Moving toward smart maintenance with prescriptive analytics

As companies adopt cloud-based, Software-as-a-Service systems such as Computerized Maintenance Management Software (CMMS), there is an opportunity to move beyond preventive or predictive maintenance. Prescriptive maintenance is the next big step forward in the evolution of asset management. In fact, the ability to connect assets and feed information into a central system gives organizations the power to turn data into powerful insights and automatically take corrective, preventive or predictive action.

In the future of prescriptive analytics, machines will be able to diagnose themselves, and communicate when to perform certain “restorative” or “discard” preventive maintenance tasks (PM). Today, there are only two types of PMs: Scheduled Restoration and/or Scheduled Discard. Using the concept of predictive maintenance, these preventive maintenance tasks could be automated where it is economically advantageous as opposed to a Run to Failure strategy.

A CMMS solution works by storing asset data, automating work order and request processes, monitoring equipment using predictive maintenance, scheduling maintenance work and resources, recording inventory levels, and providing management with reports in order to make data-driven decisions. CMMS can be effective for any organization that is constantly working on reactive maintenance and unable to do preventive maintenance, frustrated with tracking and managing spare parts inventory, having difficulty with providing documentation for regulatory compliance, or wasting time on costly manual processes for tracking maintenance.

As companies embrace the Internet of Things and CMMS, there is greater opportunity to take control of operations, quality and safety. The ability to connect assets and feed information into a central system gives organizations the power to turn data into powerful insights and automatically take corrective, preventive or predictive action.