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Cognite Data Fusion for Domain Experts


Sverre Fjerdingstad
Practitioner
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This discussion is linked to the course Cognite Data Fusion for Domain Experts.

A data-driven approach to maintenance is more efficient than relying on a fixed schedule or fixing something once it’s already broken. There are plenty of opportunities around us to take advantage of smart maintenance. Look around in your home, your office, or think of your work tasks. Where could data-driven maintenance make a difference?

Share your thoughts! For example, explain what data you have available or would need in order to do smart maintenance, and how this would be an improvement of current methods. 

11 replies

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We agree and 100% support this, and would like Cognite to build out functionality and capability that can help us do smart maintenance at Celanese.

 

 


Awesome resource! I just took the course. 
One question, in the last videos it is mentioned that there was a shutdown in July hence the mileage of the valve is counted from that point, also it is suggested to do the same from other maintenance events to measure the mileage between events. Where can I see which were maintenance events? from the time series there are some signals that indicate if the compressor is working or not, but I have not seen one related with a maintenance procedure. 


  • Cognite Academy Instructor
  • 39 replies
  • October 6, 2022

Hi @Luis Ramon Ramirez Rodriguez , glad you liked the course!
You are right that events in Open Industrial Data are harder to use as they are anonymised. We are planning to look into removing some of the abstraction and making more information available about events in this project. Stay tuned in the community for more updates on OID and new courses that work with the data.


Great! Thanks Eniko 


Yes, condition monitoring and predictive maintenance is the best way to run operations in asset intensive industries.  

 

Preston, (Vibration Cat III, CMRP)


Yewtaah
Active
  • Active
  • 1 reply
  • January 3, 2024

Condition based maintenance is a natural evolution that has already presented itself in consumers daily lives.  Newer automobiles, for instance, are much more likely to suggest maintenance based on measured conditions instead of the time-based approach conventionally used.  Proper tire inflation and oil effectiveness are crucial for vehicle performance, and simple sensors provide insights that simplify maintenance tasks and prolong the life of a vehicle.  Home heating/cooling systems have long used current air temperature to control when a thermostat activates climate control - much more effective than trying to guess how many minutes per day to run your heater!


I would like to implement smart maintenance for the central cooling and heating units at my house. Now, I get the units serviced on a schedule usually once or twice a year.  Or, I call a repairman out when something goes wrong e.i. not cooling or heating as expected. I’d like the units to communicate to me about maintenance needed based on actually usage/runtime, or predictively notify me that freon is running low or some other part of the system has become unreliable or damaged so that I can get these things addressed before there is a failure, and we are stuck in the Texas summer with no AC. 


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I'm looking forward to using Cognite to help me monitor some alarms used in my company's installation. There are many sensors in a refinery. It's so big that I don't know what the best area to start would be. Creating tags and organizing knowledge will help us a lot. I have never used this type of solution before and I believe it will be very useful.


One of our customers is having the asset related data in disparate sources and it is really difficult to see whats going on actually in the machine in one unified view ...Data is from ERP (Master data),CMMS (Maintenance data ),Oil Analysis(Quality data),Historian systems (Operational and Production data ) and PLM (Design data) .

The Landscape is complex and there are entangled interfaces with limited analytics capabilities

We are seeing how Cognite could solve such interesting problems enabling simple users to do complex industrial analytics in a jiffy..

Looking forward to get certified in the course..


  • Active
  • 1 reply
  • September 16, 2024

One specific use case is to try to predict pump performance/efficiency loss based on two readily available transitters and stored in PI data historian  (upstream vessel level to suction of pump and downstream flow control valve with PV, SP and OP)..  All data available in OSISoft PI.


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Yes, monitoring the status of equipment and linking it to the parameters that influence its optimal operation can help detect alarms and improve the execution time of corrective actions.


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