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Unify operations and optimize asset value with AI-infused monitoring and maintenance.

IBM Maximo Application Suite is a unified asset and facilities lifecycle management solution. It streamlines maintenance, inspection, and reliability of critical equipment and infrastructure by leveraging generative AI, advanced analytics, and the Internet of Things (IoT). The platform serves as a centralized operations hub, providing intuitive dashboards, automated workflows, and predictive analytics for planning, operating, and optimizing asset and facilities tasks. Maximo supports various asset classes across industries, from equipment and factories to fleets and infrastructure. Its AI assistant helps resolve problems before they occur, extend asset lifespan, and enhance technician productivity. Maximo integrates AI-powered insights to optimize planning, maintenance, and performance across the entire asset lifecycle, from procurement to decommissioning. It enables preventive maintenance strategies, lowers lifecycle costs, and aligns budgets with strategic objectives.
IBM Maximo Application Suite is a unified asset and facilities lifecycle management solution.
Explore all tools that specialize in predictive maintenance. This domain focus ensures IBM Maximo Application Suite delivers optimized results for this specific requirement.
Uses machine learning algorithms to identify deviations from normal operating parameters, triggering alerts for potential failures.
Optimizes maintenance schedules based on predicted asset health, usage patterns, and environmental factors.
Enables technicians to conduct inspections using mobile devices, capturing data and photos directly in the field.
Creates a virtual replica of physical assets, allowing for simulations and analysis to optimize performance and predict failures.
Provides tools for planning and prioritizing asset investments based on risk, cost, and performance considerations.
Define asset hierarchy and criticality.
Configure IoT device integration for real-time data ingestion.
Set up predictive maintenance models using historical data.
Customize workflows for different asset types and maintenance tasks.
Train technicians on using the mobile app for streamlined maintenance.
Integrate with existing ERP and financial systems for budget alignment.
Establish key performance indicators (KPIs) for asset performance monitoring.
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