By harnessing the power of connected hardware and the Industrial Internet of Things (IIoT), digital manufacturing can drive up the efficiency of your plant and increase your profit margins, while minimizing costly, unplanned downtime.
Predictive maintenance is a technique that has been used in manufacturing since the 1990s, but it has evolved in the age of digital transformation. Let’s walk through the different types of equipment maintenance and their differences, all of which enabled by digital manufacturing solutions.
Predictive maintenance is the ongoing analysis of the condition of manufacturing equipment. By understanding the key indicators of a breakdown, you can identify and fix problems before they occur. Through a combination of real-time data and algorithms based on past performance, you can conduct equipment maintenance at a time that is convenient for you, reducing the need for costly machine downtime.
Before components within a manufacturing line were digitally connected, a manufacturer would run manual checks, use guesswork and perform unnecessary maintenance procedures. With predictive maintenance, a real-time alert is sent to the owner of the machine indicating the likelihood of a future breakdown. This gives the owner a chance to maintain the potentially faulty part before a problem occurs, or a costly and dangerous breakdown.
Preventative maintenance is scheduled maintenance on a machine, regardless of whether the machine has shown any signs of needing it. Preventative maintenance is an effective way to maintain your production line however it can be inefficient as can result in unnecessary maintenance taking place.
Preventative maintenance does not require condition-monitoring of a machine. You would determine when to run your preventative maintenance schedules based on known lifecycles of a machine. Predictive maintenance, on the other hand, is maintenance that is planned, based on the past-performance and real-time data provided by your connected machines.
Predictive maintenance and condition-based maintenance are both forms of proactive equipment maintenance that aim to prevent the future breakdown of a machine. The difference is that predictive maintenance relies on both real-time data collected by your sensors and formulas created to predict future maintenance events. Condition-based monitoring is only based on real-time alerts, so once your machine has hit a threshold parameter level, the maintenance occurs there and then. Predictive monitoring can be thought of as intelligent condition-based monitoring.
By proactively scheduling maintenance, you do not have to risk costly and reputation-damaging outages. Unplanned machine outages can interfere with your existing production schedules and can lead to wasted raw materials, missed production deadlines and lost customers.
Predictive maintenance provides workers with the information they need to be able to schedule equipment maintenance. This means they do not need to interrupt their work to tend to an unexpected breakdown or malfunction. It also means you can schedule your equipment maintenance around your employee’s work schedules, making your workplace more efficient.
The data collected through your machine’s sensors can give your product designers vital information they need to create longer-lasting machines. Such data has never been accessible before and is invaluable information for designers to use when creating better machinery.
Predictive maintenance makes for a safer workplace. An unexpected breakdown or malfunction can lead to hazardous working conditions for factory employees. By predicting when a malfunction may occur, you can ensure your employees are nowhere near a machine as it breaks down.