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Predictive maintenance services
The Internet of Things (IoT) is revolutionizing field services. Manufacturers are using IoT to obtain usage and status data from sensors embedded on their equipment at customer sites. This data, continuously analyzed by streaming and predictive analytics, enables manufacturers to offer predictive maintenance services to help customers maximize uptime, predict maintenance needs and reduce maintenance costs.
What are predictive maintenance services?
Predictive maintenance services monitor the condition of a machine, component or product to predict when it is going to break down or fail and to prevent the problem from occurring
Why use predictive maintenance?
Increasingly, companies use predictive maintenance to differentiate from the competition and create new recurring revenue streams, offering products on a subscription basis. Predictive maintenance services improve key efficiency metrics for field services like first-call repair rate, costs to serve and customer lifetime value. They also increase customer loyalty and satisfaction by preventing costly downtime.
Sample use cases
A machine manufacturer deployed predictive maintenance services to eliminate downtime for products at customer sites. This IoT solution provides the manufacturer with:
- Real-time monitoring of various operational parameters on its equipment
- Real-time fault detection
- Remote equipment configuration
- Customized management of operational and technical dashboards
With predictive maintenance-as-a-service, the company has established a new benchmark in rapid equipment servicing while also switching to a cost-effective, usage-based pricing model.
Another manufacturer embedded sensors in its products to innovate new ways to use IoT to benefit customers. The manufacturer collects live data on conditions like temperature and vibration to proactively show customers how equipment is performing, how to prevent downtime, how to improve ROI, and what maintenance is needed to avoid service trips.
Key considerations
When choosing an IoT platform for predictive maintenance services, ask:
- Is the platform self-service, or will you need an army of developers to use it?
- Will you be able to connect equipment easily?
- Will you be locked into a particular vendor’s technology stack, including infrastructure, hardware and proprietary systems?
- Will you be able to integrate IoT data easily with your core systems and processes?
- Will you be able to evolve and expand your solution based on how your needs change over time?
- How easily can you define advanced rules so you can monitor and act on events?
- Will you have access to expertise to help you build a proof of concept and prove its value?
Benefits of predictive maintenance services
Predictive maintenance allows manufacturers to monitor equipment performance that leverages real-time sensor data. With it, you’ll gain an understanding of historical data and current and predicted equipment availability as an overall measure of equipment effectiveness. You can predict maintenance failures and get alerts about maintenance when needed, as opposed to a suggested schedule.
In short, you can:
- Increase customer satisfaction through improved service levels at reduced costs
- Optimize reliability and performance of equipment on customer sites
- Create new revenue models and methods of competing
Software AG’s Cumulocity IoT platform uniquely provides the capabilities you need to deliver predictive maintenance services. You’ll be able to:
- Connect to hundreds of device types and protocols, including LPWAN, out of the box
- Run your solution in the cloud, on-premises, at the edge, or any combination
- Quickly connect to third-party applications and enterprise systems to share data and integrate processes, often without coding
- Use the leading streaming analytics engine, pre-integrated into Cumulocity IoT
- Securely serve many customers without worry of improper data access, thanks to true multi-tenancy
In addition, Software AG offers Professional Services to help you achieve faster time-to-value with predictive maintenance.
