My husband works for a company that makes machines used for milk, beer and wine production. His customers are usually small businesses, where sometimes the only worker is the owner himself.
Since he works in electrical and software design, I often ask him why his company is not developing an Industrial Internet of Things (IIoT) solution to embed in its machines to provide additional services to its customers.
“You know, Dear,” he tells me, “the people who we sell our machines to sometimes do not even know how to turn on a computer.”
When he answers like this, I try to explain him that—from my point of view—what he says it is not really the right answer. Though it’s true that sometimes his customers are not particularly familiar with technology, they are still quite aware of their sensitivity to price and performance, to waste and other issues that could be controlled or even solved by adding the right software to a machine. Any resistance to technology would be overcome by showing the total savings that a company could get by adopting such a solution.
In my experience, I’ve seen OEMs integrating IIoT solutions with their machines—to provide additional services or to sell the machine itself as a service based on its performance outcome. They are using these solutions as leverage to differentiate themselves from other companies selling the same kind of machines.
For an OEM producing series machines or machines very similar to others, developing or buying a solution from a third party to integrate this kind of service is not a big investment compared with the benefits and income it can generate.
But let’s see a more detailed example on how an OEM could benefit from IIoT:
- Performance: Clearly monitoring the machine performance, an OEM can demonstrate to its customers the added value that the machine is providing to production. New business models are growing that sell machines as a service, basing the price on the machine’s performance.
- Maintenance: If the machine is connected online and the data is accessible to the OEM, the OEM can collect data on how the machine is working and, if an anomaly is detected, can warn the customer and take the required corrective actions.
- Big Data analysis: If data are collected from all the machines all over the world, a huge data set can be obtained. With this, it is possible for the OEM to calculate statistics to understand how to improve the machine design process. This data set is usually big enough to enable even a global complex predictive maintenance strategy.
And now let’s see the benefits a final customer can get from these solutions:
- Performance: Clearly monitoring the machine performance, the customer can tune its process to reduce the process lead time, the waste and the downtime. If the end user bought the machine as a service, it will not pay for machine production defects and will know that the OEM has put all its efforts into producing a properly functioning machine; and that any problems will be resolved promptly.
- Maintenance: Correctly elaborating the collected data, it is easy to recognize possible machine failures in advance using predictive maintenance. Also, by allowing the OEM to collect data from the machine, the OEM can analyze the data and suggest any kind of required maintenance.
- Big Data analysis: Sharing the data of its machine, the customer can take advantage of insights coming from the analysis of the data collected globally that the OEM will be able to perform. Statistics and KPIs could allow the user to benchmark itself against competitors, or each machine’s performance vs. the others if he has more than one connected machine, line or plant.
I really believe that the future will follow this direction—that being able to adapt and introduce this kind of solution from the beginning is a sign of believing in the progress and of being a visionary, but also just understanding the need to stay competitive in the market.
The possibilities presented by introducing new software technologies in machine development are huge, and we’ve only just started to scratch the surface.
Elisa Costa is a software engineer at Autoware, a certified Control System Integrators Association (CSIA) member based in Vicenza, Italy; and is in business development at Autoware Digital. For more information about Autoware, visit its profile on the Industrial Automation Exchange.
