Predictive maintenance continuously analyzes the condition of equipment during normal operations to reduce the likelihood of future failure. Through a combination of real-time data and algorithms based on past performance, you can predict when future maintenance will need to take place. Predictive maintenance drives costs down, increases efficiency, and gives manufacturers a competitive edge.
Predictive maintenance picks up on different indicators such as slow bearing speed and will proactively send real-time alerts to the owner of the machine indicating the likelihood of a future breakdown. This reduces the chance of a costly and dangerous breakdown and gives the manufacturer the opportunity to schedule maintenance around their own production schedule.
Most monitoring systems use both predictive and preventative maintenance. Preventative maintenance is scheduled based on the machine’s life-cycle regardless of whether the machine has shown any signs of needing it.
Predictive maintenance is planned based on past-performance and real-time data provided by your machines. Interconnected internet of things (IoT) sensors provide insights about machines, so as they wear over time, manufacturers can proactively schedule maintenance and avoid a costly, unexpected breakdown.
Often used interchangeably, both terms aim to prevent the future breakdown of a machine. Predictive maintenance relies on real-time data collected by IoT sensors and formulas created to predict future maintenance events. Condition-based monitoring is based on real-time alerts signaling a need for maintenance once your machine has hit a threshold parameter level. Powered by the industrial internet of things, predictive maintenance gathers intel directly from your machines to stay ahead of potential machine breakdowns.
Predictive maintenance is a transformative application of the IIoT. Advantages include:
In auto-manufacturing, for example, downtime can cost a manufacturer $1.3 million per hour. To avoid the risk of these costly and reputation-damaging outages, manufacturers can proactively schedule maintenance using predictive maintenance.
There is no need to disrupt worker productivity for an unexpected malfunction or breakdown. Predictive maintenance plans around workers’ schedules to optimize workforce efficiency.
Harness the power of the data collected through your machine’s sensors. Empower product designers to use vital information on your asset’s performance to build more efficient and longer-lasting machines in the future.
An unexpected breakdown or malfunction can lead to hazardous working conditions for your employees. By predicting when a malfunction may occur, you can ensure your employees are nowhere near a machine when it breaks down.
You no longer have to wait until your machine is down to fix it. Start being proactive at your plant with predictive maintenance and optimize your workforce efficiency. Kickstart your business’s IIoT transformation with PTC’s webcast on predictive analytics and remote monitoring or learn more about PTC’s Enterprise Operational Intelligence Solutions.