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Canvass AI Mass Balance Solution
Canvass Analytics Inc.
Canvass AI Mass Balance Solution
Canvass Analytics Inc.
Canvass AI Mass Balance Solution
Canvass Analytics Inc.
Industrial AI Mass Balance Solution for Crude Unit
The Crude Unit Mass Balance Solution uses
advanced Industrial AI techniques to detect
faulty sensors, reconcile measurements and fill
in instrumentation gaps through soft sensors
to report feed and product material flows more
accurately.
Canvass’ Mass Balance solution has been
successfully used on a Crude Distillation
Column by engineers to diagnose material loss,
input corrected measurements into
optimization tools, and improve feedstock
intake and production. By using the solution in
everyday process troubleshooting, engineers
can improve unit yield performance while also
improving their own efficiency.
Solution Benefits for Operators:
Solution Benefits for Engineers:
- Engineers save up to 40% of their time while solving complex troubleshooting and optimization problems by using the Mass Balance solution for early diagnosis and data reconciliation in their existing workflow.
- By using current and more accurate measurements engineers can make more confident decisions to improve yield, yield accounting and provide timely support for operations.
- The AI-based mass balancing monitoring tool integrates the experiential knowledge of the unit engineer in troubleshooting mass balance issues into a tool that both improves efficiency of the unit engineer and shortens the ramp up time for future incoming engineers to the unit.
- An average refinery in the USA will generate $1M/Year in additional profits with only 0.1% improvement in feed intake through corrected mass balance measurements.
- The accurate and timely data-informed guidance to operators from the Mass Balance solution will result in additional benefits such as better energy utilization, reduced emissions and improved yield.
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https://store-images.s-microsoft.com/image/apps.47557.70b53b1b-aac6-4796-91d4-2510fefc5ef1.120d4801-d2a8-4860-96e1-951cb4b6a7d1.3e187144-c60f-4b44-94e7-597f71d0410e
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