Predictive Maintenance

IBM Predict
IBM Maximo® Predict is an application within the IBM Maximo Application Suite (MAS) designed to enhance the reliability of your assets. By leveraging artificial intelligence (AI) and integrating performance data, maintenance records, inspection reports, and environmental data, Maximo Predict forecasts asset downtime, degradation, and failures. Predict allows you to track potential failures and manage maintenance schedules proactively and more efficiently.
Predictive Maintenance - Features
Predictive Analytics
Utilize AI-driven insights to predict asset downtime, potential degradations, and failure events. By analyzing historical and real-time data, Maximo Predict provides forecasts that help in preventing asset failures.
Predictive Model Development
Collaborate with data scientist to create predictive models using the group IDs and default notebooks. These models can be trained and deployed to generate valuable predictions like failure probabilities or expected failure dates for asset groups.
Comprehensive Integration
Maximo Predict encompasses all features available in Maximo Health, along with enhanced predictive capabilities. By consolidating data from various sources, it provides a unified view of asset health and operational status.
Seamless Integration with IBM Watson & API's
Maximo Predict is powered by IBM Watson® Machine Learning, providing advanced AI-driven insights. The platform includes five prebuilt predictive model templates, along with a comprehensive analytics API library, enabling businesses to develop custom predictive models tailored to their industry and operational needs.
Automated Workflows & AI- Driven Maintenance Scheduling
Maximo automates maintenance workflows by integrating predictive insights into asset management systems. The platform automatically generates work orders, prioritizes tasks based on risk assessment and failure probability, and assigns technicians with the right skills and resources to resolve issues quickly. This minimizes manual intervention and reduces overall maintenance costs.
Customizable Analytics
Your data scientists have the flexibility to configure custom notebooks, extending default capabilities or creating entirely new models. All custom models are deployed through Watson Machine Learning to ensure reliable performance and accuracy.
Why Predictive Maintenance?
Minimize unnecessary repairs by shifting from routine to predictive maintenance.
Maximize efficiency by scheduling maintenance only when needed.
Identify early warning signs and prevent unexpected failures.
Improve manufacturing and production efficiency with reliable, well-maintained assets
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Prevent Failures Before They Happen with AI-Powered Predictive Maintenance
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