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  • 1.  Leveraging AI Broker and Python Automation in IBM Maximo Application Suite for Smarter Maintenance

    Posted 21 hours ago

    Title: Leveraging AI Broker and Python Automation in IBM Maximo Application Suite for Smarter Maintenance

    Introduction

    In today's digital maintenance landscape, organizations are striving to automate decision-making and operational workflows.
    By combining the power of AI Broker and Python scripting within IBM Maximo Application Suite (MAS), it is now possible to create intelligent, self-triggered Work Orders based on real-time conditions and AI-driven insights.

    This integration brings the vision of autonomous maintenance closer to reality - reducing downtime, human intervention, and operational costs.

    What is AI Broker in MAS?

    The AI Broker in IBM MAS acts as a bridge between AI models and operational applications.
    It connects AI insights (from Monitor, Visual Inspection, Predict, etc.) to business logic in Maximo, allowing automated actions to be executed seamlessly.

    In this context, the AI Broker can trigger a Python automation script whenever an anomaly or threshold breach is detected on a monitored asset.

    Technical Context: Python Automation in MAS

    IBM Maximo provides a scripting engine based on Python (Jython) that enables automation within the system.
    With this capability, developers can dynamically create Work Orders, notifications, or maintenance actions based on data or events - without modifying the core application.

    Common automation use cases include:

    • Automatically creating Work Orders upon anomaly detection

    • Scheduling preventive maintenance based on AI model predictions

    • Integrating IoT data streams into maintenance workflows

    Example: Automatic Work Order Creation Triggered by AI Broker

    

    

    

    

    

    

    from psdi.server import MXServer
from psdi.mbo import MboRemote

# Connect to Maximo server
mxServer = MXServer.getMXServer()
userInfo = mxServer.getSystemUserInfo()

# Create Work Order set
woSet = mxServer.getMboSet("WORKORDER", userInfo)

# Add a new Work Order triggered by AI event
newWO = woSet.add()
newWO.setValue("DESCRIPTION", "AI Alert: Pump P-1001 temperature anomaly detected")
newWO.setValue("ASSETNUM", "P-1001")
newWO.setValue("WOPRIORITY", 1)
newWO.setValue("WORKTYPE", "CM")  # Corrective Maintenance
newWO.setValue("SITEID", "MAINPLANT")

woSet.save()

print("Work Order created automatically via AI Broker and Python automation!")

    How It Works

    1. The AI Broker receives data from an AI model (e.g., anomaly detection or predictive analytics).

    2. When a defined threshold is exceeded, the broker triggers a Python script inside MAS.

    3. The script automatically creates a new Work Order with the relevant details.

    4. Maintenance teams are instantly notified, enabling faster, data-driven responses.

    Benefits of AI Broker and Python Automation

    • Autonomous creation of Work Orders based on real-time AI insights

    • Reduced downtime and faster issue response

    • Seamless integration between AI, IoT, and EAM systems

    • Scalable, low-code automation without altering Maximo core logic

    • Improved asset reliability and operational efficiency

    Conclusion

    The synergy between AI Broker and Python scripting in IBM Maximo Application Suite represents a major step toward intelligent maintenance operations.
    This combination allows companies to evolve from reactive maintenance to predictive and autonomous maintenance, guided by real-time AI insights.



    ------------------------------
    Yasmine Ghomri
    IBM Maximo / MAS 9 Expert | Technical Lead | IBM Digital Badges
    SINORFI
    ------------------------------


  • 2.  RE: Leveraging AI Broker and Python Automation in IBM Maximo Application Suite for Smarter Maintenance

    Posted 7 hours ago

    Hi Yasmine,

    Great article, I'm curious whether you tried the AI service in MAS 9.1, if yes do you have any insights on that and does it work the similar way as AI broker. And do you have any implementation steps for AI service.

    Happy to hear back some insights.

    Thanks

    Prashant



    ------------------------------
    Kind Regards,
    Prashant Patil
    Maximo Consultant
    EmailId: prashantp.1697@gmail.com
    Ph: +91 9901670972
    ------------------------------

    Original Message


  • 3.  RE: Leveraging AI Broker and Python Automation in IBM Maximo Application Suite for Smarter Maintenance

    Posted 31 minutes ago

    Hi Prashant,

    Thank you for your comment and for raising such an interesting point!

    I haven't tested the AI Service in MAS 9.1 yet, but it's definitely on my roadmap to explore and compare it with AI Broker in terms of architecture and automation capabilities.

    From what I've seen in the documentation, it offers a more native integration layer for predictive models within MAS.

    Once I have some concrete insights and implementation experience, I'll be happy to share a dedicated article.

    Thanks again for engaging - great question!

    Best,
    Yasmine



    ------------------------------
    Yasmine Ghomri
    IBM Maximo / MAS 9 Expert | Technical Lead | IBM Digital Badges
    SINORFI
    Tunisie
    ------------------------------

    Original Message


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