What is enterprise asset management (EAM)?

Enterprise asset management involves work management, asset maintenance, planning and scheduling, supply chain management, and environmental, health and safety (EHS) initiatives.

In the Internet of Things (IoT) era—with everything from valves to vehicles connected by sensors and systems—practitioners are incorporating advanced analytics and artificial intelligence (AI) into EAM. Data gathered from instrumented assets is analyzed by using AI techniques. The resulting insights help maintenance teams make better decisions, enhance efficiency, perform preventive maintenance and maximize investments in their physical assets.

EAM is often associated with a computerized maintenance management system (CMMS), but a closer look at EAM versus CMMS reveals they are different. A CMMS can be one aspect of EAM. It focuses on centralizing information to facilitate and automate maintenance management processes. EAM is an asset lifecycle management approach that supports asset performance from acquisition to disposal.

EAM is important because it helps organizations track, assess, manage and optimize asset quality and reliability. Organizations of all kinds are asset intensive, which means they have hundreds, thousands or even millions of assets.

Assets come in many shapes and sizes—such as railroads, pipelines, manufacturing equipment, transportation fleets and windmills—and include virtually any piece of equipment needed to sustain production, services and operations. EAM best practices help maintenance teams gain greater control of complex environments to:

• Centralize asset information
• Resolve issues before they happen
• Monitor assets smarter
• Maximize asset utilization
• Manage aging assets and infrastructure
• Elevate maintenance management
• Consolidate operational applications

A CMMS, as part of EAM, tells maintenance managers where an asset is, what it needs, who should work on it and when. It automates critical asset management workflows and makes them accessible and auditable.

Asset management software supports preventive capabilities to maintain equipment for stable, continuous operations. It helps ensure warranty compliance and preempt issues that disrupt production.

AI-powered remote monitoring delivers actionable insight into current and expected states of assets. It aggregates data across departments and information silos, allowing for fewer, more accurate alerts and enhanced decision-making.

Historical and real-time data collected from IoT devices and analytical and diagnostic tools help extend the availability, reliability and usable life of physical assets.

Equipment lifecycles are extended through more informed maintenance strategies and by embedding risk management into business processes to improve return on investment.

IoT, AI and analytics enhance equipment maintenance practices. Asset tracking and traceability meet increasingly complex EHS requirements.

EAM helps establish a single technology system to manage virtually all asset types. Processes are unified and standardized for wide-ranging asset functions across an enterprise.

John Myers of CHS Inc. has been working with IBM® Maximo® for over 20 years and witnessed the shift in EAM to predictive maintenance. Hear why, with the cloud and IoT, he still sees new possibilities in working with Maximo.

Manage both planned and unplanned work centrally, from initial request through completion and including the recording of actuals.

Move from corrective maintenance, when repairs are made after a problem occurs, to preventive maintenance, when repairs are scheduled, and predictive maintenance, when repairs are made because data indicates imminent failure.

View work orders and preventive maintenance schedules graphically on a Gantt chart. Intuitively handle work order management to help dispatchers manage task and work dependencies.

Integrate assets and their maintenance materials into the supply chain, from sourcing to usage. Effective tools should incorporate IoT technologies that help integrate EAM with supply chain management systems.

Document and report EHS concerns. Reduce risk by using incident analysis, corrective action traceability and process change management.

Accomplish more from reading meters to capturing electronic signatures to using bar codes and radio frequency identification. Take advantage of smartphone capabilities such as photos and voice-to-text to capture information and deliver tools, documentation and collaboration.

Run extended and enhanced analytics, often powered by AI, to gain operational insights. Use optimization models to automate the planning, scheduling and work management processes based on analysis.

Support software-as-a-service (SaaS), cloud-based deployment or hybrid cloud deployment to control costs, improve system flexibility and decrease dependency on IT.

The future of EAM might be in the cloud. Hosted in the cloud, SaaS EAM offers the flexibility to expand and contract with data demands. Users pay only for the data resources they need. SaaS requires far less intervention and support from IT than on-premises deployments. As a result, capital expenses related to IT can be converted into operational expenses and resources.

Service providers make upgrades in the cloud, so the latest versions and functionality are always applied. SaaS also integrates new technologies faster and with less risk.

See why asset-intensive industry leaders use IBM Maximo EAM software.