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  • 1.  Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 09-30-2025 04:22 AM

    Hi,

    Everywhere now Condition Monitoring is getting " smart" , just like everything is with AI now .More companies are starting to use AI and smart sensors to monitor machine health and catch faults earlier. Instead of waiting for routine inspections or hand held monitoring , world is shifting to remote online monitoring in Condition Monitoring .

    How are you approaching this shift? Have you tried AI tools for early fault detection, and what has your experience been so far?

    For those already using smart sensors with AI-driven monitoring, what benefits have you seen? Where do you think this combination will have the biggest impact in the future?

    Looking forward for your opinions and suggestions on this discussion .

    Thanking you ,

    Adith Kumbrote 

    +44 7747240475

    mailtoadith.k@gmail.com



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    Adith Kumbrote
    Technical Sales Engineer
    Fizix
    Sheffield
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  • 2.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-01-2025 06:13 AM

    The shift to AI-driven Condition Monitoring is game-changing. We're combining smart sensors with predictive and TTF models to detect faults early and prescribe maintenance actions.
    Real-time analytics on vibration, temperature, and oil data helps catch subtle issues traditional methods miss, reducing downtime and protecting critical assets.
    Starting with high-value machinery and validating AI predictions ensures reliability before scaling across the plant



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    Joseph Uwoajega CMRP
    Field Service Engineer
    engrjoe2007@gmail.com
    +447891173499
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    Original Message


  • 3.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-02-2025 08:14 AM
    The best place to start is to make sure planning and scheduling effectively is in place. Condition monitoring just produces corrective maintenance and if the P&S is not in place first, firefighting will ensue.

    ---------------------------------
    Derek Brown
    Reliability Engineer
    bp
    Grangemouth
    ---------------------------------



    Original Message


  • 4.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-02-2025 09:21 PM

     Hello everyone, 

    Yes Sir as you mentioned, this is a remarkable advancement: AI is now a great help for condition monitoring and rapid decision help support. I believe it's a broadly open tool, to the point where it could be widely applied. After testing it in a collaborative trial on remote monitoring of gas turbine parameters, I think it will no longer be necessary to know the equipment, but simply be focus on the data to make decisions (which could be problematic). However, some conditional decisions are not like that, you must very check before conclude.
    Regarding the benefits, I see them as long-term economic aspects in terms of safety, human resources, and financial resources. But don't forget that, monitoring by someone who doesn't understand the facilities would expose us to many risks.
     
    Thank you.  


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    FRANCOIS VIVIAN KINGUE NJANJO
    Senior Mechanic
    Cegelec(Actemium) / Perenco Cameroon
    Douala
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    Original Message


  • 5.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-04-2025 08:37 PM

    Hi,

    Just to share about what we do in Indonesia, we are trying utilize AI/ML to develop anomaly detection for equipment and also impact to process in real time integrate with IT system. Every anomaly will trigger email notification that consist of anomaly detection, the most process parameter impact to anomaly, anomaly classification and also alert if any operation of pump uot from pump curve that may make condition of pump operate in fouling, cavitation, imperformance and so on. Yo can brief it by read my paper : https://onepetro.org/SPEOGWA/proceedings-abstract/25OPES/25OPES/673801

    Thanks

    Febri

    Maintenance & Integrity



    ------------------------------
    Febrita Kusuma Wardana
    Superintendent Facility & Maintenance
    Pertamina EP Cepu
    Tuban
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    Original Message


  • 6.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-05-2025 12:45 AM
    Hello everyone,
    Interesting and good work Febri.
    Thanks for sharing. Your abstract is very telling.



    Original Message


  • 7.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-07-2025 08:51 PM

    Thanks Francois,

    We have sustainability program to develop AI ML in several Gas Plant now, starting with anomaly detection to equipment, spread to process anomaly, forecasting to predict strainer/filter cleaning/replace, predict and extended Gas Turbine offline wash/overhaul, ruled Based AI for monitoring operational Pump and Process, computer vision for safety and security in plant, and so on. All innovation/initiative develop in realtime system integrated IT-OT system. We are using all sensor/transmitter related with what we are doing for AI/ML training, pass through to DCS, OPC, Data Historian and then AI ML system. We are still using predictive maintenance for condition monitoring using Vibration Monitoring System, Asset Integrity Management System and so on. Hopefully integration between system is our goal to optimize performance of production and equipment.

    Thank you



    ------------------------------
    Febrita Kusuma Wardana
    Superintendent Facility & Maintenance
    Pertamina EP Cepu
    Tuban
    ------------------------------

    Original Message


  • 8.  RE: Reliability in Transition – Smart Machine Health Monitoring with AI for Early Fault Detection

    Posted 10-06-2025 10:05 AM

    Hello Adith, 

    We are using ML to detect issues and drive corrective actions. We are specifically using a measured approach and looking for specific types of failures. This targeted approach helps to make sure our time is spent reacting to real issues. 

    Best of luck!

    Zachary Whear



    ------------------------------
    Zachary Whear
    Engineer II
    Boardwalk Pipelines
    Owensboro KY
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    Original Message


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