With the development integration of new technology, the industrial revolution has changed the modern world completely. The knowledge of maintenance is on the way of transformation and advanced technologies are being evolved. The older method of maintenance was time-based maintenance which is proved to be an inefficient way of maintenance. The current method of maintenance is the condition-based maintenance which is adopted by most of the companies and factories.
Predictive maintenance involves the application of algorithms of machine learning and analytics to the operational data. Prescriptive maintenance is another advanced method of maintenance that works by making recommendations and also by acting on the recommendations.
Predictive Maintenance:
As said above, predictive maintenance is an advanced method on maintenance that is used to predict the time of failure of malfunctioning of the machine component. With this prediction, one can replace the component before it fails to function properly. This helps to enhance the uptime of the machine or any other equipment, and the lifetime of the machine is increased.
Why Predictive Maintenance:
Every factory comprises of old and new machinery that is required by every manufacturer. Any sudden equipment failure and unplanned downtime may show an adverse effect on the operations of the company. And the repair can be costly and time-taking. Usually, the inspection of the condition of the equipment is done only when certain damage has occurred which may pause or slow down the production lines. The predictive maintenance predicts the damage or the failure well before they fail by utilizing huge sets of data together with the evaluation of physical parameters like temperature, vibration, pressure or flow.
How does it Work?
The modern systems use the machine service and repair history the equipment to predict when the component may fail and fall below its maximum operating efficiency. With this data, one can schedule the service before the failure occurs and before it could impact the production lines.
The predictive maintenance utilizes the Internet of Things (IoT) that in turn depends on the sensors. IoT enables the working of different systems together that helps in the analysis of the data and further action can be taken. The sensors detect where the problem is going to arise and helps one to prevent the damage.
Diagnosis of the failure can be done by following the below steps:
- Gathering the data about the equipment from the factory.
- Run the data analytics on the data to locate where the failure is about to happen.
- Replacement of the component of the machine.
Benefits Of Predictive Maintenance:
- Decreases costs of maintenance.
- Prevents machine failure and downtime.
- Improves the lifetime of the equipment.
- Increased production.
- Safety of the operator.
Trends are showing that a number of companies are shifting towards predictive maintenance and are improving the automation process by installing newer technologies. Companies of various fields like oil and gas industries have already employed predictive maintenance and many others are looking forward to doing so.