Predictive Maintenance has redefined the way things work in the field service management industry.
Years ago (or when the predictive maintenance concept was yet to be born), the monitoring of machinery and production plants, for the significant part, was the job of a shift worker. The job was performed by manually checking the machines for any unusual sounds, vibrations, or damage to key components.
Repairs and Maintenance were done on the spot, and if parts were needed to make the machine work as required, the ensuing downtime impacts production and impedes uptime throughout the facility.
But today, the scenario has changed. Thanks to the Internet of Things (IoT) that helps make decisions based on the data. With remote sensors and cloud-hosted applications, you can facilitate real-time monitoring and track inventory. By integrating the IoT in the production process, field service managers can make better decisions with preventive and predictive maintenance.
To help you get a better understanding, here’s are a few points about how predictive maintenance is useful in field service:
Less equipment failures
Equipment failure is something that every manager in the field service management industry wants to avoid. But how can it be possible? It can be by monitoring the conditions of all machines & equipment on a regular basis. The frequent inspection of equipment can reduce the chances of sudden machine failures by more than 60%.
By implementing a condition monitoring maintenance system in place, field managers can get access to real-time information about asset operating conditions at client’s location so that necessary action can be taken before failure happens. Predictive maintenance can help reduce unexpected machine failures by 90%, which means almost eliminating breakdowns and thereby downtime.
Increased asset lifetime
Detecting machine and system defects earlier and resolving the same on time helps in enhancing the service life of the facility machine to a great extent. Once you implement a predictive maintenance system, you not only get the power to reduce the severity of damages but also the propagation of defects. With fewer defects and timely maintenance, you can make the asset lifecycle longer.
Reduced MTTR (Mean time to repair)
Along with eliminating unexpected machine failures, predictive maintenance also reduces the time involved in repairing or reconditioning plant equipment.
As remote sensors indicate to the managers that there’s something wrong with the machine or equipment and it might lead to a major issue or breakdown, technicians can be allotted to fix the issue before it converts into bigger damage.
Predictive maintenance can reduce the meantime to repair (MTTR) by 60%.
Accurate assets data
One of the significant benefits of predictive maintenance is to power the system’s ability to use sensor data and make predictions about the mean time between failures.
With such data in hand, field managers can determine the cost-effective time to repair or replace equipment in place of scheduling costly maintenance tasks that can cost them much in the long run.
The data will help to predict when maintenance is required so that the continuing operation costs do not exceed replacement costs.
Better workplace safety
Workplace safety is one of the prime concerns of every industry. With predictive maintenance, field service managers can reduce the chances of accidents in the workplace environment related to machine failure. These accidents are not only fatal but can also lead to lawsuits with major financial impacts.
Prior detection of equipment and maintenance issues can lower the risk of catastrophic failures, eliminating the chances of injury and even death.
By eliminating the breakdown of complex machines, field service managers need to invest fewer resources in maintenance tools and services. Additionally, this will help them increase work productivity as they will be able to spare more time to focus on vital maintenance tasks.
Also, optimizing equipment conditions reduces machine downtime, which directly makes the work easier for the bottom line.
Predictive maintenance sensors help in conducting oil analysis, vibration analysis, thermal imaging, equipment observation, and more. And this is not limited to day-to-day operations but is also used to verify whether a repair is successful or not before starting the machine again.
That increases safety and eliminates the need for a second shutdown, ensuring smooth operations in industries.