April 7, 2026 • 25 mins
Most plants already have more data than they know what to do with. The hard part is turning that operational data into clear decisions that prevent downtime, boost reliability, and make the work on the floor feel less like constant firefighting. We close out our manufacturing deep dive by getting brutally practical about “insights to impact” and why data-driven manufacturing only counts when it changes what we do next.
We talk through how modern intelligent devices shift maintenance from guesswork to evidence. Smart overload relays and connected diagnostics can capture trip snapshots, fault history, and operating status so teams can stop debating symptoms and start fixing root causes. We share a real example where repeated nuisance trips on a grinder motor looked like motor degradation until diagnostics showed the equipment was being overfed, creating unnecessary stress and premature failures. That’s the kind of insight that saves real money because planned downtime beats unplanned downtime every time.
From there, we zoom out to the first steps that actually work: start with critical assets, add intelligent sensing (current, vibration, temperature, power monitoring), and make the data visible through dashboards or mobile access so it doesn’t live in a silo. We also dig into the human side of industrial automation and predictive analytics: how digital tools reduce clipboard work, raise job satisfaction, preserve institutional knowledge as veterans retire, and help attract a new generation that expects intuitive interfaces.
If you want a clear path to predictive maintenance, smarter troubleshooting, and better plant decisions, hit play, then subscribe, share the show with a colleague, and leave a review so more manufacturing teams can find it.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_00 (00:00):
Welcome to Eco Ask Why, a podcast that dives into
industrial manufacturing topicsand spotlights the heroes that
keep America running.
I'm your host, Chris Granger,and on this podcast, we do not
cover the latest features andbenefits on products that come
to market.
Instead, we focus on advice andinsight from the top minds of
(00:20):
industry because people andideas will be how America
remains number one inmanufacturing in the world.
Welcome to Eco Ask Why.
I'm your host, Chris Granger.
Look forward to spending sometime with you today.
And this is kind of this episodean episode where we're going to
be wrapping up this dive intoindustrial manufacturing that
(00:43):
we've been doing for the lastnine or ten months.
It's been a really fun to takethese topics each and every
month and unpack them for you.
Hopefully, you found a lot ofvalue out of it.
We've talked about howeverything's been involving so
much in industrial manufacturingand starting with the workforce
directly and the skill set, thetalent that's needed to move
(01:04):
industrial manufacturing in thefuture.
We spent some time talking aboutdigital twins.
That was a fun dive as westarted thinking about how
digital twins could be utilizedto simulate operational success
and validation and training andthings like that.
We talked about predictive powerof AI agents and what that could
look like in manufacturing andjust had some fun unpacking that
(01:27):
at length.
Then we spent some time over acouple months really diving into
industrial control panelsspecifically because there's so
many core components that wewant to make sure that you were
familiar with and understood.
We talked about electricalsafety, reliability,
(01:48):
connectivity, data acquisition.
Then we also did a little diveinto industrial cybersecurity
and what does that look like andthings we need to be thinking
about these days.
And then most recently we talkedabout data-driven manufacturing,
and that leads us into this.
And today we're going to havetalk really discuss how we can
take these insights that we getfrom all this data that's
(02:10):
available to us and transferthat to impact.
Okay, so insights to impact, uh,because it comes down to
decision making and fulfillingwhat engineering is requiring of
us in manufacturing today.
And while the technicalfoundation of a digital twin
provides really great frameworkfor simulation and modeling,
(02:32):
let's just think about what theultimate goal.
The ultimate goal of adata-driven manufacturing is
bigger than that, right?
Because the real transformationoccurs when that operational
data becomes the digitalfoundation for our leadership,
for the decisions that we make.
That empowers the engineers, thetechnicians, the plant managers
to make faster, smarterdecisions.
(02:55):
And in modern manufacturingenvironments, data should not
simply record what has alreadyhappened.
Okay.
It should instead provideinsight needed to shape what
decisions are made next.
Okay, you see how that works?
Then when it's properlyimplemented, that digital
infrastructure reduces theoperational stresses that we all
(03:17):
feel.
It also improves our systemreliability and creates a more
rewarding and impactful careerpath for people that are
thinking about coming into theindustrial manufacturing space.
And this is what we're allabout.
We want to encourage as manypeople as we can to come into
industrial manufacturing becausewe see there's so much value to
be had here, and there's so muchvalue when we keep producing
(03:40):
more.
Okay, so now we're going to talkabout informed decision making,
okay, and how thinking about thedata that comes in, how we can
move beyond reactivemaintenance.
So in the traditionalmanufacturing environment,
operational data functions as alike a like a post-mortem tool.
(04:00):
Think about it like that, right?
So we we study stuff after itfails, and there's there's value
in that.
And maintenance teamstroubleshoot and restore
production, and they then theyjust move on, right?
And without fully understandingthe root cause uh of the
ultimate instruction thathappened.
But modern intelligent devicesare changing that dynamic very
(04:24):
quick, very quickly.
I mean, you have components likeRockwell has these electronic
overload relays, and Eaton hasthe same thing as well.
Yeah, Scowa has these differenttypes of devices as well.
All the different manufacturersout there, they give us
transform transformative data tohelp us take the action that we
need, right?
And it really become an activeoperational asset, really, we
(04:47):
start thinking about it.
Because these devices providecritical diagnostics
information.
So we're talking about tripsnapshots and operational status
monitoring and fault histories,everything that happened, as
well as motor protectionanalysis.
I mean, so the information canbe accessed directly at the
device level or remotely througha secure web interface.
(05:10):
This is really the technology,it's just it blows you away.
And what the result is you havea very different troubleshooting
process.
So instead of guessing whatcaused a motor failure, your
teams now have the abilitythrough data to identify what
occurred and uh ultimatelyaddress the underlying issue
(05:34):
that could have led to thatfailure.
Right?
And when you start thinkingabout this, and we've we've
we've seen instances at anelectrical equipment company
where a railroad manufacturerwas having a bunch of repeat
nuisance trips over this thislarge grinder motor.
And the assumptions suggestedthat the equipment failure uh or
(05:55):
uh it suggested that it was likea motor degradation.
But after doing somediagnostics, we were able to
under to determine that reallywhat was happening is that the
equipment was being overfed.
Okay, and that and since theequipment was being overfed, uh
that was putting an undue stresson that equipment and leading to
(06:17):
the premature failures, right?
And once you've identified thatissue, right, then you can make
the necessary adjustments andeliminate the problem.
Then in this case, they save asignificant amount of
unnecessary uh downtime onequipment and replacement costs.
So it's using technology thisway, like the intelligent
(06:38):
diagnostics, that transformsmaintenance from reactive to uh
oh, this machine just brokedown.
Wait a minute, what can we do toget ahead of it so that we're
not having this issue in thefuture, you know, and moving to
more proactive, you know,because that that plan downtime
is so much more cost effectivethan the unplanned.
(07:02):
And so, what does this look likeon a plant floor?
So, for many manufacturers, thepath forward uh towards like
this data-driven operationsbegins with practical steps,
right?
This we're not talking aboutcoming in trying to change the
the whole culture overnight, butjust small additions, small
steps of intelligence toexisting equipment to generate
(07:25):
meaningful insights.
So you may want to like consideradding a smart motor overload
relay to uh to start recordingwhen you do have those motor
trips so you can startdiagnosing them.
Maybe you want to start puttingsome power monitoring devices to
uncovering some hit hiddenenergy inefficiencies that may
(07:45):
be out there.
Uh, they have some really greattechnology these days in
vibration sensors.
Uh, so you start detectingbearing wear before a failure
happens.
And if you integrate all thesedashboards together and start
pulling this data in a way in away that a maintenance
technician can actually consumeit and understand, right, then
they can start making real-timeequipment health decisions.
(08:08):
So instead of treating eachmachine or piece of equipment as
an isolator assets, you couldutilize this technology to turn
the equipment into informationsources through a connected
system.
You see that that startschanging the game when you start
thinking of it that way andstart approaching decision
making in such a manner.
And and manufacturers out thereoften begin by applying these
(08:32):
tools to really think about it.
I want to go what's criticalfirst.
I want to go what's criticalfirst and what's going to give
me the biggest impact on return.
I'm going to prove it there,okay?
Because then if that works out,man, then then I can replicate
that throughout my plan, right?
And scale it out.
So this is kind of consider thislike an incremental strategy
(08:56):
because this allows you as anorganization to build that
digital foundation withoutdisrupting existing operations
and just build it out fromthere.
Because at the end of the day,we're trying to go from
proactive to reactive operationsbecause we it's expensive to
firefight in industrialmanufacturing.
And one of the most significantadvantages of intelligent
(09:19):
monitoring systems, like we'retalking about, is their ability
to move this from this uhreactive to uh a more proactive.
And historically, if you start,I mean, I've been in plants my
whole life, and I and you seethis happen.
Maintenance departments operatewith a firefighting mentality.
(09:39):
This is just what works.
So something breaks down thattriggers a request for repair,
and technicians respond, okay?
And you have to respond wheneverit happens, right?
And this is why it's gonna bevery much like a firefighter
mentality, and productionschedules and operations always
have to adjust to accommodatethis on plan downtime.
(10:01):
Okay, so this is a big deal, bigdeal.
But when you start incrementinguh implementing real-time
monitoring and predictiveanalytics, that changes
everything, okay?
Because when we start thinkingabout this, these platforms,
again, they're they're they'repulling in, they're monitoring
data on a continuous basis, andthey're analyzing these
(10:23):
variables like vibration andmotor current and temperature
and energy and all these things.
And those systems give you theability to detect early
indicators of any type ofpotential failure long before
that the moment of where theequipment goes down completely.
(10:44):
So instead of just think abouthow much better of an operation
inside plant would be if theyinstead of had they they weren't
responding to 3 a.m.
down calls.
Right?
What if their maintenance teamscould schedule repairs during
this these planned downtimewindows where you can manage the
(11:04):
cost much more efficiently?
Production managers can gain agreater scheduling confidence
doing this, and what you'removing towards is a greater
predictability and stuff andstability within the plant.
And that's what that there'spower with that.
So if you start automating andmonitoring these different data
points simultaneously, you startbuilding a self-correcting
(11:29):
operational environment wherethese problems are identified
long before they becomedisruptive.
Okay, we're not going toeliminate the problems, but we
just want to know what they areso that we can we can address
them directly.
And then there's we fulfill thisthrough the innovation that
keeps happening.
So despite concerns thatautomation might reduce the
(11:50):
importance of people, right?
The opposite is proving to betrue in modern manufacturing.
Data-driven systems aretransforming the nature of
engineering and maintenanceroles.
So they're they're just they'rechanging, they're shifting up.
As automated systems do starthandling repetitive monitoring
(12:11):
tasks like data collection, sowe're not walking around with a
clipboard as much, you know,fault logging and inventory
tracking, things like that.
What we're able to do for thepeople that were doing those
tasks was elevate them to highervalue challenges that require
creativity and analysis andstrategic thinking, the things
that make us uh a valuable partof industrial manufacturing.
(12:36):
This evolution, this evolutionis changing the nature of
industrial careers in somemeaningful ways because it's
reducing redundancy.
So these digital tools eliminatethese outdated manual processes
that like clipboard-basedinspections, right, or hand
maintenance or handwrittenrather maintenance logs.
So technicians now can insteadthey can access the detailed
(13:00):
equipment diagnostics directlyfrom digital dashboards or even
phones now.
I mean, this is crazy how thetechnology has really shifted.
And what we're doing is we'reempowering problem solving
because with access to real-timeoperational metrics and
performance projections, such asOEE, right, overall equipment,
equipment effectiveness,engineers and technicians are no
(13:24):
longer limited to repairing justmachines.
They can proactively identifyopportunities to improve system
efficiency and reliability.
And at the same, all along, whatthis is what this is really
doing inside of industrialmanufacturing, and I don't think
we can just fly by this, you'reincreasing job satisfaction.
So employees, right, they'rebeing trained to walk to work
(13:47):
alongside these intelligentsystems, and they're they're
finding opportunities to expandtheir career, to learn, to bring
more value.
So instead of just maintainingthis equipment, they become
system optimizers and innovativetype thinkers within their
organization.
And this is this is great.
It's a wonderful step for us.
(14:09):
So now we have to think abouthow we preserve this knowledge
and we and bridge thegenerational gap because
manufacturing, it is facing asignificant workforce challenge.
It has faced this for years.
You have people retiring andexperienced technicians moving
out, and this stuff is not beingtransferred, right, at
oftentimes uh through throughapprenticeship programs and
(14:29):
things like that, through allhands-on experiences.
Uh, and and historically, uhpeople within industrial
manufacturings develop uh likeum an intuitive type of
understanding of machinebehavior because they were just
around, they were listening,they were talking to each other,
they would and they could theycould understand these subtles,
(14:51):
these subtle warning signsbefore problems escalated.
And those people, you know,bless them, you know, that
they're they're we're findingthis less and less of those
types of capable type of peoplein these manufacturing
facilities, but now the digitalmonitoring systems start helping
elevate this and extending thiseffort expertise because the
(15:13):
monitoring systems themselvesare starting to capture these
patterns and histories andtrends and and and and they
document this knowledge, right?
This does not just go on and golive in, say, one individual,
but it's experience for it's anopera, it's an opportunity for
everyone to tap into that.
Okay, so it's really cool whenat the same time, younger
(15:37):
workers that are coming to theindustry are comfortable with
these interfaces.
Okay, because think about it,they grew up on them, they grew
up with tablets and smartphonesand things like that.
So when you have these intuitivedisplays and mobile-friendly
accessibility and uh userinterfaces to like smartphones
and tablets, you're just makingit so much easier to draw in
(15:59):
people into the into theindustry directly.
So this is a combination ofcaptured institutional
knowledge, right, and intuitivedigital tools that bridge the
generational divide that used tobe there.
And when we lean into it and wethink of it that way, it changes
everything, right?
And this also makesmanufacturing careers more
(16:20):
attractive to a new generationof engineers and technicians and
operators, and that's reallycool.
That is really cool.
So you have to get started.
You know, you get started, youbuild a digital foundation.
So if you're thinking right now,uh, like how do I take the
things you're talking abouthere, Chris?
(16:41):
How do I take this and implementthis in a strategic way?
I'm gonna give you three thingsto consider, okay?
First, we've already talkedabout it to some degree, but
identify those critical assets.
Focus on where the downtimecarries the greatest operational
cost or production risk.
If you just identify that,that'll give you the area that
(17:01):
that where attention needs to begiven.
Second, start looking atintelligent sensing.
So there's different smartdevices out there.
Look, an electrical equipmentcompany, we would love to come
and talk to you about this andand and walk through you with
you through this decision-makingprocess because you can start
deploying these smart devicesthat maybe you want to look at
(17:23):
motor currents, or maybe youwant to look at vibration or
temperature or powerconsumption, whatever it may be,
we can help you figure that out.
But that intelligent sensing isbig.
And then third, this is wherethe rubber meets your road.
Make the data visible, ensurethat the operational insights
are accessible throughdashboards or maybe integrated
(17:43):
control systems or mobiledevices so that engineers,
engineers, and maintenance teamscan act on that information.
Like you don't want it justliving in a silo for one or two
people to understand.
No, you want you want to getthis uh deployed so that it can
be adopted and then you startbuilding advocates, okay?
So even incremental improvementsand visibility, as small as you
(18:07):
may think they are, incrementalincrement uh improvements in
visibility dramatically reducetroubleshooting time and starts
increasing reliability andstarts building advocacy, okay?
So at EECO, this is what we'rethis is what we do.
We have a role in helping youenable data-driven manufacturing
because we work withmanufacturers across multiple
(18:29):
industries, from wood processingto food production to metals to
packaging to chemical, pharmaacross the board.
And we're helping these manythese these different types of
manufacturers begin thistransition.
And many organizations start bylooking at these key motor
control systems with intelligentdevices.
(18:52):
And we have the partners, wehave Rockwell, we have Eaton, we
have all the vendors in place,the the strategic partners
aligned to walk with you to helpyou enable deeper visibility
into quim into equipmentperformance without requiring
ripping everything out andredoing it.
We're talking about strategicintegration of intelligent
(19:15):
components, and then you can beable to gradually build a
digital infrastructure thatsupports predicted maintenance,
helps improve operationaldecision making, and sets you up
for long-term systemreliability.
So at the end of the day, wehave to turn data into decisions
(19:35):
that leaders make.
And the future of manufacturingwill not be defined solely by
faster machines or increasedautomation.
That's gonna be a great part ofit, but it's not what it's gonna
be.
It's gonna be defined howeffectively organizations
convert operational data intoinformed decision making.
(19:56):
Because when that data becomesvisible, contextual, and then
moves to actionable, that's whenthe game changes.
That's when engineers andtechnicians gain the clarity
needed to move from thistroubleshooting, firefighting
mentality towards continuousimprovement to give you a
competitive advantage, to add toyour edge in the market.
(20:20):
It's a competitive market welive in.
This is what this is this is apractical way to gain an edge
because the real promise ofdigital manufacturing is not
simply operational efficiency,it's the ability to create an
environment where people canlead the systems instead of
chasing problems, and that'swhere insights become impact.
(20:45):
So we really hope you've enjoyedthis dive into industrial
manufacturing.
And look, at ElectricalEquipment Company, we have so
many, so many skilled, talented,incredible people that would
love to come alongside from thehighly technical roles to
storerooms to what you name it,procurement.
(21:05):
We're here to help.
We're here to serve, we're hereto connect.
And we even have labs.
We have labs built, designed, sothat you can come in and get
hands-on and understand how thetechnology works, to lower your
risk profile, to increase yourconfidence so that when you add
this technology into yourfacility, you're doing it from a
(21:26):
place of understanding, notguesswork.
We want to take that guessworkout of it.
So schedule some time with us.
We'd love for you to come intoone of our labs.
We'll have bring in uh somesandwiches and sit down and get
the brass tacks onto what helpyou need and let us be a part of
designing that with you.
So just reach out.
So ecoonline.com, you canconnect with us there.
(21:49):
We have system planninginformation.
We have lots of ways youconnect.
You can schedule time directly.
We'll make sure it's in the shownotes here.
You can schedule time directly,you can go on our scheduler.
And book time to come into oneof our labs to have that
personal one-on-one conversationthat could change everything.
And it could be something assmall.
It's look, I have this one lineof motors, and I really want to
(22:13):
start implementing some of thistechnology around that.
Let's think through what's areally good way to step into
that systematically.
You know, we don't want to biteoff the whole thing at once.
Well, how can we get started?
We would love to have thatconversation.
Or maybe you have some olderswitch gear and you want to
start thinking about modernizingthat and upgrading that and
(22:33):
start putting a plan togetherfor minernization.
This is what we do.
And we have the experts thatjust across the board that are
ready to sit and walk with you.
So reach out to us, okay?
EcoOonline.com.
Follow us on LinkedIn.
We have a lot of great resourceson LinkedIn as well.
We'd love to connect with youthere.
You again reach out, you canreach out to me directly.
(22:53):
You can reach out to the LetterEquipment Company.
There's all sorts of ways for usto connect and plug in, plug in
with you.
We do have a weekly new uh not aweekly, a monthly newsletter on
LinkedIn as well, so you canconnect with us there.
But ecoonline.com is the placeto go, okay?
So look, please share this stuffout.
And we really, I cannotemphasize enough how how excited
(23:15):
I am starting next month withour new episodes that are going
to be coming out.
So uh in 1926, ElectricalEquipment Company was founded.
And here we are, 100 yearslater, and we're gonna really
walk through over these upcomingmonths some stories, some some
of the things that are so coreto eco, and we just want to
(23:37):
share that with you and justgive you a peek behind the
curtain and into what has madeElectrical Equipment Company uh
just stand out for 100 years.
100 years.
I'm so excited for this.
So it's gonna be excited.
Hopefully, you'll be encouragedby it.
So thank you so much again forlistening.
Share this stuff out withothers, particularly those that
are in an industrialmanufacturing uh type of work
(24:00):
workspace.
We we would love to for to toget these reflections in front
of them because there may besomething that just just by
hearing this, maybe it's like,hey, yeah, I know exactly where
we can start.
I know it's a good it's gonna bea great launching point for uh
to for modernization, and let'slet's begin that conversation.
So share that stuff out if youdon't mind.
(24:21):
Thank you so much for listeningand for hanging out.
We'll see you next month.
And remember to keep asking why.
Thank you for listening to EcoAsk Why.
This show is supported ad-freeby Electrical Equipment Company.
EECO is redefining theexpectations of an electrical
distributor by placing peopleand ideas before products.
(24:43):
Please subscribe and share withyour colleagues and friends.
Also leave comments, feedback,and any new topic that you would
like to hear.
To learn more or to share yourinsights, visit ecosy.com that's
e co.
A S K S W H Y dot com.
Welcome to Eco Ask Why, a podcast that dives into
industrial manufacturing topicsand spotlights the heroes that
keep America running.
I'm your host, Chris Granger,and on this podcast, we do not
cover the latest features andbenefits on products that come
to market.
Instead, we focus on advice andinsight from the top minds of
(00:20):
industry because people andideas will be how America
remains number one inmanufacturing in the world.
Welcome to Eco Ask Why.
I'm your host, Chris Granger.
Look forward to spending sometime with you today.
And this is kind of this episodean episode where we're going to
be wrapping up this dive intoindustrial manufacturing that
(00:43):
we've been doing for the lastnine or ten months.
It's been a really fun to takethese topics each and every
month and unpack them for you.
Hopefully, you found a lot ofvalue out of it.
We've talked about howeverything's been involving so
much in industrial manufacturingand starting with the workforce
directly and the skill set, thetalent that's needed to move
(01:04):
industrial manufacturing in thefuture.
We spent some time talking aboutdigital twins.
That was a fun dive as westarted thinking about how
digital twins could be utilizedto simulate operational success
and validation and training andthings like that.
We talked about predictive powerof AI agents and what that could
look like in manufacturing andjust had some fun unpacking that
(01:27):
at length.
Then we spent some time over acouple months really diving into
industrial control panelsspecifically because there's so
many core components that wewant to make sure that you were
familiar with and understood.
We talked about electricalsafety, reliability,
(01:48):
connectivity, data acquisition.
Then we also did a little diveinto industrial cybersecurity
and what does that look like andthings we need to be thinking
about these days.
And then most recently we talkedabout data-driven manufacturing,
and that leads us into this.
And today we're going to havetalk really discuss how we can
take these insights that we getfrom all this data that's
(02:10):
available to us and transferthat to impact.
Okay, so insights to impact, uh,because it comes down to
decision making and fulfillingwhat engineering is requiring of
us in manufacturing today.
And while the technicalfoundation of a digital twin
provides really great frameworkfor simulation and modeling,
(02:32):
let's just think about what theultimate goal.
The ultimate goal of adata-driven manufacturing is
bigger than that, right?
Because the real transformationoccurs when that operational
data becomes the digitalfoundation for our leadership,
for the decisions that we make.
That empowers the engineers, thetechnicians, the plant managers
to make faster, smarterdecisions.
(02:55):
And in modern manufacturingenvironments, data should not
simply record what has alreadyhappened.
Okay.
It should instead provideinsight needed to shape what
decisions are made next.
Okay, you see how that works?
Then when it's properlyimplemented, that digital
infrastructure reduces theoperational stresses that we all
(03:17):
feel.
It also improves our systemreliability and creates a more
rewarding and impactful careerpath for people that are
thinking about coming into theindustrial manufacturing space.
And this is what we're allabout.
We want to encourage as manypeople as we can to come into
industrial manufacturing becausewe see there's so much value to
be had here, and there's so muchvalue when we keep producing
(03:40):
more.
Okay, so now we're going to talkabout informed decision making,
okay, and how thinking about thedata that comes in, how we can
move beyond reactivemaintenance.
So in the traditionalmanufacturing environment,
operational data functions as alike a like a post-mortem tool.
(04:00):
Think about it like that, right?
So we we study stuff after itfails, and there's there's value
in that.
And maintenance teamstroubleshoot and restore
production, and they then theyjust move on, right?
And without fully understandingthe root cause uh of the
ultimate instruction thathappened.
But modern intelligent devicesare changing that dynamic very
(04:24):
quick, very quickly.
I mean, you have components likeRockwell has these electronic
overload relays, and Eaton hasthe same thing as well.
Yeah, Scowa has these differenttypes of devices as well.
All the different manufacturersout there, they give us
transform transformative data tohelp us take the action that we
need, right?
And it really become an activeoperational asset, really, we
(04:47):
start thinking about it.
Because these devices providecritical diagnostics
information.
So we're talking about tripsnapshots and operational status
monitoring and fault histories,everything that happened, as
well as motor protectionanalysis.
I mean, so the information canbe accessed directly at the
device level or remotely througha secure web interface.
(05:10):
This is really the technology,it's just it blows you away.
And what the result is you havea very different troubleshooting
process.
So instead of guessing whatcaused a motor failure, your
teams now have the abilitythrough data to identify what
occurred and uh ultimatelyaddress the underlying issue
(05:34):
that could have led to thatfailure.
Right?
And when you start thinkingabout this, and we've we've
we've seen instances at anelectrical equipment company
where a railroad manufacturerwas having a bunch of repeat
nuisance trips over this thislarge grinder motor.
And the assumptions suggestedthat the equipment failure uh or
(05:55):
uh it suggested that it was likea motor degradation.
But after doing somediagnostics, we were able to
under to determine that reallywhat was happening is that the
equipment was being overfed.
Okay, and that and since theequipment was being overfed, uh
that was putting an undue stresson that equipment and leading to
(06:17):
the premature failures, right?
And once you've identified thatissue, right, then you can make
the necessary adjustments andeliminate the problem.
Then in this case, they save asignificant amount of
unnecessary uh downtime onequipment and replacement costs.
So it's using technology thisway, like the intelligent
(06:38):
diagnostics, that transformsmaintenance from reactive to uh
oh, this machine just brokedown.
Wait a minute, what can we do toget ahead of it so that we're
not having this issue in thefuture, you know, and moving to
more proactive, you know,because that that plan downtime
is so much more cost effectivethan the unplanned.
(07:02):
And so, what does this look likeon a plant floor?
So, for many manufacturers, thepath forward uh towards like
this data-driven operationsbegins with practical steps,
right?
This we're not talking aboutcoming in trying to change the
the whole culture overnight, butjust small additions, small
steps of intelligence toexisting equipment to generate
(07:25):
meaningful insights.
So you may want to like consideradding a smart motor overload
relay to uh to start recordingwhen you do have those motor
trips so you can startdiagnosing them.
Maybe you want to start puttingsome power monitoring devices to
uncovering some hit hiddenenergy inefficiencies that may
(07:45):
be out there.
Uh, they have some really greattechnology these days in
vibration sensors.
Uh, so you start detectingbearing wear before a failure
happens.
And if you integrate all thesedashboards together and start
pulling this data in a way in away that a maintenance
technician can actually consumeit and understand, right, then
they can start making real-timeequipment health decisions.
(08:08):
So instead of treating eachmachine or piece of equipment as
an isolator assets, you couldutilize this technology to turn
the equipment into informationsources through a connected
system.
You see that that startschanging the game when you start
thinking of it that way andstart approaching decision
making in such a manner.
And and manufacturers out thereoften begin by applying these
(08:32):
tools to really think about it.
I want to go what's criticalfirst.
I want to go what's criticalfirst and what's going to give
me the biggest impact on return.
I'm going to prove it there,okay?
Because then if that works out,man, then then I can replicate
that throughout my plan, right?
And scale it out.
So this is kind of consider thislike an incremental strategy
(08:56):
because this allows you as anorganization to build that
digital foundation withoutdisrupting existing operations
and just build it out fromthere.
Because at the end of the day,we're trying to go from
proactive to reactive operationsbecause we it's expensive to
firefight in industrialmanufacturing.
And one of the most significantadvantages of intelligent
(09:19):
monitoring systems, like we'retalking about, is their ability
to move this from this uhreactive to uh a more proactive.
And historically, if you start,I mean, I've been in plants my
whole life, and I and you seethis happen.
Maintenance departments operatewith a firefighting mentality.
(09:39):
This is just what works.
So something breaks down thattriggers a request for repair,
and technicians respond, okay?
And you have to respond wheneverit happens, right?
And this is why it's gonna bevery much like a firefighter
mentality, and productionschedules and operations always
have to adjust to accommodatethis on plan downtime.
(10:01):
Okay, so this is a big deal, bigdeal.
But when you start incrementinguh implementing real-time
monitoring and predictiveanalytics, that changes
everything, okay?
Because when we start thinkingabout this, these platforms,
again, they're they're they'repulling in, they're monitoring
data on a continuous basis, andthey're analyzing these
(10:23):
variables like vibration andmotor current and temperature
and energy and all these things.
And those systems give you theability to detect early
indicators of any type ofpotential failure long before
that the moment of where theequipment goes down completely.
(10:44):
So instead of just think abouthow much better of an operation
inside plant would be if theyinstead of had they they weren't
responding to 3 a.m.
down calls.
Right?
What if their maintenance teamscould schedule repairs during
this these planned downtimewindows where you can manage the
(11:04):
cost much more efficiently?
Production managers can gain agreater scheduling confidence
doing this, and what you'removing towards is a greater
predictability and stuff andstability within the plant.
And that's what that there'spower with that.
So if you start automating andmonitoring these different data
points simultaneously, you startbuilding a self-correcting
(11:29):
operational environment wherethese problems are identified
long before they becomedisruptive.
Okay, we're not going toeliminate the problems, but we
just want to know what they areso that we can we can address
them directly.
And then there's we fulfill thisthrough the innovation that
keeps happening.
So despite concerns thatautomation might reduce the
(11:50):
importance of people, right?
The opposite is proving to betrue in modern manufacturing.
Data-driven systems aretransforming the nature of
engineering and maintenanceroles.
So they're they're just they'rechanging, they're shifting up.
As automated systems do starthandling repetitive monitoring
(12:11):
tasks like data collection, sowe're not walking around with a
clipboard as much, you know,fault logging and inventory
tracking, things like that.
What we're able to do for thepeople that were doing those
tasks was elevate them to highervalue challenges that require
creativity and analysis andstrategic thinking, the things
that make us uh a valuable partof industrial manufacturing.
(12:36):
This evolution, this evolutionis changing the nature of
industrial careers in somemeaningful ways because it's
reducing redundancy.
So these digital tools eliminatethese outdated manual processes
that like clipboard-basedinspections, right, or hand
maintenance or handwrittenrather maintenance logs.
So technicians now can insteadthey can access the detailed
(13:00):
equipment diagnostics directlyfrom digital dashboards or even
phones now.
I mean, this is crazy how thetechnology has really shifted.
And what we're doing is we'reempowering problem solving
because with access to real-timeoperational metrics and
performance projections, such asOEE, right, overall equipment,
equipment effectiveness,engineers and technicians are no
(13:24):
longer limited to repairing justmachines.
They can proactively identifyopportunities to improve system
efficiency and reliability.
And at the same, all along, whatthis is what this is really
doing inside of industrialmanufacturing, and I don't think
we can just fly by this, you'reincreasing job satisfaction.
So employees, right, they'rebeing trained to walk to work
(13:47):
alongside these intelligentsystems, and they're they're
finding opportunities to expandtheir career, to learn, to bring
more value.
So instead of just maintainingthis equipment, they become
system optimizers and innovativetype thinkers within their
organization.
And this is this is great.
It's a wonderful step for us.
(14:09):
So now we have to think abouthow we preserve this knowledge
and we and bridge thegenerational gap because
manufacturing, it is facing asignificant workforce challenge.
It has faced this for years.
You have people retiring andexperienced technicians moving
out, and this stuff is not beingtransferred, right, at
oftentimes uh through throughapprenticeship programs and
(14:29):
things like that, through allhands-on experiences.
Uh, and and historically, uhpeople within industrial
manufacturings develop uh likeum an intuitive type of
understanding of machinebehavior because they were just
around, they were listening,they were talking to each other,
they would and they could theycould understand these subtles,
(14:51):
these subtle warning signsbefore problems escalated.
And those people, you know,bless them, you know, that
they're they're we're findingthis less and less of those
types of capable type of peoplein these manufacturing
facilities, but now the digitalmonitoring systems start helping
elevate this and extending thiseffort expertise because the
(15:13):
monitoring systems themselvesare starting to capture these
patterns and histories andtrends and and and and they
document this knowledge, right?
This does not just go on and golive in, say, one individual,
but it's experience for it's anopera, it's an opportunity for
everyone to tap into that.
Okay, so it's really cool whenat the same time, younger
(15:37):
workers that are coming to theindustry are comfortable with
these interfaces.
Okay, because think about it,they grew up on them, they grew
up with tablets and smartphonesand things like that.
So when you have these intuitivedisplays and mobile-friendly
accessibility and uh userinterfaces to like smartphones
and tablets, you're just makingit so much easier to draw in
(15:59):
people into the into theindustry directly.
So this is a combination ofcaptured institutional
knowledge, right, and intuitivedigital tools that bridge the
generational divide that used tobe there.
And when we lean into it and wethink of it that way, it changes
everything, right?
And this also makesmanufacturing careers more
(16:20):
attractive to a new generationof engineers and technicians and
operators, and that's reallycool.
That is really cool.
So you have to get started.
You know, you get started, youbuild a digital foundation.
So if you're thinking right now,uh, like how do I take the
things you're talking abouthere, Chris?
(16:41):
How do I take this and implementthis in a strategic way?
I'm gonna give you three thingsto consider, okay?
First, we've already talkedabout it to some degree, but
identify those critical assets.
Focus on where the downtimecarries the greatest operational
cost or production risk.
If you just identify that,that'll give you the area that
(17:01):
that where attention needs to begiven.
Second, start looking atintelligent sensing.
So there's different smartdevices out there.
Look, an electrical equipmentcompany, we would love to come
and talk to you about this andand and walk through you with
you through this decision-makingprocess because you can start
deploying these smart devicesthat maybe you want to look at
(17:23):
motor currents, or maybe youwant to look at vibration or
temperature or powerconsumption, whatever it may be,
we can help you figure that out.
But that intelligent sensing isbig.
And then third, this is wherethe rubber meets your road.
Make the data visible, ensurethat the operational insights
are accessible throughdashboards or maybe integrated
(17:43):
control systems or mobiledevices so that engineers,
engineers, and maintenance teamscan act on that information.
Like you don't want it justliving in a silo for one or two
people to understand.
No, you want you want to getthis uh deployed so that it can
be adopted and then you startbuilding advocates, okay?
So even incremental improvementsand visibility, as small as you
(18:07):
may think they are, incrementalincrement uh improvements in
visibility dramatically reducetroubleshooting time and starts
increasing reliability andstarts building advocacy, okay?
So at EECO, this is what we'rethis is what we do.
We have a role in helping youenable data-driven manufacturing
because we work withmanufacturers across multiple
(18:29):
industries, from wood processingto food production to metals to
packaging to chemical, pharmaacross the board.
And we're helping these manythese these different types of
manufacturers begin thistransition.
And many organizations start bylooking at these key motor
control systems with intelligentdevices.
(18:52):
And we have the partners, wehave Rockwell, we have Eaton, we
have all the vendors in place,the the strategic partners
aligned to walk with you to helpyou enable deeper visibility
into quim into equipmentperformance without requiring
ripping everything out andredoing it.
We're talking about strategicintegration of intelligent
(19:15):
components, and then you can beable to gradually build a
digital infrastructure thatsupports predicted maintenance,
helps improve operationaldecision making, and sets you up
for long-term systemreliability.
So at the end of the day, wehave to turn data into decisions
(19:35):
that leaders make.
And the future of manufacturingwill not be defined solely by
faster machines or increasedautomation.
That's gonna be a great part ofit, but it's not what it's gonna
be.
It's gonna be defined howeffectively organizations
convert operational data intoinformed decision making.
(19:56):
Because when that data becomesvisible, contextual, and then
moves to actionable, that's whenthe game changes.
That's when engineers andtechnicians gain the clarity
needed to move from thistroubleshooting, firefighting
mentality towards continuousimprovement to give you a
competitive advantage, to add toyour edge in the market.
(20:20):
It's a competitive market welive in.
This is what this is this is apractical way to gain an edge
because the real promise ofdigital manufacturing is not
simply operational efficiency,it's the ability to create an
environment where people canlead the systems instead of
chasing problems, and that'swhere insights become impact.
(20:45):
So we really hope you've enjoyedthis dive into industrial
manufacturing.
And look, at ElectricalEquipment Company, we have so
many, so many skilled, talented,incredible people that would
love to come alongside from thehighly technical roles to
storerooms to what you name it,procurement.
(21:05):
We're here to help.
We're here to serve, we're hereto connect.
And we even have labs.
We have labs built, designed, sothat you can come in and get
hands-on and understand how thetechnology works, to lower your
risk profile, to increase yourconfidence so that when you add
this technology into yourfacility, you're doing it from a
(21:26):
place of understanding, notguesswork.
We want to take that guessworkout of it.
So schedule some time with us.
We'd love for you to come intoone of our labs.
We'll have bring in uh somesandwiches and sit down and get
the brass tacks onto what helpyou need and let us be a part of
designing that with you.
So just reach out.
So ecoonline.com, you canconnect with us there.
(21:49):
We have system planninginformation.
We have lots of ways youconnect.
You can schedule time directly.
We'll make sure it's in the shownotes here.
You can schedule time directly,you can go on our scheduler.
And book time to come into oneof our labs to have that
personal one-on-one conversationthat could change everything.
And it could be something assmall.
It's look, I have this one lineof motors, and I really want to
(22:13):
start implementing some of thistechnology around that.
Let's think through what's areally good way to step into
that systematically.
You know, we don't want to biteoff the whole thing at once.
Well, how can we get started?
We would love to have thatconversation.
Or maybe you have some olderswitch gear and you want to
start thinking about modernizingthat and upgrading that and
(22:33):
start putting a plan togetherfor minernization.
This is what we do.
And we have the experts thatjust across the board that are
ready to sit and walk with you.
So reach out to us, okay?
EcoOonline.com.
Follow us on LinkedIn.
We have a lot of great resourceson LinkedIn as well.
We'd love to connect with youthere.
You again reach out, you canreach out to me directly.
(22:53):
You can reach out to the LetterEquipment Company.
There's all sorts of ways for usto connect and plug in, plug in
with you.
We do have a weekly new uh not aweekly, a monthly newsletter on
LinkedIn as well, so you canconnect with us there.
But ecoonline.com is the placeto go, okay?
So look, please share this stuffout.
And we really, I cannotemphasize enough how how excited
(23:15):
I am starting next month withour new episodes that are going
to be coming out.
So uh in 1926, ElectricalEquipment Company was founded.
And here we are, 100 yearslater, and we're gonna really
walk through over these upcomingmonths some stories, some some
of the things that are so coreto eco, and we just want to
(23:37):
share that with you and justgive you a peek behind the
curtain and into what has madeElectrical Equipment Company uh
just stand out for 100 years.
100 years.
I'm so excited for this.
So it's gonna be excited.
Hopefully, you'll be encouragedby it.
So thank you so much again forlistening.
Share this stuff out withothers, particularly those that
are in an industrialmanufacturing uh type of work
(24:00):
workspace.
We we would love to for to toget these reflections in front
of them because there may besomething that just just by
hearing this, maybe it's like,hey, yeah, I know exactly where
we can start.
I know it's a good it's gonna bea great launching point for uh
to for modernization, and let'slet's begin that conversation.
So share that stuff out if youdon't mind.
(24:21):
Thank you so much for listeningand for hanging out.
We'll see you next month.
And remember to keep asking why.
Thank you for listening to EcoAsk Why.
This show is supported ad-freeby Electrical Equipment Company.
EECO is redefining theexpectations of an electrical
distributor by placing peopleand ideas before products.
(24:43):
Please subscribe and share withyour colleagues and friends.
Also leave comments, feedback,and any new topic that you would
like to hear.
To learn more or to share yourinsights, visit ecosy.com that's
e co.
A S K S W H Y dot com.
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