Predictive maintenance uses real-time data collected via the Industrial Internet of Things (IIoT) platforms to continuously analyze the machine's condition as it operates normally so that any sudden and unexpected failure can be avoided. It allows organizations to monitor and check the status of indicators like lubricants, speed, and bearing speed. These tools detect any abnormal behavior when the machine is operating normally and immediately send the report to the owner of the machine so that any potential incident can be avoided. The body content of your post goes here. To edit this text, click on it and delete this default text and start typing your own or paste your own from a different source.
In simpler terms, predictive maintenance analyzes and monitors the health of an asset in real-time and reports abnormalities to the owner in real-time to avoid any potential failure, breakdowns, and so on. It also offers the manufacturer an option to plan maintenance as per their production schedule. agraph
Working of predictive maintenance
Predictive maintenance works in the following ways:
How is predictive maintenance different from preventive maintenance?
It occurs at regular time intervals depending on the lifecycle of the machine, irrespective of its usage, to prevent any issues.
It occurs only as needed based on the reports provided by the IoT sensors regarding the status of the machine. This allows manufacturers to schedule maintenance to avoid any sudden unexpected potential breakdowns or failures.
How is predictive maintenance different from condition-based maintenance?
This type of proactive maintenance uses sensors to collect real-time insights about a piece of machine based on various factors like temperature, vibration, and pressure. In this case, the service is only deployed when the machine conditions demand. This type of maintenance includes a risk of multiple machines needing service simultaneously.
Predictive maintenance is a type of condition-based maintenance, but it uses IIoT sensors at a larger scale to gain continuous insights into the machine's condition. Along with the equipment condition insights, it also uses big data methodologies to predict the machine degradation depending on the history of the equipment. It allows technicians to detect potential issues beforehand to avoid any potential issues and schedule maintenance more efficiently.
Key benefits of predictive maintenance
Here are the top five benefits predictive maintenance offers your organization:
Implementing predictive maintenance
Follow these steps to start with your predictive maintenance. There are several ways to do it:
Option 1: Do it yourself:
Program design
IIoT installation
You can use machines having sensors, connected to an IIoT platform to conduct predictive maintenance.
System integration
Use IIoT tools to implement predictive maintenance. The connectivity established by IIoT based condition monitoring can be used to enhance efficiency using analytics, automation, and integration between OT and IT.
Schedule maintenance
Your team is equipped with advanced real-time alerts about equipment insights for scheduling service delivery and coordinating maintenance.
Option 2: accelerate with the combined platform and data science:
Use predictive maintenance and stand apart from the competition
The ultimate and numerous benefits of
predictive maintenance will provide you an edge over your competitors. Don’t face the risk of downtime and its associated hurdles. Be proactive with your plan and service delivery using predictive maintenance.