Transcript of a discussion on how a Canadian maker of containers leverages the Internet of Things to create a positive cycle of insights and applied learning.

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Manufacturer Gains Advantage
by Expanding IoT Footprint from
Many Machines to Many Insights
Transcript of a discussion on how a Canadian maker of containers leverages the Internet of
Things to create a positive cycle of insights and applied learning.
Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett
Packard Enterprise.
Dana Gardner: Hello, and welcome to the next edition of the BriefingsDirect Voice of
the Customer podcast series. I’m Dana Gardner, Principal Analyst at Interarbor
Solutions, your host and moderator for this ongoing discussion on digital transformation
success stories.
Our next manufacturing modernization and optimization case study centers on how a
Canadian maker of containers leverages the Internet of Things (IoT) to create a positive
cycle of insights and applied learning. We will now hear how CuBE Packaging Solutions,
Inc. in Aurora, Ontario has deployed edge intelligence to make 21 formerly isolated
machines act as a single, coordinated system as it churns out millions of reusable
package units per month.
Stay with us as we explore how harnessing edge data with more centralized real-time
analytics integration cooks up the winning formula for an ongoing journey of efficiency,
quality control, and end-to-end factory improvement.
Here to describe the challenges and solutions for injecting IoT
into a plastic container’s production advancement success
journey is Len Chopin, President at CuBE Packaging Solutions.
Welcome, Len.
Len Chopin: Hi, thanks for having me.
Gardner: Len, what are the top trends and requirements
driving the need for you to bring more insights into your
production process?
Chopin: The very competitive nature of injection molding
requires us to stay ahead of the competition and utilize the
intelligent edge to stay abreast of that competition. By tapping
into and optimizing the equipment, we gain on downtime
efficiencies, improved throughput, and all the things that help
drive more to the bottom line.
Chopin

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Gardner: And this is a win-win because you’re not only improving quality but you're able
to improve the volume of output. So it’s sort of the double benefit of better and bigger.
Get the information you need
Chopin: Correct. Driving volume is key. When we are running, we are making money,
and we are profitable. By optimizing that production, we are even that much more
profitable. And by using analytics and protocols for preventive and predictive
maintenance, the IoT solutions drive an increase the uptime on the equipment.
Gardner: Why are sensors in of themselves not enough to attain intelligence at the
edge?
Chopin: The sensors are reactive. They give you information. It’s good information. But
leaving it up to the people to interpret [the sensor data] takes time. Utilizing analytics, by
pooling the data, and looking for trends, means IoT is pushing to us what we need to
know and when.
Otherwise we tend to look at a lot of
information that’s not useful. Utilizing
the intelligent edge means it's pushing
to us the information we need, when
we need it, so we can react
appropriately with the right resources.
Gardner: In order to understand the benefits of when you do this well, let's talk about the
state at CuBE Packaging when you didn't have sensors. You weren't processing and
you weren't creating a cycle of improvement?
Chopin: That was firefighting mode. You really have no idea of what's running, how it’s
running, is it trending down, is it fast enough, and is it about to go down. It equates to
flying blind, with blinders on. It’s really hard in a manufacturing environment to run a
business that way. A lot of people do it, and it’s affordable -- but not very economical. It
really doesn’t drive more value to the bottom line.
Gardner: What have been the biggest challenges in moving beyond that previous
“firefighting” state to implementing a full IoT capability?
Chopin: The dynamic within our area in Canada is resources. There is lot of technology
out there. We rise to the top by learning all about what we can do at the edge, how we
can best apply it, and how we can implement that into a meaningful roadmap with the
right resources and technical skills of our IT staff.
It’s a new venture for us, so it's definitely been a journey. It is challenging. Getting that
roadmap and then sticking to the roadmap is challenging, but as we go through the
Utilizing the intelligent edge means it’s
pushing to us the information we need,
when we need it, so we can react
appropriately with the right resources.

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journey we learn the more relevant things. It's been a dynamic roadmap, which it has to
be as the technology evolves and we delve into the world of IoT, which is quite
fascinating for us.
Gardner: What would you say has been the hardest nut to crack? Is it the people, the
process, or the technology? Which has been the most challenging?
Trust the IoT process
Chopin: I think the process, the execution. But we found that once you deploy IoT, and
you begin collecting data and embarking on analytics, then the creative juices become
engaged with a lot of the people who previously were disinterested in the whole process.
But then they help steer the ship, and some will change the direction slightly or identify a
need that we previously didn't know about – a more valuable way than the path we were
on. So people are definitely part of the solution, not part of the problem. For us, it’s about
executing to their new expectations and applying the information and technology to find
solutions to their specific problems.
We have had really good buy-in with the people, and it’s just become about layering on
the technical resources to help them execute their vision.
Learn How to Automate and
Drive Insights
From Your IIoT Data and Apps
Gardner: You have referred to becoming, “the Google of manufacturing.” What do you
mean by that, and how has Hewlett Packard Enterprise (HPE) supported you in gaining
that capability and intelligence?
Chopin: “The Google of manufacturing” was first coined by our owner, JR. It’s his vision
so it’s my job to bring it to fruition. The concept is that there’s a lot of cool stuff out there,
and we see that IoT is really fascinating.
My job is to take that technology and turn
it into an investment with a return on
investment (ROI) from execution. How is
that all going to help the business? The
“Google of manufacturing” is about growth
for us -- by using any technology that we
see fit and having the leadership to be
open to those new ideas and concepts.
Even without having a clear vision of the roadmap, it means focusing on the end results.
It’s been a unique situation. So far it’s been very good for us.
“The Google of manufacturing” is
about growth for us – by using any
technology that we see fit and
having the leadership to be open to
those new ideas and concepts.

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Gardner: How has HPE helped in your ability to exploit technologies both at the edge
and at the data center core?
Chopin: We just embarked on a large equipment expansion [with HPE], which is
doubling our throughput. Our IT backbone, our core, was just like our previous
equipment -- very old, antiquated, and not cutting edge at all. It was a burden as
opposed to an asset.
Part of moving to IoT was putting in a solid platform, which HPE has provided. We work
with our integrator and a project team that mapped out our core for the future. It’s not
just built for today's needs -- it's built for expansion capabilities. It's built for year-two,
year-three. Even if we’re not fully utilizing it today -- it has been built for the future.
Learn How to Automate and
Drive Insights
From Your IIoT Data and Apps
HPE has more things coming down the pipeline that are built on and integrated to this
core, so that there are no real limitations to the system. No longer will we have to scrap
an old system and put a new one in. It’s now scalable, which we think of as the platform
for becoming the “Google of manufacturing,” and which is going to be critical for us.
Gardner: Future-proofing infrastructure is always one of my top requirements. All right,
please tell us about CuBE Packaging, your organization’s size, what you're doing, and
what end products are.
The CuBE takeaway
Chopin: We have a 170,000-square-foot facility, with about 120 employees producing
injection-molded plastic containers for the food service industry, for home-meal
replacement, and takeout markets, distributed to Canada as well as the US, which is
obviously a huge and diverse market.
We also have a focus on sustainability. Our products are reusable and recyclable. They
are a premier product that come with a premier price. They are also customizable and
brandable, which has been a key to CuBE’s success. We partner with restaurants, with
sophisticated customers, who see a value in the specific branding and of having a robust
packaging solution.
Gardner: Len, you mentioned that you're in a competitive industry and that margin is
therefore under pressure. For you to improve your bottom line, how do you account for
more productivity? How are you turning what we have described in terms of an IoT and
data capability into that economic improvement to your business outcome?

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Chopin: I refer to this as having a plant within a plant. There is always lot more you can
squeeze out of an operation by knowing what it’s up to, not day-by-day, but minute-by-
minute. Our process is run quite quickly and so slippage in machine cycle times can
occur rapidly. We must grasp the small slippages, or predict failures, or when something
is out of technical specifications from the injection molding standpoint or we could be
producing a poor-quality product.
Getting a handle on what the machines are doing, minute-by-minute-by-minute gives us
the advantage to utilize the assets and the people and so to optimize the uptime, as well
as improve our quality, to get more of the best product to the market. So it really does
drive value right to the bottom line.
Gardner: A big buzzword in the industry now is artificial intelligence (AI). We are seeing
lots of companies dabble in that. But you need to put in place certain things before you
can take advantage of those capabilities that not only react but have the intelligence to
prescribe new processes for doing things even more efficiently.
Are you working in conjunction with your integrator and HPE to allow you to exploit AI
when it becomes mature enough for organizations like your own?
AI adds uptime
Chopin: We are already embarking on using sensors for things that were seemingly
unrelated. For example, we are picking up data points off of peripheral equipment that
feed into the molding process. This provides us a better handle on those inputs to the
process, inputs to the actual equipment, rather than focusing on the throughput and of
how many parts we get in a given day.
For us, the AI is about that equipment uptime
and of preventing any of it going down. By
utilizing the inputs to the machines, it can notify
us in advance, when we need to be notified.
Rather than monitoring equipment performance manually with a clipboard and a pen, we
can check on run conditions or temperatures of some equipment up on the roof that's
critical to the operation. The AI will hopefully alert us to things that we don't know about
or don't see because it could be at the far end of the operations. Yet there is a
codependency on a lot of that pre-upstream equipment that feeds to the downstream
equipment.
So for us to gain transparency into that end-to-end process and having intelligence built-
in enough to say, “Hey, you have a problem -- not yet, but you're going to have a
problem,” allows us to react before the problem occurs and causes a production upset.
Gardner: You can attain a total data picture across your entire product lifecycle, and
your entire production facility. Having that allows you to really leverage AI.
For us, the AI is about that
equipment uptime and of
preventing any of it going down.

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Sounds like that means a lot of data over long period of time. Is there anything about
what's happening at that data center core, around storage, that makes it more attractive
to do this sooner than later?
Learn How to Automate and
Drive Insights
From Your IIoT Data and Apps
Chopin: As I mentioned previously, there are a lot of data points coming off the
machines. The bulk of it is useless, other than from an historical standpoint. So by
utilizing that data -- not pushing forward what we don't need, but just taking the relevant
points -- we piggyback on the programmable logic controllers to just gather the data that
we need. Then we further streamline that data to give us what we're looking for within
that process.
It's like pushing out only the needle from the haystack, as opposed to pushing the whole
haystack forward. That’s the analogy we use.
Gardner: So being more intelligent about how you gather intelligence?
Chopin: Absolutely! Yes.
Gardner: I’m afraid we’ll have to leave it there. We have been exploring how a Canadian
maker of containers is leveraging IoT to create a positive cycle of insights and applied
learning. And we've learned how harnessing edge data in centralized, real-time analysis
can cook up a winning formula for an ongoing journey of efficiency, quality control, and
ongoing, end-to-end factory improvement.
Please join me in thanking our guest, Len Chopin, President at CuBE Packaging
Solutions in Aurora, Ontario. Thank you so much, Len.
Chopin: Thanks for having me.
Gardner: And a big thank you as well to our audience for joining this BriefingsDirect
Voice of the Customer digital transformation success story. I’m Dana Gardner, Principal
Analyst at Interarbor Solutions, your host for this ongoing series of Hewlett Packard
Enterprise-sponsored interviews.
Thanks again for listening. Please pass this along to your IT community, and do come
back next time.
Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Hewlett
Packard Enterprise.

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Transcript of a discussion on how a Canadian maker of containers leverages the Internet of
Things to create a positive cycle of insights and applied learning. Copyright Interarbor Solutions,
LLC, 2005-2019. All rights reserved.
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