Find the most effective ways to reduce total cost of ownership, improve reliability, availability and safety of your assets with a predictive maintenance regime powered by Xempla’s advanced analytics engine.
Waste no time getting started with your predictive maintenance journey using our in-built workflows library covering the most popular use cases. Customized workflows unique to your building conditions can also be set up easily using our no-code workflow builder.
Connect with Slack, Teams, WhatsApp or email to receive notifications the way you want and save valuable time using platforms you’re already familiar with. Leverage Xempla’s easy integration with your CMMS or simply use our Work Order Management module to remove friction points and quickly get things underway.
Adjust baselines, choose from different forecasting models relevant to your assets and breathe efficiency, flexibility and agility into your operations and maintenance. Eliminate complexities and resolve issues before they escalate to deliver the ultimate experience for customers.
Bring your teams, tools and resources together to investigate, drill down to the bottom of problems and understand what needs to be done. Make an impact with each intervention and drive better decisions with Xempla’s on-demand assistance features.
See how Xempla’s advanced analytics engine helps you find the best way and time to deal with a problem, improve decision making and create impact.
This algorithm works on past data to develop a forecasting model basis in which the actual performance levels of the asset (Fan in this case) can be evaluated against the expected levels.
In this case the investigation suggested that there was a problem with the calibration of the controllers which was causing the fans to work at higher RPM.
This FDD logic uses a backcasting method to determine the control speed feedback to CT Fan and alerts if there is an optimisation possibility.
Investigation revealed that the way the BMS controls have been set, even a minor change in CT Water Outlet Temp will cause the CT Fan to work at max levels.
FM O&M Team is now working on further tweaking the control strategy, without impacting thermal comfort.
This algorithm works on historical data to develop a forecasting model basis in which the actual performance levels of the asset (compressor motor) can be evaluated against the expected levels.
Annual maintenance is being brought forward to understand the possible reason and to close in on motor performance.
Predictive analytics playing a vital role in energy management and building operations
Read More
