In my role I talk a lot about the benefits of digitalization. But the data delivered by #IoT brings so many possibilities with it, that it’s hard for anyone to talk about them all. And of course different organisations find value in different benefits, but generally, one that is relevant to every customer I speak to is predictive maintenance.
Traditionally, manufacturers use the age of their machinery to determine maintenance cycles. Checks, services and replacements are carried out at regular scheduled intervals in the hope of pre-empting equipment failure.
But technology does not always behave in the way that we expect it to. So, unexpected faults or failures not caught by the pre-determined maintenance schedule can surprise manufacturers with potentially massive unexpected costs. Costs not only relating to fixing or even replacing the faulty equipment but also of having a machine out of action for days or weeks.
The data delivered by IoT offers the chance to spot warning signs of these problems before they occur. Machines no longer simply perform their primary function, they are now equipped to trigger decisions and technical assistance.
How is this achieved? MindSphere – our cloud-based IoT operating system – analyses real-time digital data streams from equipment and alerts manufacturers to impending faults that humans can’t see. These could be vibration indicators, or product quality starting to reach the boundaries of acceptable quality. By spotting problems early, down time and maintenance costs are significantly reduced because problems can be solved before they occur.
Now, we are taking this innovation one step further. This data – shared via MindSphere - is not only used to monitor equipment performance – it is also used to align the cost of the technology with the benefits it brings.
In collaboration with the customer, a minimum production volume is agreed (which the production line almost never undershoots). Smart performance finance then introduces a pay-for-performance rate for production in excess of this minimum. MindSphere monitors a machine’s performance, and the customer pays for that performance accordingly.
For me, this is a game-changer in helping manufacturers that want to invest in digitalization but are concerned about investing a fixed monthly charge when they have variable production levels. Being able to pay for performance helps manage the investment risk. It also means that when the data indicates a problem that needs attention, the machine’s drop in production level will be reflected in its cost.
Predictive maintenance is a benefit of digitalization where all manufacturers can see immediate value. Nevertheless, the technology that makes it possible requires investment. By connecting finance with the digital world we are helping more businesses embrace digitalization sustainably.
Siemens Financial Services
Head of Region West, Commercial Finance