The Internet of Things (IoT) is revolutionizing field services. Companies are using IoT to get usage and status information from sensors embedded on the gear of theirs at customer sites. This information, constantly analyzed by streaming and predictive analytics, allows companies to provide predictive maintenance solutions to assist clients maximize uptime, predict maintenance requirements and lower maintenance costs.
What are predictive maintenance services?
Predictive maintenance software monitors the problem of a machine, item or element in order to foresee when it’s likely to digest and break and also to keep the issue from occurring.
Why install predictive maintenance?
Frequently, companies utilize predictive maintenance to differentiate from the competition and build brand new recurring revenue streams, providing items for a membership basis. Predictive maintenance services improve performance metrics that are key for field services like first call repair rate, expenses to deliver and also client lifetime value. Additionally they increase satisfaction and customer loyalty by preventing expensive downtime.
Sample use cases
A computer manufacturer deployed predictive maintenance solutions to eliminate downtime for things at client sites. This IoT solution offers the company with:
Real-time monitoring of various functional parameters on the equipment of its
Real-time fault detection
Remote equipment configuration
Customized management of technical and operational dashboards
With predictive maintenance, the company has created an innovative benchmark in quick equipment taking care of while additionally changing to a cost effective, usage based pricing model.
Another manufacturer embedded receptors in its products to innovate fresh methods to make use of IoT to help customers. The company collects fresh information on problems as vibration and heat to proactively show customers the way equipment is doing, exactly how to avoid downtime, how to enhance ROI, and also what maintenance is necessary to stay away from service trips.
Crucial considerations
When selecting an IoT platform for predictive maintenance services, ask:
Is the platform self service, or perhaps will you want an army of developers to utilize it?
Will you have the ability to link equipment easily?
Will you be locked right into a specific vendor’s technology stack, such as proprietary, hardware, and infrastructure systems?
Will you be in a position to incorporate IoT data effortlessly with the core methods of yours and processes?
Will you be in a position to develop and grow your answer based on the way your requirements change over time?
Exactly how quickly are able to you determine superior rules to help you monitor and act on events?
Will you’ve access to expertise that will help you develop a proof of principle and prove its worth?
Benefits of predictive maintenance services
Predictive maintenance allows companies to monitor equipment performance which leverages real time sensor data. With it, you will acquire an understanding of historical details and present and also predicted equipment availability as a general way of measuring equipment effectiveness. You are able to predict maintenance problems for alerts about maintenance when necessary, compared to a suggested schedule.
In a nutshell, you can:
Increase customer satisfaction through better service levels at reduced costs
Optimize performance and reliability of gear on customer sites
Create new revenue models and strategies of competing
Software AG’s Cumulocity IoT platform exclusively supplies the skills you have to provide predictive maintenance services. You will have the ability to:
Link to plenty of unit types and protocols, including LPWAN, from the box
Run the option of yours within the cloud, on premises, at the edge, and any combination
Instantly link to third party applications and enterprise systems to talk about information and integrate processes, typically without coding
Use the top streaming analytics engine, pre integrated into Cumulocity IoT
Securely serve lots of customers with no worry of incorrect data access, because of real multi-tenancy