What is predictive maintenance?
Predictive maintenance continuously analyzes the condition of connected assets and equipment to reduce the likelihood of unplanned downtime or machine failure. It is a transformative application of the IIoT (Industrial Internet of Things) with tremendous advantages for your organization.
Decreased downtime: Predictive maintenance enables technicians to detect issues in advance and resolve problems before equipment failure can occur.
Greater worker productivity: There is no need to disrupt worker productivity for an unexpected malfunction or breakdown. Predictive maintenance plans around workers’ schedules.
Reduced field service costs: By anticipating machine maintenance, service departments can generate major cost-savings and increased ROI (Return on Investment).
Improved product design: Harnessing the power of IIoT data collected through your machine’s sensors, product designers can use this vital information.
Improved worker safety: An unexpected breakdown or malfunction can lead to hazardous working conditions for your employees. By predicting when a malfunction may occur, service can be carried out before a machine becomes dangerous.
How predictive service works and why is it important?
Through a combination of real-time collected data, predictive maintenance continuously analyzes the condition of equipment during normal operations to identify potential machine failure.
Watch this 3-minute video to find out how organizations can monitor and test various indicators such as bearing speed, lubrication, and temperature using predictive maintenance, and learn more about the latest trends in service operations in the report linked below.
Predictive maintenance vs condition based monitoring
Although both forms of proactive maintenance are aimed at preventing machine failure, there is a significant difference between condition-based and predictive maintenance. Condition-based maintenance uses sensors to collect real-time measurements from equipment about various conditions, such as temperature, pressure, or vibration. While predictive maintenance is a type of condition-based maintenance, it uses the constant stream of IIoT sensor data on a much larger scale.
Learn about the 4 phases of AI adoption and how service leaders are applying service optimization strategy to transform the predictive maintenance process in Part 1 and Part 2 of this Emerj report.
Transform service outcomes with predictive maintenance
Up to a
Drop in unplanned downtime
Up to
Faster service resolutions
Up to
Less time on site
Combine machine data and AI to deliver predictive maintenance
Unplanned downtime reduces your customers’ productivity and requires costly truck rolls to resolve. Predict and prevent failures before they happen, coordinate onsite visits, and minimize disruptions with a machine learning predictive maintenance strategy. PTC’s technology helps you monitor performance with IoT connectivity, use AI to predict problems, and even simulate conditions during the design process—making your products more reliable in the field.