By Eric Lund, Burr Oak Tool, Inc.
The Industrial Internet of Things (IIoT) has been on the radar now for a year or two. Yet companies still wonder what the best implementation approach might be. As a veteran machine builder, I have been watching evolving trends with regard to digitalization, automation and IIoT in order to plan how Burr Oak Tool, Inc. would implement them in our own equipment and services. Our goal was to get ahead of our customers by becoming familiar in IIoT implementations before being deluged by requests for such functionality as the technology transitions beyond the early adopter stage.
Our initial focus was on data gathering. We realized we had to ensure our machines shipped with the necessary networking hardware installed to facilitate IIoT. Therefore, we began to design our solutions to collect relevant data in a single location – within the processor. This allows our customers to easily access the information they need. Another important element of our IIoT plan was to not only add its capabilities to our new-build machines, but to be able to add or retrofit it into our machines already in the field.
We were initially worried about having to add analytics capabilities into our machines. Instead, we came to understand our role in the overall IIoT spectrum as making data available to customer or third-party analytics engines. Analytics tools have been devised over many years and contain logic that could take us years to perfect. Why reinvent the wheel when you can provide a smooth data path that transports the customer along the IIoT journey? This approach kept us aligned to our core competencies.
Fulfilling Customer IIoT Needs
Each customer has different requirements for IIoT. One user of our machines simply wanted to be able to count the number of strokes made by our presses. By gaining access to this information, they could more efficiently schedule tooling maintenance on actual usage rather than by the calendar. This began as a relatively straightforward project. But word quickly got around. Other departments within our customer’s organization soon began requesting additional information be made available from their machines.
We realized that once people see the benefits from having data they can use to make more informed decisions, they’ll want more. This was a good learning experience. We understood that we had to design something that could be easily expanded in functionality. That’s why we house all data from our machines in a single memory area inside the processor. Network servers can then be programmed to gather whatever data they need and at the time intervals they require.
Further, we learned to be more flexible in our IIoT designs in order to encompass both old and new architectures. For example, the Siemens Simotion D425 controller we use in some of our equipment is variable based rather than using memory addressing. To smooth the transition to IIoT, we added a Siemens S7-1200 PLC to communicate with the D425. This provided the addressed-based memory we use as our IIoT standard.
Another example: early versions of the D425 lacked an Ethernet port. We incorporated the Siemens CBE 20 Profinet module to provide the ports we needed. Quite a few of our older machines out in the field also had PLCs without a Profinet port, only Profibus. In those cases, we took advantage of the Siemens CP 343-1 Lean module to add Profinet capabilities.
A new technology field such as IIoT can seem overwhelming. By breaking it down into meaningful steps or phases, it becomes much easier to implement workable solutions. Our strength, after all, has always been in building machines. We are now extending our IIoT capabilities by devising ways to provide our machine data to data analytics and visualization platforms such as MindSphere. This is helping us to gain a valuable foothold into the emerging world of digitalization.
Our partnership with Siemens is expanding our horizons. One customer, for example, is interested in exploiting IIoT for analytics. As we are already a long-term Siemens Automation user, Siemens MindSphere is the obvious choice as a data analytics and visualization platform to make a complete IIoT solution available to our customers.
MindSphere will help our customers in many different directions. It will help them find ways to operate our machines more efficiently. They will be able to access machine and sensor data to initiate predictive maintenance programs based on actual usage rather than arbitrary time periods. They will be able to detect faults based on equipment or component health warnings to prevent unscheduled downtime. They can use MindSphere to plan more effectively and streamline the flow of products through their plants. By tracking equipment trends, they will be able to identify where to improve machine operation and performance, and when to engage in operator training. Additionally, as a machine builder, we can gather far more information on machine performance to improve our own designs.
As MindSphere is available as a cloud solution, it will simplify the development path toward IIoT. Data storage, analytics, and visualization can all be accomplished in the cloud without having to architect an internal solution. Siemens has the hardware needed to get data into the cloud. In our case, we have been able to utilize Siemens Nano IPCs and Siemens S7-1500 Advanced Controllers to gather data from our machine processors and transmit it to the cloud.
By working closely with Siemens, Burr Oak Tool is finding smart ways to retrofit IIoT capabilities into our older machines, and design new capabilities into our latest offerings.Have an Inquiry for Siemens about this article? Click Here >>