Big Data Analytics Optimizes HPP Equipment, Processes
Springing in large part from its acquisition of HPP equipment provider Avure a few years ago, JBT’s iOPS cloud-based performance optimization platform helps to improve utilization, visibility, and control in HPP facilities.
JBT has developed iOPS to provide performance optimization across not only its Avure HPP offerings but across its full equipment line.
Photo courtesy of JBT
When JBT acquired Avure Technologies in early 2017, it gave the high-end equipment supplier for the food and beverage industry an entrée into the increasingly popular field of high-pressure processing (HPP). Avure was known for its HPP systems, and JBT could see the potential for market adoption of the cold pasteurization technology in the protein and liquid food sectors that it served.
From Avure’s perspective, they gained access to some considerable resources—applied not only to equipment development but also to communication and data analytics tools that Avure had been working on, according to Tim Boyle, JBT Avure’s director of customer care and support. From that sprang iOPS, a cloud-based performance optimization platform that analyzes JBT equipment and processes in real time. The overall equipment effectiveness (OEE) software was created to improve utilization, visibility, and control in HPP facilities.
Boyle explains how iOPS is evolving and why it’s important to HPP tolling customers and the food industry beyond.
PFW: Tell me how iOPS came about. Why develop this OEE solution in-house?
Tim Boyle, JBT AvurePhoto courtesy of JBTBoyle: We wanted to develop something in-house that could go across the entire JBT product line. JBT has been purchasing companies like Avure and growing through acquisition but also growing the base, so we’ve got different operating systems, different platforms, throughout all of our equipment. It made sense to the IT guys at the time to look at how we could use one base tool that can go across all the platforms to keep that control in-house.
We look at iOPS as a dual-fold benefit for both the customer and for us. The customer can get real-time operational performance data—they can get alarm histories, they can get a lot of different analytic data—brought back to them on a nice, clean dashboard. But also, we get to collect data on our machines on the backside with a cloud solution, so it allows us to keep looking at the overall picture of all of our equipment out there and start developing some different features along the way that can do things like predictive maintenance. And we can develop better tools so we can continue to improve performance for the customer along the way.
PFW: How do your customers feel about all of that data being fed to the cloud?
Boyle: The nice thing about utilizing the cloud solution is we work with a lot of different security functions. We’ve got military-grade, airport-grade security functionality in the cloud. And the nice thing about utilization of the cloud vs. utilizing direct access into the machine is that the customer’s machine is transmitting data to the cloud, and we’re pulling the data and doing the business analytics in the cloud solution. So we’re not interfacing with the customer network. We’re also not interfacing directly into their equipment, so it protects the customer.
We have some customers that are still wary of the data security. So the primary focus for us is making sure all data communications, all interfaces are completely secure to protect the customer. We also make sure all the data between the customer is proprietary—we don’t share that data with anybody. When we look at machines, we’re consolidating and we’re not pulling customer information into the consolidation; it’s just looking at machine data, so it’s random and anonymous. There’s no risk to their proprietary or customer information.
PFW: Was iOPS developed specifically for HPP or is it being applied to other processes as well?
Boyle: We were working on our own solution for HPP [at Avure], and then we got acquired by JBT. Now iOPS is across all of JBT’s product lines. If we’ve got a customer that has multiple JBT pieces of equipment in their buildings, we can have one iOPS solution and even travel through dashboards based on which machine you want to look at.
PFW: Tell me more about what iOPS offers to JBT equipment users.
Boyle: We are still kind of in our infancy with iOPS. But what the customers are getting is a nice clean dashboard where they can look at all the data analytics. We’re using a system called Power BI [a data visualization tool from Microsoft]. Once we get the data in the cloud, we’re going back and looking at the data, and we’re reporting operational efficiency, uptime, alarm histories, if they have anything that’s causing the machine to have downtime—anything that’s going on. We can monitor any sensor—anything in that machine—and report on it and graph it.
JBT has developed iOPS to provide performance optimization across not only its Avure HPP offerings but across its full equipment line.Photo courtesy of JBT
For example, on our machines, we have some thermal gauges, and we can get a readout on those thermal gauges and say, ‘OK, if we start seeing a trend above a certain temperature, it means you’re starting to get a water leak in the system.’ We can pinpoint that water leak based on that sensor and tell the customer they need to take a look at this particular part and do maintenance on it in advance.
PFW: What are examples of how your customers are making use of iOPS?
Boyle: We’re working with some key customers now that are really utilizing the system very well. There’s a customer in the Netherlands called Pascal Processing, and then we’ve got a customer in Ohio that is called Hydrofresh. Both of them are tolling customers, so they provide HPP services and other services to customers.
Those customers make their money based on how many pounds of product they can run through, and how efficiently they can run it. So iOPS gives them the tools to really monitor and check their systems to keep looking for better efficiency improvements, better throughput improvements and less downtime.
PFW: What sorts of things have they been able to achieve?
Boyle: With Pascal, we were able to find that they were kind of starving the machine. The machine was up and available, but they weren’t utilizing it as much as they should. So they are changing how they prepare their process equipment or product to get it ready for the machine. They were able to increase their overall throughput because they were seeing that their operation in advance of the machine wasn’t feeding it at the right rates.
We were also able to look at their alarm histories and see that they were actually triggering an alarm breaking the light curtain when they were offloading material. Every time they’d have to break the light curtain, they’d have to go back and reset it, and the machine would stop running. It was something we were able to reconfigure with them and have them do the offload outside of the light curtain system.
It’s just a simple thing that was causing a lot of downtime and delays. But they weren’t aware of it. Once management saw what was going on, they were able to address it and keep the machine running more consistently.
PFW: How do you see iOPS continuing to evolve?
Boyle: What we really want to get to is predictive maintenance. As we collect more and more data, we’re going to start seeing: OK, this is the trend that started right before a part needed to be replaced.
We want to continue to kind of home in and mine all that data to give predictive responses to customers. Today, we already send out to the systems an email saying you’re coming up on your 4,000-cycle service, or you’re coming up on your 3,000-cycle service. We send that email to them about 200 cycles prior to them needing the maintenance. But we want to evolve to give real-time responses back to the customers saying, ‘Hey, you’ve got a temperature issue on this check valve on this intensifier on this side of the machine. You need to get that maintained right away before it does any further damage.’
We’re seeing it evolve to be more of an interactive response back to customers to get them prepared to keep the machine running as much as possible.
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Tim Boyle, JBT AvurePhoto courtesy of JBT
