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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.
 |
| Gardner |
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 |
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.
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.
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 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.
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?
People are definitely part of the solution, not part of the problem. For us, it's about executing to their new expectations and applying information and technology to find solutions to specific problems.
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.
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.
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?
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.
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 if that is critical to the operations.
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?
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.
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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