IoT is still in the early stages of being used by equipment-driven companies who deal with rental, leasing, and services. That said, companies are quickly seeing how useful IoT can be, and that goes beyond monitoring and optimizing processes, equipment performance, and customer trends. The Internet of Things, combined with data you’ve gathered about your assets over time, can make a huge difference in how companies work with predictive equipment maintenance.
For this short article, let’s get quickly to the point—if you have an equipment rental and services solution that integrates with ERP, and lets you take advantage of technologies like IoT, it’s likely that you can make dramatic improvements in your approach to predictive equipment maintenance.
The need for a data-driven approach to equipment maintenance
Changing your approach to predictive equipment maintenance is essential. Many companies have hard-baked predictive service cycles for equipment, and in many cases these aren’t based on accurate forecasting and real-time monitoring of performance and usage. Businesses try to anticipate issues, but until recently they’ve often landed in a hot zone of costly routine predictive service that isn’t really accurate about “pre-emptive strikes that anticipate problems. As a result, equipment rental and service companies can’t optimize maintenance planning and execution—if they’re good companies they literally have too much routine maintenance and too many unexpected corrective or emergency service calls.
Combine historical records and IoT for a data-driven approach to equipment maintenance
With the right software, companies can take a two-fold approach to more precise equipment maintenance. They can take historical data that they gather during equipment lifecycles—most companies have lots of wisdom about equipment types, performance, and customer scenarios. A strong ISV solution will let you analyze whatever angle you need to about equipment to put together robust but flexible predictive equipment maintenance cycles. Service will vary depending on a number of variables, but you’ll be able to standardize complex and changing cycles so that they work much more efficiently.
Just as important, you can combine historical analysis with data from IoT sensors to gain 24/7 information about equipment performance, usage, break points, working conditions—highly nuanced information. Without a huge investment, you have access to detailed information in real time that lets you plan how to service equipment effectively. IoT can also ensure that you’re instantly alerted if the unexpected does occur. Either way, you’ll be ready to handle any issue before it gets out of hand, while reducing overhead and improving ways of working.
Making Predictive Equipment Maintenance a profit center: