years of experience, to provide early warning of equipment problems to ultimately reduce unscheduled downtime, improve reliability and control maintenance costs.
Centralised Data Management
Enterprise Data Management Platform to help collect, store, display, analyse, contextualise and report on data collected from the operational side as well as from the enterprise side to achieve increased efficiency. Bridge the information gap between IT/OT data sources such as process control, operations management, IT and other 3rd party business systems.
Cloud Operator Training Simulator
A perfect fit to meet the need of distributed learning and address the need to train newer operators staff in a more straightforward, cost-effective manner while addressing the aging workforce with minimal maintenance cost for the simulator.
Access from anywhere
Generic/Custom model with fidelity
Support distributed operations teams
Software/Training as a Service
Flexible pricing and support models
Closing the Performance Gap
Close to 75-80% of Variation in performance is attributed to human factors and this is caused by lack of advanced decision support methods/tools, Scarce use of performance data except for reports, productivity loss due to tacit knowledge. This directly impacts the economic and sustainability factor and the way to minimise this is by improving decision making support, improve analytics/insights into plant performance, introducing innovative and predictive methods in not only improving, but sustaining the performance. Closing the performance gap results in:
Fleet performance monitoring
Mature from Reactive to Predictive
Actionable insights into technical consequences impacting the company economics
The Schneider Electric industrial software business and AVEVA have merged to trade as AVEVA Group plc, a UK listed company. The Schneider Electric and Life Is On trademarks are owned by Schneider Electric and are being licensed to AVEVA by Schneider Electric.